# CEO.com > CEO.com is a journal of leadership. We cover the leaders shaping our world. Public Ghost content for AI and LLM tooling. This file includes a bounded export of public pages first, then recent public posts. Append `.md` to any post or page URL to get the content in Markdown (for example, `/example-post.md`). ## Pages ### The leaders shaping our world URL: https://www.ceo.com/home-hero/ Last updated: 2026-08-15T19:48:51.000Z [Start watching](https://www.ceo.com/episodes/) [Meet the guests](https://www.ceo.com/guests/) ### Episodes URL: https://www.ceo.com/episodes-index/ Last updated: 2026-08-15T20:05:03.000Z _No content available._ ### Writings URL: https://www.ceo.com/blog-index/ Last updated: 2026-09-02T18:32:43.000Z _No content available._ ### About CEO.com URL: https://www.ceo.com/about/ Last updated: 2026-09-01T00:10:49.000Z CEO.com is a journal of leadership. We cover the leaders shaping our world. A few thousand people make decisions that reach into billions of lives. Most of what's written about them is either an advertisement or an attack. We cover leaders accurately. We also give them a fair platform to explain themselves plainly, without manipulative editing or sensationalism. ### Why we exist Trust in business media has eroded, for good reason. Too much coverage falls into one of three traps. - Stories built to generate clicks or controversy rather than to inform. - Algorithmic thought leadership that carries none of the actual voice of the leader it claims to represent. - Access journalism that protects the relationship at the public's expense. We believe there is a better way. ### Our approach It isn't our job to tell you what to think. It's to give an honest account of how leaders operate in the real world: the decisions, the trade-offs, the failures, the genuine wins, and the costs behind them all. - **We ask real questions and leave room for real answers.** An interview is not an interrogation, and it is not a favor. We ask what matters and we let people finish. - **If you're criticized on our platform, we'll publish your response unedited.** Any leader critiqued on our platform is invited to reply, at length, with the same care we give everyone else. This is not a courtesy we extend selectively. - **We show our work.** We make our stance clear, we source what we can, and we correct our errors promptly, completely, and in public. - **Nobody buys our coverage.** No advertiser, sponsor, investor, business partner, or member influences what we publish. ### More than a publication We believe leadership is learned and practiced in community, not in isolation. CEO.com extends beyond our journalism into membership: a community of leaders, live events and dinners in rotating cities, and Boards of eight to twelve peers who meet monthly. We gather leaders who show up, give more than they take, and learn what no piece of content can ever teach. ### Our promise Accurate, unvarnished coverage. A published correction every time we get it wrong, and a published response every time someone is criticized on our platform. If we ever fail at either, please tell us at **hello@ceo.com**, and we'll fix it in the open. ### The community for leaders. URL: https://www.ceo.com/support/ Last updated: 2026-09-01T21:54:58.000Z _No content available._ ### Join the community for leaders. URL: https://www.ceo.com/join-community/ Last updated: 2026-09-04T16:56:46.000Z _No content available._ ### Guests URL: https://www.ceo.com/guests/ Last updated: 2026-09-01T20:00:29.000Z _No content available._ ### Your Library URL: https://www.ceo.com/library/ Last updated: 2026-08-14T17:27:21.000Z _No content available._ ### Contact URL: https://www.ceo.com/contact/ Last updated: 2026-09-15T17:37:00.000Z ## What’s it about? #### Pitch a guest Who should we interview next? [Submit Form](https://www.ceo.com/podcast-guest-submission-form/) #### Sponsor the show Reach a global audience of CEOs and leaders [partners@ceo.com](mailto:partners@ceo.com) #### Press & Media Interviews, quotes, and press kit requests. [press@ceo.com](mailto:press@ceo.com) #### Everything else Feedback, corrections, or just to say hi. [hello@ceo.com](mailto:hello@ceo.com) ### Terms of Use URL: https://www.ceo.com/terms-of-use/ Last updated: 2026-08-18T18:04:42.000Z **Last Updated: August 18, 2026** These Terms of Use govern your access to and use of CEO.com, including all content, features, newsletters, podcasts, livestreams, events, community programs, and services offered by CEO.com ("CEO.com," "we," "our," or "us"). By accessing or using this site, you agree to be bound by these terms. If you do not agree, do not use this site. ## **1\. About CEO.com** CEO.com is a journal of leadership published by CEO.com LLC. Our mailing address is 42 West Center St., Provo, Utah 84664. ## **2\. Eligibility** You must be at least 13 years old to use this site. If you are under 18, you may use the site only with the involvement of a parent or guardian. By using the site, you represent that you meet this requirement. ## **3\. Your Account** Some features of CEO.com require you to create an account. You are responsible for maintaining the confidentiality of your login credentials and for all activity that occurs under your account. You agree to notify us immediately at contact@ceo.com if you suspect unauthorized use of your account. We are not liable for any loss resulting from unauthorized use of your account. ## **4\. Subscriptions** Subscription pricing, features, and availability are subject to change. We will notify active subscribers of any material changes to their tier in advance. ### **Billing and Renewal** Paid subscriptions are billed in advance on a monthly or annual basis, depending on the plan you select. Your subscription will automatically renew at the end of each billing period unless you cancel before the renewal date. By subscribing, you authorize us to charge your payment method on a recurring basis. ### **Cancellation** You may cancel your subscription at any time through your account settings or by contacting us at contact@ceo.com. Cancellation takes effect at the end of your current billing period. We do not provide refunds for partial billing periods. ### **Refunds** All subscription fees are non-refundable except where required by applicable law or at our sole discretion. ## **5\. Events, Livestreams, and Community Programs** CEO.com hosts events, livestreams, dinners, and mentorship programs. Participation in any CEO.com community program is subject to these terms and any additional terms presented at registration. Participation in the CEO.com community confers no editorial benefit. Attending our events, joining our programs, or otherwise supporting our work does not entitle you to favorable coverage, advance notice of stories, or any influence over editorial decisions, as described in our Editorial Charter. Events and livestreams may be recorded, photographed, and published. By attending or appearing at a CEO.com event or livestream, you consent to the recording and publication of your appearance, likeness, and remarks in connection with our content and promotion, unless we agree otherwise in writing before the event. We reserve the right to refuse or revoke event registration and program participation at our discretion. ## **6\. Content and Intellectual Property** All content published on CEO.com is the property of CEO.com, LLC and is protected by United States and international copyright law. You may share links to our content. You may not reproduce, republish, copy, distribute, sell, or create derivative works from our content without prior written permission, except as permitted under fair use or other applicable law. To request permission to reproduce CEO.com content, contact us at contact@ceo.com. ## **7\. No Professional Advice** CEO.com publishes journalism about business, markets, politics, technology, and the people who lead them. Nothing on this site constitutes investment, financial, legal, tax, or professional advice, and no content should be relied upon as a recommendation to buy, sell, or hold any security or asset, or to make any business, legal, or financial decision. We do not endorse companies, products, funds, or investments. You are responsible for your own decisions, and you should consult qualified professionals before acting on anything you read here. ## **8\. User Conduct** When using CEO.com, including comment sections or any interactive features, you agree not to: Post content that is defamatory, harassing, threatening, obscene, or unlawful. Impersonate any person or entity. Interfere with or disrupt the site or its servers. Use automated tools to scrape, crawl, or harvest content. Attempt to gain unauthorized access to any part of the site. Use the site to manipulate or attempt to manipulate any market or security. Use the site for any commercial purpose without our written consent. We reserve the right to remove any user-submitted content and to terminate accounts that violate these terms at our discretion and without notice. ## **9\. Comments, Letters, and User Submissions** Certain subscription tiers include the ability to comment on articles. CEO.com also accepts personal essays for publication in our Letters section, submitted to letters@ceo.com. By submitting a comment, a Letter, or any other content to CEO.com, you grant us a non-exclusive, royalty-free, perpetual, worldwide license to use, display, reproduce, edit for length and clarity, and distribute that content in connection with the operation of the site. You retain ownership of your submissions. Submitting a Letter does not guarantee publication. Letters are selected at our editorial discretion and published in the author's own voice. The views expressed in Letters are the author's, not ours. You are solely responsible for any content you submit. You represent that your submissions are your own original work, that they are factually accurate to the best of your knowledge, and that they do not infringe on the rights of others. Do not submit content that you do not have the right to share. ## **10\. Third-Party Links and Services** CEO.com may contain links to third-party websites or services. We do not endorse and are not responsible for the content, privacy practices, or terms of those sites. Your use of third-party sites is at your own risk. ## **11\. Disclaimer of Warranties** CEO.com is provided on an "as is" and "as available" basis without warranties of any kind, express or implied. We do not warrant that the site will be uninterrupted, error-free, or free of viruses or other harmful components. We make no warranty regarding the accuracy, completeness, or reliability of any content published on the site. ## **12\. Limitation of Liability** To the fullest extent permitted by law, CEO.com, LLC and its officers, employees, contributors, and agents shall not be liable for any indirect, incidental, special, consequential, or punitive damages arising from your use of or inability to use the site, including any trading, investment, or business losses, even if we have been advised of the possibility of such damages. Our total liability to you for any claim arising from these terms or your use of the site shall not exceed the amount you paid to us in the twelve months preceding the claim. ## **13\. Indemnification** You agree to indemnify and hold harmless CEO.com, LLC and its officers, employees, contributors, and agents from any claims, damages, losses, liabilities, and expenses (including reasonable attorneys' fees) arising out of your use of the site, your violation of these terms, or your violation of any third-party rights. ## **14\. Privacy** Your use of the site is also governed by our Privacy Policy, which is incorporated into these terms by reference. Please review our Privacy Policy at CEO.com/privacy. ## **15\. Changes to These Terms** We may update these Terms of Use from time to time. When we do, we will update the "Last Updated" date at the top of this page. For material changes, we will provide notice to registered users by email or through a notice on the site. Your continued use of the site after any changes constitutes your acceptance of the updated terms. ## **16\. Governing Law** These terms are governed by the laws of the State of Utah, without regard to its conflict of law provisions. Any disputes arising under these terms shall be resolved in the state or federal courts located in Utah County, Utah, and you consent to personal jurisdiction in those courts. ## **17\. Contact** If you have questions about these Terms of Use, contact us at: CEO.com LLC 42 West Center St. Provo, Utah 84663 contact@ceo.com ### Privacy Policy URL: https://www.ceo.com/privacy/ Last updated: 2026-08-18T18:09:33.000Z CEO.com, LLC ("CEO.com," "we," "our," or "us") operates CEO.com and is committed to being straightforward about how we collect, use, and protect your information. This Privacy Policy explains what data we collect when you visit our site, subscribe to our publications, contribute to civic bounties, attend our events, or interact with our content, and what we do with it. By using CEO.com, you agree to the practices described in this policy. If you do not agree, please do not use the site. ## **1\. Information We Collect** ### **Information You Give Us** When you create an account, subscribe, contribute to a civic bounty, register for an event, submit a Letter, or contact us, you may provide: Your name and email address. Payment information, including credit or debit card details. This is processed by our third-party payment processor and is not stored on our servers. Event registration details, such as dietary preferences or accessibility needs, when you register for an in-person event. Content you submit for publication, including Letters and comments. Any other information you choose to provide when contacting us. ### **Information We Collect Automatically** When you visit CEO.com, we may automatically collect certain information about your device and how you interact with the site, including: Your IP address and general location. Browser type and version. Operating system. Pages visited, time spent on pages, and referring URLs. Links clicked and content accessed. Date and time of your visit. We collect this information through cookies, web beacons, and similar tracking technologies, described further in Section 5. ### **Information from Third Parties** We may receive information about you from third-party services we use to operate the site, including our payment processor, email delivery provider, event registration and livestream platforms, and analytics services. We only receive what is necessary to provide our services. ## **2\. How We Use Your Information** We use the information we collect to: Provide, operate, and improve the site and our publications. Process your subscription and send you what you paid for, including newsletters and subscriber content. Process civic bounty contributions and administer the escrow, disclosure, and refund commitments described in our Terms of Use. Register you for events and livestreams and communicate with you about them. Review and publish content you submit, including Letters. Send you service-related communications, such as receipts, renewal notices, and account updates. Send you editorial content and newsletters consistent with your subscription tier. Respond to your questions and requests. Monitor and analyze how the site is used so we can make it better. Detect and prevent fraud, abuse, and security incidents. Comply with our legal obligations. We do not use your personal information to make automated decisions that have legal or significant effects on you. ## **3\. How We Share Your Information** We do not sell your personal information. We do not rent it. We do not trade it. We may share your information only in the following limited circumstances: **Service providers.** We share information with vendors who help us operate the site and deliver our services, including payment processing, email delivery, event registration, livestream hosting, and site analytics. These vendors are permitted to use your information only to perform services on our behalf and are contractually required to protect it. **Published content.** If you submit a Letter or a comment that we publish, it appears under your name. If you attend or appear at a CEO.com event or livestream, recordings and photographs of your appearance may be published, as described in our Terms of Use. **Legal compliance.** We may disclose information if we believe in good faith that doing so is required by law, regulation, or legal process, or to protect the rights, property, or safety of CEO.com, our readers, or others. **Business transfers.** If CEO.com is acquired, merged, or sold, your information may be transferred as part of that transaction. We will notify you before your information becomes subject to a materially different privacy policy. **With your consent.** We may share your information in other circumstances if you give us explicit permission. ## **4\. Email Communications** You can unsubscribe from marketing and newsletter emails at any time by clicking the unsubscribe link at the bottom of any email or by contacting us at contact@ceo.com. Note that even if you unsubscribe from newsletters, we may still send you transactional emails related to your account, such as subscription confirmations and billing notices. ## **5\. Cookies and Tracking Technologies** We use cookies and similar technologies to operate the site and understand how it is used. **Essential cookies** are necessary for the site to function. They enable things like logging in, remembering your subscription status, and processing payments. You cannot opt out of these without disabling the site. **Analytics cookies** help us understand how visitors use the site, which pages are most popular, and where readers come from. We use this data in aggregate to improve our content and experience. **Email tracking** allows us to see whether newsletters were opened and which links were clicked. This helps us understand what our readers find valuable. You can disable this by turning off automatic image loading in your email client. You can manage cookie preferences through your browser settings. Disabling cookies may affect your ability to use certain features of the site, including logging in and accessing subscriber content. ## **6\. Data Retention** We retain your personal information for as long as your account is active or as needed to provide you with services. If you cancel your subscription or close your account, we will retain your information for a reasonable period afterward to fulfill any outstanding obligations, resolve disputes, and comply with legal requirements. When we no longer need your information, we delete or anonymize it. ## **7\. Data Security** We take reasonable technical and organizational measures to protect your information from unauthorized access, disclosure, alteration, and destruction. These include encrypted transmission via HTTPS, limited access to personal data by staff and contractors, and use of reputable third-party providers with their own security standards. No method of transmission over the internet or electronic storage is completely secure. We cannot guarantee absolute security, but we take it seriously and will notify you promptly if a breach affects your information. ## **8\. Children's Privacy** CEO.com is not directed at children under the age of 13\. We do not knowingly collect personal information from children under 13\. If you believe a child under 13 has provided us with personal information, contact us at contact@ceo.com and we will delete it promptly. ## **9\. Your Rights and Choices** Depending on where you live, you may have certain rights regarding your personal information, including: The right to access the personal information we hold about you. The right to correct inaccurate information. The right to request deletion of your information, subject to certain exceptions. The right to opt out of marketing communications at any time. The right to data portability in certain circumstances. To exercise any of these rights, contact us at contact@ceo.com. We will respond within a reasonable time and no later than required by applicable law. We may need to verify your identity before fulfilling your request. We do not discriminate against you for exercising your privacy rights. Deletion requests do not extend to published journalism. Content we have published, including stories that mention you, Letters, and public civic bounty disclosures, is retained and published under our editorial standards and applicable law. ### **California Residents** If you are a California resident, you have additional rights under the California Consumer Privacy Act (CCPA), including the right to know what personal information we collect and how it is used, the right to request deletion, and the right to opt out of the sale of personal information. We do not sell personal information. To submit a CCPA request, contact us at contact@ceo.com. ### **European and UK Residents** If you are located in the European Economic Area or the United Kingdom, you have rights under the General Data Protection Regulation (GDPR) or UK GDPR, including the right to object to processing, the right to restrict processing, and the right to lodge a complaint with a supervisory authority. Our legal basis for processing your personal information is generally contract performance (to deliver your subscription and administer civic bounties), legitimate interests (to operate and improve the site and publish journalism in the public interest), and your consent (for marketing communications). To exercise your rights, contact us at contact@ceo.com. ## **10\. Third-Party Services** CEO.com may contain links to third-party websites. This Privacy Policy applies only to CEO.com. We are not responsible for the privacy practices of any third-party site and encourage you to review their policies before providing any personal information. We currently use the following categories of third-party services: payment processing, email delivery, event registration, livestream and podcast hosting, and site analytics. We evaluate these providers for security and data practices before use. ## **11\. Changes to This Policy** We may update this Privacy Policy from time to time. When we do, we will update the "Last Updated" date at the top of this page. For material changes, we will notify registered users by email or by posting a notice on the site. Your continued use of CEO.com after any changes constitutes your acceptance of the updated policy. ## **12\. Contact** If you have questions, concerns, or requests related to this Privacy Policy, contact us at: CEO.com, LLC 42 West Center St. Provo, Utah 84601 contact@ceo.com ### Cookie Policy URL: https://www.ceo.com/cookie-policy/ Last updated: 2026-08-18T18:06:15.000Z CEO.com, LLC ("CEO.com," "we," "our," or "us") uses cookies and similar technologies on CEO.com. This policy explains what they are, what we use them for, and what choices you have. ## **What Cookies Are** A cookie is a small text file placed on your device when you visit a website. Cookies allow a site to recognize your device, remember your preferences, and understand how you use the site over time. They do not contain viruses and cannot access other files on your device. Similar technologies include web beacons, pixel tags, and local storage, which function in comparable ways. When we say "cookies" in this policy, we mean all of these technologies. ## **Cookies We Use** ### **Essential Cookies** These cookies are necessary for the site to function. They enable you to log in, maintain your session, access subscriber content, and complete purchases, including subscription payments and civic bounty contributions. Without them, core features of the site do not work. These cookies cannot be disabled through our site. If you disable them through your browser, you will not be able to log in or access paid content. Examples of what they do: keep you logged in as you navigate the site, remember your subscription status, and support secure payment processing at checkout. ### **Analytics Cookies** These cookies help us understand how visitors use the site. They tell us which articles are read most, how long people spend on a page, where readers come from, and which newsletter links get clicked. We use this information in aggregate to improve our content, navigation, and editorial decisions. We use Google Analytics and/or Plausible for this purpose. No data collected through analytics cookies is sold or shared with advertisers. You can opt out of analytics cookies through our cookie preference settings or through your browser. Opting out does not affect your ability to read content or access your subscription. ### **Functional Cookies** These cookies remember choices you have made to improve your experience on the site, such as your preferred display settings or whether you have dismissed a notice. They are not essential but make the site more convenient to use. ### **Media Playback Cookies** Our livestreams, podcast episodes, and video interviews are delivered through embedded media players. These players may set cookies to support playback, remember your volume and playback settings, resume where you left off, and measure viewership. Some of these are set by the third-party platforms that host our media, as described under Third-Party Cookies below. ### **Email Tracking Pixels** Our newsletters contain small image files that tell us whether an email was opened and which links were clicked. This helps us understand what our readers find useful so we can make the newsletter better. If you prefer not to be tracked in this way, you can disable automatic image loading in your email client. This will prevent the tracking pixel from firing. Your ability to read the newsletter is not affected. ## **What We Do Not Do** We do not use cookies to serve targeted or behavioral advertising. We do not sell or share cookie data with advertisers or data brokers. We do not use cookies to build profiles of you for commercial purposes beyond operating and improving our own site. ## **Third-Party Cookies** Some third-party services we use may set their own cookies. These include: Our payment processor, which sets cookies to support secure transactions. Our analytics provider, which sets cookies to measure site usage. Our email delivery provider, which may track engagement with newsletters. Our livestream and podcast hosting platforms, which may set cookies to support media playback and measure viewership. Our event registration platform, which may set cookies when you register for an event. These third parties operate under their own privacy and cookie policies. We do not control their cookies and encourage you to review their policies if you have concerns. We do not permit third-party advertising networks to set cookies on CEO.com. ## **Your Choices** **Browser settings.** You can manage, block, or delete cookies through your browser settings. The process varies by browser. Instructions for major browsers are available at the links below. Chrome: support.google.com/chrome/answer/95647 Firefox: support.mozilla.org/kb/cookies-information-websites-store-on-your-computer Safari: support.apple.com/guide/safari/manage-cookies-sfri11471 Edge: support.microsoft.com/help/4468242 Blocking all cookies will prevent you from logging in and accessing subscriber content on CEO.com. **Analytics opt-out.** If we use Google Analytics, you can opt out using the Google Analytics Opt-Out Browser Add-On available at tools.google.com/dlpage/gaoptout. If we use a privacy-focused analytics provider, we will note any available opt-out here. **Do Not Track.** Some browsers send a Do Not Track signal to websites. We currently do not respond to Do Not Track signals in a standardized way, as no industry-wide standard has been established. **California residents.** If you are a California resident, you have additional rights under the CCPA. See our CA Notice of Collection. ## **Changes to This Policy** We may update this Cookie Policy from time to time. When we do, we will update the "Last Updated" date at the top of this page. Continued use of CEO.com after any changes constitutes your acceptance of the updated policy. ## **Contact** Questions about this policy can be directed to: CEO.com, LLC 42 West Center St. Provo, Utah 84601 contact@ceo.com ### Cookie Settings URL: https://www.ceo.com/cookie-settings/ Last updated: 2026-08-18T18:07:41.000Z CEO.com uses cookies to keep the site running, understand how it's being read, and remember your preferences. Below is a breakdown of what we use and what you can turn off. For the full story, read our Cookie Policy. ## **Essential Cookies** These cookies are required for the site to work. They keep you logged in, remember your subscription, and support secure checkout for subscriptions and civic bounty contributions. We cannot turn these off, and neither can you, without breaking the site. ## **Analytics Cookies** These cookies help us see which articles are being read, how long people stay, and where readers come from. We use that information to make better editorial decisions. The data is aggregate. We do not sell it or share it with advertisers. Turning these off will not affect your ability to read content or access your subscription. ## **Functional Cookies** These cookies remember small preferences, like whether you have dismissed a notice. They are not essential, but they make the site a bit more convenient. Turning them off will not prevent you from using the site. ## **Media Playback Cookies** Our livestreams, podcast episodes, and video interviews run through embedded players that may set cookies to support playback, remember your settings, and measure viewership. Some are set by the platforms that host our media. Turning these off may affect playback, but not your ability to read the site. ## **Email Tracking** Our newsletters contain a small image that tells us whether an email was opened and which links were clicked. This helps us understand what our readers find valuable. You can also disable this by turning off automatic image loading in your email client. We do not use cookies to serve you ads. We do not sell your data. Questions? Contact us at contact@ceo.com ### Notice of Collection for California Residents URL: https://www.ceo.com/notice-of-collection-for-california-residents/ Last updated: 2026-08-18T18:09:17.000Z **Required under the California Consumer Privacy Act (CCPA) as amended by the California Privacy Rights Act (CPRA)** At or before the time we collect your personal information, California law requires us to tell you what we collect and why. This notice applies to California residents only. Our full Privacy Policy is available at CEO.com/privacy. ## **What We Collect and Why** **Identifiers** Such as your name, email address, IP address, and account credentials. We collect this to create and manage your account, deliver newsletters, and operate the site. **Payment information** Such as your credit or debit card number and billing details. We collect this to process subscription payments and civic bounty contributions. Payment data is handled directly by our third-party payment processor and is not stored on our servers. **Commercial information** Such as your subscription tier, purchase history, billing records, and civic bounty contribution history. We collect this to manage your subscription, administer civic bounties, and provide customer support. **Event registration information** Such as your name, contact details, and any dietary or accessibility needs you provide. We collect this to register you for events and livestreams and to host you at them. **Content you submit** Such as Letters, comments, and other material you send us for publication. We collect this to review it and, if selected, publish it under your name. **Internet and network activity** Such as pages visited, links clicked, time on site, browser type, and device information. We collect this to analyze how the site is used and improve our content and experience. **Email engagement data** Such as whether you opened a newsletter and which links you clicked. We collect this to understand what content our readers find valuable. ## **How Long We Keep It** We retain your personal information for as long as your account is active or as needed to provide you with services. When we no longer need it, we delete or anonymize it. Civic bounty contribution records are retained as long as necessary to fulfill the escrow, disclosure, and transparency commitments described in our Editorial Charter and Terms of Use. Content we publish, including Letters and comments, remains published under our editorial standards. ## **Do We Sell or Share Your Information?** We do not sell your personal information. We do not share your personal information with third parties for cross-context behavioral advertising. We share limited information with service providers who help us operate the site and deliver our services, including our payment processor, email delivery provider, event registration and livestream platforms, and analytics provider. These providers are permitted to use your information only to perform services on our behalf. One form of disclosure is unique to CEO.com. If you contribute to a civic bounty above a threshold we set, your name and contribution amount may be publicly disclosed, as described in our Editorial Charter, Terms of Use, and Privacy Policy, unless anonymity is granted for a legitimate protective purpose. This is a transparency commitment of our journalism, and you accept it when you contribute above the threshold. ## **Your California Privacy Rights** As a California resident, you have the right to: Know what personal information we collect, use, disclose, and retain. Request access to the specific personal information we have collected about you. Request deletion of your personal information, subject to certain exceptions. Request correction of inaccurate personal information. Opt out of the sale or sharing of your personal information. We do not sell or share. Limit the use of sensitive personal information. We do not use sensitive personal information beyond what is necessary to provide our services. Not be discriminated against for exercising your rights. Deletion and correction rights do not extend to published journalism. Content we have published, including stories, Letters, and public civic bounty disclosures, is retained and published under our editorial standards and applicable law. ## **How to Submit a Request** To exercise any of your California privacy rights, contact us at: Email: contact@ceo.com Mail: 42 West Center St. Provo, Utah 84601 We will acknowledge your request within 10 business days and respond within 45 calendar days. If we need more time, we will notify you. We may need to verify your identity before fulfilling your request. You may designate an authorized agent to make a request on your behalf. We will require written authorization or a power of attorney, and may verify your identity directly. ## **Contact for Privacy Questions** CEO.com, LLC 42 West Center St. Provo, Utah 84601 contact@ceo.com For our full Privacy Policy, visit CEO.com/privacy. ### The CEO Project URL: https://www.ceo.com/project/ Last updated: 2026-08-19T03:34:27.000Z We believe that entrepreneurial talent exists everywhere, but opportunity does not. The CEO Project aims to bridge this gap by equipping remote communities in Vanuatu with the capabilities, connections, and confidence to maximize their potential in the digital economy. [Apply Now](https://www.ceo.com/ceo-project-application/) ## From island ideas to global markets Through the mentorship program, small businesses in remote regions can achieve several transformative benefits. Some examples include: - Market Expansion: Local artisans learn e-commerce strategies to sell traditional handicrafts to global markets - Tourism Innovation: Small operators develop digital booking systems and marketing approaches to attract international travelers - Agricultural Advancement: Farmers implement supply chain technologies to reduce waste and increase profits - Sustainable Business Models: Entrepreneurs create resilient, climate-conscious businesses built for long-term success ## A two-way exchange The CEO Project isn't just about mentorship - it's about mutual growth. For business leaders in the CEO.com network, this program offers: - The opportunity to make a meaningful impact by sharing expertise with motivated entrepreneurs - Fresh perspectives on business challenges from individuals navigating unique market conditions - Cultural exchange that broadens leadership vision and inspires innovative thinking - Connections with a community rich in tradition and natural resources - The satisfaction of contributing to sustainable economic development ## Get involved This program values mentors who approach their role as partners in development, acknowledging the agency and expertise of mentees whilst providing relevant support that enhances existing capabilities. We look forward to welcoming you to be part of this transformative journey. ### Economic micro hub Building economic powerhouses in remote communities. [Learn More](https://www.welchmankeen.com/post/welchman-keen-and-ceo-com-collaborate-on-entrepreneurship-mentorship-via-remote-connectivity-in-deve?ref=ceo.com) ### What to expect Mentorship milestones and timeline. [Learn More](https://www.ceo.com/ceo-project-mentor-expectations/) ### Become a mentor For seasoned executives seeking to guide aspiring rural business owners to success. [Apply Now](https://www.ceo.com/ceo-project-application/) ### The CEO Project: Expectations for Mentors URL: https://www.ceo.com/ceo-project-mentor-expectations/ Last updated: 2026-08-18T20:39:04.000Z Success is not a fixed or universal standard in this program; instead, we recognise progress as the true measure. The expectations and goals are for each mentor and mentee to define together, fostering a supportive and personalised journey. To facilitate this mentor-mentee relationship, mentors are expected to demonstrate cultural sensitivity and adaptability whilst supporting entrepreneurs from rural and remote regions. We seek individuals who approach this opportunity with: - A commitment to flexible scheduling that accommodates significant time zone differences and intermittent connectivity challenges faced by mentees. - An understanding of the unique contextual barriers that entrepreneurs encounter in developing regions, including limited infrastructure, resource constraints and market access challenges. - A sense of humility and genuine desire to engage in mutual learning, recognising the valuable indigenous knowledge and innovative approaches mentees bring to entrepreneurship. - The ability to offer guidance that respects local cultural contexts and business environments rather than imposing external frameworks or solutions. - Patience and resilience when navigating communication barriers or unexpected obstacles. - A collaborative mindset that empowers mentees to develop solutions appropriate to their circumstances and communities. Mentorship Milestones ![](https://assets-v2.circle.so/av1ks084tv2pqqsqw6bwxlkcjift) Starting with [Vanuatu](https://www.welchmankeen.com/emua-vila-launch?ref=ceo.com), the six-month mentorship program operates through a structured yet flexible process designed to create meaningful connections: - Call for Applications: CEO.com members can apply through the CEO.com website, stating why they would like to be a mentor. Similarly, budding entrepreneurs from Vanuatu can submit their application through the Economic Micro-Hub (EMH) portal, detailing their business or e-commerce ideas, challenges, and goals. - Mentor Matching: Welchman Keen and CEO.com match entrepreneurs in Vanuatu with prospective mentors, focusing on maximizing the benefits of e-commerce and expanding regional and global market reach for community-based products. - Meet Your Match: Following the results of the mentor-matching, successful applicants can initiate contact and establish their preferred communication channels. Both mentors and mentees are encouraged to take ownership of this relationship, arranging meetings at mutually convenient times and frequencies. The program does not prescribe a rigid structure, allowing pairs to customise their engagement according to specific development objectives and availability. We recommend an initial introductory session to align expectations, followed by regular check-ins as determined by both parties. - Mid-Term Update: During the third month of the mentorship, we invite both mentors and mentees to share their experiences and insights. Feel free to express yourself in whatever format works best for you. Whether it is a compilation of images from your mentorship activities, a short video reflection, or even a recorded conversation between you and your mentorship partner – we value your authentic feedback. Your update should touch on key milestones reached, challenges you have navigated together, and any unexpected benefits discovered along the way. This isn't about formal reporting but rather creating a meaningful checkpoint in your mentorship relationship that helps everyone get the most from this experience. - Easy out: After month six of the mentorship, both mentor and mentee will be asked if they want to continue the matched relationship. If either party answers with a “no,” the relationship will be discontinued and participants rematched with no questions asked. - Annual Showcase: Similar to the mid-term update, we encourage creativity and emphasis on knowledge-sharing with the wider community. An annual showcase, featured alongside the annual CEO.com event, will highlight the most creative and successful instances of mentees demonstrating their new business approach at an existing community market, connecting with potential customers, or sharing their entrepreneurial journeys and mentorship experiences This program values mentors who approach their role as partners in development, acknowledging the agency and expertise of mentees whilst providing relevant support that enhances existing capabilities. We look forward to welcoming you to be part of this transformative journey. More information on the [CEO.com-Welchman Keen collaboration](https://www.welchmankeen.com/post/welchman-keen-and-ceo-com-collaborate-on-entrepreneurship-mentorship-via-remote-connectivity-in-deve?ref=ceo.com) [Apply Now](https://www.ceo.com/ceo-project-application/) ### CEO Project Application URL: https://www.ceo.com/ceo-project-application/ Last updated: 2026-08-18T20:43:04.000Z _No content available._ ### The CEO Project: Guidelines for Mentors URL: https://www.ceo.com/ceo-project-mentor-guidelines/ Last updated: 2026-08-18T20:45:07.000Z To ensure a positive, fulfilling experience for both mentors and entrepreneurs, it is important that we set some expectations and guidelines for this engagement. Designed to facilitate meaningful knowledge exchange and to balance business growth with cultural realities, these guidelines ensure productive mentor-mentee relationships while acknowledging the unique challenges and opportunities that exist within emerging market economies. Adherence to these principles will maximize the program’s impact on each project and improve chances of a meaningful outcome for both partners. Mentors should strive to: **1\. Understand and support the goals of the individual** Mentors should avoid the temptation to hijack a project with their own ideas. These entrepreneurs will rarely say no to avoid offense but will likely begin to disengage. **2\. Work within the local cultural context** Some business standards and practices may not apply. Show openness to criticism, as in many cultures, disagreeing with authority figures is considered disrespectful. Create a safe space for honest feedback. **3\. Be professional but kind and patient** While punctuality and regular measurable progress should be prioritized, bear in mind that some cultures do not place the same emphasis on planning and timeliness. A little patience goes a long way. **4\. Be committed** Seek to work past shortfalls and disappointments. This is a mutual learning process. **5\. Ask questions** Seek understanding of local market conditions, permits, regulatory frameworks and economic circumstances to ensure informed decision-making. **6\. Document the process** This is a journey. Keep records, photos, data and metrics to show growth and tell your joint story. **7\. Feel free to use your resources and network to the extent you are comfortable and no further** Report any inappropriate requests for funds that you have not volunteered. Do not make promises that you are unable to deliver. **8\. Follow responsible and sustainable business practices** Do not pursue business ideas that cause harm to the individual, their community or the environment. ### Recent Guests URL: https://www.ceo.com/recent-guests/ Last updated: 2026-09-01T16:59:37.000Z Used on the Home page to organize the list of recent guests. ### Podcast Guest Submission Form URL: https://www.ceo.com/podcast-guest-submission-form/ Last updated: 2026-09-15T17:35:02.000Z _No content available._ ## Posts ### The AI crisis is a leadership crisis URL: https://www.ceo.com/episodes/the-ai-crisis-is-a-leadership-crisis/ Last updated: 2026-10-02T06:59:19.000Z What should we make of the claim that AI has a greater than 10 percent chance of killing all humans within the next decade? 10 percent is no joke. For example, two weeks before the 2016 election, [The New York Times](https://www.nytimes.com/interactive/2016/upshot/presidential-polls-forecast.html?rref=collection%2Fsectioncollection%2Fupshot&action=click&contentCollection=upshot®ion=rank&module=package&version=highlights&contentPlacement=2&pgtype=sectionfront&%5Fr=0&ref=ceo.com) gave Donald Trump just a 7 percent chance of winning. It's worth repeating: 10 percent is no joke. Greater than 10 percent is greater than no joke. This isn't coming from some random user on X. It's coming from a [senior safety researcher at Anthropic](https://x.com/EvanHub/status/2097497037956891126?s=20&ref=ceo.com), the leader of the leading frontier AI companies. So, of course, AI is wildly unpopular with the very humans whose lives it might incinerate. According to a recent Gallup poll, [only 27% of Americans trust businesses to use AI responsibly](https://news.gallup.com/poll/712751/americans-cool-toward.aspx?ref=ceo.com). Since that poll was published, given the growing number of reported incidents inside these frontier AI companies, what are the odds that public trust has improved? In response, politicians have released statements, demanded hearings, promoted more regulation, and even called for stopping AI development altogether. Of course, this does nothing to ease anyone's concerns. Congressional approval is lower than AI, [at 10 percent](https://news.gallup.com/poll/708722/disapproval-congress-ties-record-high.aspx?ref=ceo.com), which feels 10 percent too high, honestly. While President Trump is more popular than AI or Congress, he doesn't beat them by much. He's currently sitting at a [32% approval rating](https://www.ipsos.com/en-us/republicans-rating-trump-cost-living-declines?ref=ceo.com). This week he got the leaders of these companies to come to the White House, sign a document, and stand awkwardly in front of the press. He also rebranded AI as Super Intelligence, hoping America's love for superhero movies will change how it feels about things. It's worth noting where we are right now. While the purveyors of this technology build the most valuable companies in history, making them the richest and most powerful human beings in history, the average American can barely afford a tank of gas and often resorts to buying groceries on credit to feed their families. They watch their leaders make statements instead of answering legitimate questions or taking action. For example, if you're the CEO of a frontier AI company and you believe the technology you're building has more than a 10 percent chance of wiping out humanity, why don't you stop developing it? Once you stop, why don't you put all your vast resources into combating the threat this technology poses by building tools to counter the companies and countries that do continue to develop it? If you're the government, why don't you raid these companies and shut them down for developing technology that might wipe out humanity? You don't need to pass a new law to do that. Why don't you ban the technology completely? If the federal government doesn't do it, why don't governors do it? Plenty of states have banned gambling, marijuana, and even pornography. Those hurt individuals. If you believe it's capable, AI won't just hurt people. It will kill us all. What are you waiting for? Since none of that is happening, Americans rightly suspect that its politicians and tech leaders don't really believe what they're saying. If they believed it, they'd act. All of this leads Americans to wonder: Is this an AI crisis or a leadership crisis? Meaning, is the problem the technology or the leaders behind the technology? Is there a difference between what these leaders say and what they do? No story gets to the heart of these questions better than what happened earlier this year. On February 28, the United States conducted military strikes that resulted in the obliteration of an Iranian elementary school, killing more than 150 people, mostly children. While the United States has not officially or publicly taken responsibility, [Bloomberg reports](https://www.bloomberg.com/graphics/2026-iran-school-attack/?ref=ceo.com) that the Pentagon launched an investigation that, among other things, found, "Some personnel relied too much on the artificial intelligence embedded in Maven Smart System, which is made by Palantir Technologies." According to multiple press reports, the artificial intelligence embedded in Maven Smart System was Anthropic's Claude. In fact, even after the Pentagon banned Anthropic for reasons unrelated to the elementary school bombing, Palantir was still using Anthropic. "The Department of War is planning to phase out Anthropic, Palantir CEO Alex Karp told CNBC on March 12, 2026\. “Currently, it's not phased out. Our products are integrated with Anthropic, and in the future, it will probably be integrated with other large language models because of this dispute." When asked by Bloomberg whether Claude was used in the elementary school bombing, Anthropic CEO Dario Amodei said he didn't know. Then he said this: "What you're talking about is a use case that doesn't even violate our red lines. We're worried that there will be a hundred times as much with use cases that do violate our red lines." It's worth [watching the full interview](https://www.youtube.com/watch?v=v1wZwxY3CMg&ref=ceo.com), which is more nuanced than that quote, but it's also worth pausing to reflect that using AI to help facilitate a strike like the bombing of an elementary school doesn't violate Anthropic's red lines. Leading up to the bombing of the elementary school, [The Washington Post reported](https://www.washingtonpost.com/technology/2026/03/04/anthropic-ai-iran-campaign/?ref=ceo.com), "As planning for a potential strike in Iran was underway, Maven, powered by Claude, suggested hundreds of targets, issued precise location coordinates, and prioritized those targets according to importance." In a recent interview with CBS News, [Amodei said](https://x.com/dnapway/status/2099176341132476530?s=20&ref=ceo.com), "I would rather they make fun of me than to wake up one day and discover that someone used our model, Claude, to kill a bunch of people. I don't want that." It's entirely possible, though not officially confirmed, that Amodei has already woken up one day and discovered that his model was used to kill a bunch of people, mostly children. Based on what Amodei has said, one might think the company would be more than happy not to be used as a weapon of war, but it's actively fighting that decision and wants the Pentagon and its partners to continue using its technology. Of course, these contracts are enormous; the last contract between Anthropic and the Pentagon was [valued at up to $200M](https://www.cnbc.com/2025/07/14/anthropic-google-openai-xai-granted-up-to-200-million-from-dod.html?ref=ceo.com), paid for by taxpayers struggling to make ends meet. The public is baffled by the incoherence, lack of transparency about motives, and the day-to-day whiplash between doom and utopia. To say the least. Having already written off politicians, they have simple questions for the leaders of these companies: What do you stand for? What do you actually believe? What is actually going on inside your company? What are you building exactly? Put plainly, Americans are searching for a leader to meet this moment. Whether AI is a crisis on its own is an open question. For now, what's not is that we're in a leadership crisis, hoping someone or some entity can answer simple questions from a bewildered and beleaguered public running out of patience. ```chapters 00:00:00 The Threat of Artificial Intelligence 00:01:18 Public Trust and Political Responses 00:02:03 Wealth Disparity and Leadership Inaction 00:03:49 Technology Crisis or Leadership Crisis 00:04:13 AI in Military Operations 00:05:30 Red Lines and Ethical Dilemmas 00:07:29 The Search for True Leadership ``` ```vtt WEBVTT 00:00:00.160 --> 00:00:08.880 What<00:00:00.400> should<00:00:00.560> we<00:00:00.800> make<00:00:00.960> of<00:00:01.120> the<00:00:01.360> claim<00:00:01.760> that<00:00:02.000> AI<00:00:02.560> has<00:00:02.800> a<00:00:03.040> greater<00:00:03.280> than<00:00:03.600> 10%<00:00:04.240> chance<00:00:05.120> of<00:00:05.440> killing<00:00:05.839> all<00:00:06.160> humans<00:00:06.960> within<00:00:07.359> the<00:00:07.520> next<00:00:07.759> decade? 00:00:08.880 --> 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Americans<00:08:01.680> are<00:08:01.919> searching<00:08:02.240> for<00:08:02.479> a<00:08:02.720> leader<00:08:03.360> to<00:08:03.680> meet<00:08:04.000> this<00:08:04.319> moment. 00:08:05.680 --> 00:08:11.199 Whether<00:08:06.080> AI<00:08:06.479> is<00:08:06.639> a<00:08:06.879> crisis<00:08:07.199> on<00:08:07.360> its<00:08:07.680> own<00:08:08.319> is<00:08:08.560> an<00:08:08.800> open<00:08:09.120> question<00:08:10.400> for<00:08:10.720> now. 00:08:11.199 --> 00:08:19.520 What's<00:08:11.520> not<00:08:12.000> is<00:08:12.240> that<00:08:12.479> we're<00:08:12.720> in<00:08:12.960> a<00:08:13.199> leadership<00:08:13.840> crisis,<00:08:14.879> hoping<00:08:15.360> someone<00:08:15.840> or<00:08:16.240> some<00:08:16.479> entity<00:08:16.960> can<00:08:17.280> answer<00:08:17.680> simple<00:08:18.160> questions<00:08:19.120> from<00:08:19.360> a 00:08:19.520 --> 00:08:25.520 bewildered<00:08:20.639> and<00:08:20.879> beleaguered<00:08:21.599> public<00:08:22.879> running<00:08:23.199> out<00:08:23.360> of<00:08:23.520> patience. ``` ### H.J. Chammas wants authors to stop counting royalties URL: https://www.ceo.com/episodes/h-j-chammas-wants-authors-to-stop-counting-royalties/ Last updated: 2026-10-01T23:19:53.000Z The publisher's pitch was simple arithmetic. Sell a million copies, earn $2 a copy, and collect $2 million in royalties. "Wow, I thought that's a great deal," H.J. Chammas told the CEO.com Podcast. "Let me pay them $65,000 and see what happens." He launched the book in 2018, [according to his company's website](https://authority-publishing.com/?ref=ceo.com). The [author bio on his 2026 book](https://books.google.com/books/about/Publish%5FPromote%5FMonetize.html?id=IZ3n0QEACAAJ&ref=ceo.com) says it earned less than $2,000 in royalties. Chammas now runs Authority Publishing, a Dubai-based firm that helps coaches, consultants, and business leaders use books to grow their businesses. His advice to anyone counting on royalties is short. "It will never ever put money into your bank account," he said. Chammas could afford the gamble. He had already made his money in real estate. He left Lebanon in 2001 with $300 in his pocket and took a job with Nestlé in Dubai. "Everything was big, man. Everything was huge," he said. He wanted to go home. He stayed and worked his way up, and Nestlé eventually sent him to the Philippines. He was there when the 2008 financial crisis hit. While everyone around him was getting out of real estate, he started buying. At a fundraiser, he met a Lebanese-American billionaire known as Papa Joe and kept turning up at his office until Papa Joe agreed to coach him. The terms were strict. "He made me work for him in his property companies for free so that I can learn all the steps in investing in properties," Chammas said. Papa Joe, who has since died, ran on street smarts and never put a system in place for how he built his empire. Chammas had spent years inside Nestlé's processes, so he built one. Within six or seven years, his rental portfolio let him leave the corporate world. He now teaches his real estate strategy through [Employee Millionaire](https://employeemillionaire.com/?ref=ceo.com), which sells courses and one-on-one coaching on investing in rental properties. The book was supposed to be the foundation of his next business. He blames the result on his reasons for writing it. "My big why was more of an egocentric approach," he said. "I wanted to become famous. I wanted to build a business on the back of the book rather than how can I help make the world a better place." He went back and studied authors who had built loyal followings and real influence. He concluded they all had one thing in common: service. "It's all about helping others," he said. He retitled his book, repositioned it, and republished it himself; within months, it became a bestseller, according to the same bio. From 2019 on, he self-published three more books, and [his company's site](https://authority-publishing.com/?ref=ceo.com) says all three quickly became No. 1 bestsellers. He also started building a personal brand around what he had learned. That is how his first client found him. A woman he didn't know messaged him on LinkedIn. She had already published a book that went nowhere, and she had been reading up on him. "She loved how I failed," he said. He helped her for free. He reworked her positioning, connected her with editors, and coached her through promoting herself before promoting the book. It reached Amazon's bestseller list within a couple of months. The bigger change was in her calendar. She trains employees for companies and government entities in the UAE, and she now averages 1.7 engagements a week. She has also given two TEDx talks. She told him plenty of authors were as lost as she had been, and that "the world needs you." Authority Publishing took on six authors in its first year and more than 20 in its second. Chammas said it now counts more than 50 bestselling authors, and that the team is picky about whom it takes on. "We cannot make a bad book great," he said. The company sells the process he used for his own book. The first meeting is about whom the author serves and why they want a book at all. An author who says royalties is probably not a fit. Clients don't have to write their own books. Chammas interviews them chapter by chapter over Zoom, sends the questions ahead of time, and asks again when an answer comes back thin. Three ghostwriters then draft samples in the author's voice, and the author picks one. Some authors arrive with AI-written manuscripts. "Man, it's robotic. You hear it," he said. "There's no soul in the book." His team uses AI in editing and design, but only on the author's real stories. Promotion puts the author in front of audiences long before it pushes the book. New authors commit to four relevant podcast appearances a month for 12 months. They'll "suck in the first few months," he said, but the shows are "your training ground." Speaking slots, award nominations, and endorsements from established names come next, followed by social media and Amazon ads. He warns against paying for an overnight bestseller, since a spike followed by a crash teaches the algorithm to stop showing the book. The return comes as consulting, coaching, and speaking work from readers who want more. "It's not about selling the book," he said. "It's about selling what the book can sell for you." Publishing a finished manuscript costs $6,600 to $9,900, and full ghostwriting starts at $35,000\. For authors he believes in, the company will pay to publish the book and take 20% of the revenue from the sales funnel it builds for them. The business took its own hit this year. Most of his clients were in the UAE. When war with Iran broke out in late February, he said he lost more than half his business. He started pursuing authors in Singapore, Australia, Europe, and the United States. Filling that pipeline took time, he said, but the company is back to the run rates it had before the war. The CEO.com Podcast ends every interview by asking who gave the guest a chance. Chammas named the woman from LinkedIn. Then he asked to add one more thought. "Sometimes the person who gives you a chance doesn't just open a door for you," he said. "They show you which door you should be opening for others." ```chapters 00:00:00 Introduction to Authority Marketing 00:03:07 Learning From a Publishing Failure 00:06:00 Real Estate Ventures and Systems 00:12:15 Initial Steps for Aspiring Authors 00:14:04 The Publish Promote Monetize Framework 00:16:09 Ghostwriting and the Role of AI 00:19:41 Marketing a Book for Long-Term Success 00:24:42 Monetizing Beyond Book Royalties 00:31:38 Daily Routines and Work-Life Balance 00:35:26 The Power of Giving Someone a Chance ``` ```vtt WEBVTT 00:00:05.480 --> 00:00:07.480 HJ,<00:00:05.840> thank<00:00:06.040> you<00:00:06.120> so<00:00:06.240> much<00:00:06.440> for<00:00:06.560> coming<00:00:06.880> on<00:00:06.960> the<00:00:07.040> show. 00:00:07.480 --> 00:00:12.360 You<00:00:07.680> are<00:00:07.840> the<00:00:08.120> founder<00:00:08.760> and<00:00:09.040> CEO<00:00:10.000> of<00:00:10.200> Authority<00:00:10.880> Marketing. 00:00:12.360 --> 00:00:18.800 Let's<00:00:12.560> 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--> 00:02:53.480 gain<00:02:48.240> authority<00:02:49.560> using<00:02:49.880> your<00:02:50.200> term<00:02:50.560> and<00:02:50.680> your<00:02:50.920> word,<00:02:51.760> which<00:02:51.920> I<00:02:51.959> think<00:02:52.160> is<00:02:52.320> accurate. 00:02:53.480 --> 00:02:58.120 And<00:02:54.680> also<00:02:55.040> like<00:02:55.200> so<00:02:55.320> you<00:02:55.440> can<00:02:55.640> go<00:02:55.840> speak<00:02:56.560> and<00:02:56.959> do<00:02:57.160> all<00:02:57.280> sorts<00:02:57.560> of<00:02:57.640> things,<00:02:57.880> right? 00:02:58.120 --> 00:03:01.600 Like<00:02:58.320> and<00:02:58.520> which<00:02:58.760> which<00:02:58.959> again<00:02:59.280> kind<00:02:59.480> of<00:02:59.640> leads<00:03:00.120> to<00:03:00.519> authority. 00:03:01.600 --> 00:03:07.560 How<00:03:01.760> did<00:03:02.000> you<00:03:02.200> realize<00:03:02.760> that<00:03:03.040> you<00:03:03.200> were<00:03:03.400> good<00:03:03.680> at<00:03:03.840> this<00:03:04.200> and<00:03:04.360> you<00:03:04.480> could<00:03:04.640> do<00:03:04.840> this<00:03:05.120> for<00:03:05.320> other<00:03:05.560> leaders<00:03:06.040> and<00:03:06.160> CEOs? 00:03:07.560 --> 00:03:13.800 <00:03:08.022> Actually,<00:03:08.484> it<00:03:08.945> all<00:03:09.407> started<00:03:09.869> with<00:03:10.331> a<00:03:10.793> with<00:03:11.255> a<00:03:11.716> story<00:03:12.178> of<00:03:12.640> failure. 00:03:13.800 --> 00:03:19.880 When<00:03:14.000> I<00:03:14.080> first<00:03:14.360> started<00:03:14.760> with<00:03:14.920> my<00:03:15.800> first<00:03:16.160> book,<00:03:16.880> I<00:03:17.000> would<00:03:17.239> tag<00:03:17.480> myself<00:03:18.080> and<00:03:18.200> I'm<00:03:18.440> happy<00:03:18.760> with<00:03:18.959> it<00:03:19.120> now. 00:03:19.880 --> 00:03:25.000 I<00:03:20.040> could<00:03:20.360> be<00:03:20.720> the<00:03:20.920> biggest<00:03:21.480> failure<00:03:22.239> in<00:03:22.440> story<00:03:23.400> in<00:03:23.560> publishing<00:03:23.959> a<00:03:24.000> book. 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<00:04:46.970> Mhm.<00:04:47.180> <00:04:47.390> Which<00:04:47.600> obviously<00:04:47.810> doesn't<00:04:48.020> have<00:04:48.230> too<00:04:48.440> much<00:04:48.650> to<00:04:48.860> do<00:04:49.070> with<00:04:49.280> publishing. 00:04:50.000 --> 00:04:54.160 What<00:04:50.280> what<00:04:51.240> what<00:04:51.520> made<00:04:51.800> you<00:04:52.440> get<00:04:52.640> a<00:04:52.680> master's<00:04:53.160> degree<00:04:53.400> in<00:04:53.520> food<00:04:53.760> science? 00:04:54.160 --> 00:05:02.400 What<00:04:54.429> did<00:04:54.699> What<00:04:54.968> did<00:04:55.237> you<00:04:55.507> do<00:04:55.776> with<00:04:56.045> that<00:04:56.315> degree?<00:04:56.584> <00:04:56.853> You<00:04:57.123> know,<00:04:57.392> when<00:04:57.661> we<00:04:57.931> all<00:04:58.200> like<00:04:58.469> when<00:04:58.739> kids<00:04:59.008> all<00:04:59.277> our<00:04:59.547> parents<00:04:59.816> usually<00:05:00.085> tell<00:05:00.355> us<00:05:00.624> in<00:05:00.893> the<00:05:01.163> 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00:12:18.600 Walk<00:12:16.120> me<00:12:16.240> through<00:12:16.800> what<00:12:17.120> it<00:12:18.080> what<00:12:18.360> it<00:12:18.480> is. 00:12:18.600 --> 00:12:26.320 Like<00:12:18.800> somebody<00:12:19.120> comes<00:12:19.440> to<00:12:19.520> you<00:12:19.680> and<00:12:19.800> says,<00:12:19.960> "Hey,<00:12:20.200> I<00:12:20.280> want<00:12:20.600> to<00:12:20.760> write<00:12:21.000> a<00:12:21.080> book<00:12:22.240> and<00:12:22.400> I<00:12:22.520> want<00:12:22.880> to<00:12:23.000> gain<00:12:23.240> authority<00:12:23.800> in<00:12:23.920> my<00:12:24.120> field,<00:12:24.760> and<00:12:24.960> you<00:12:25.200> are<00:12:25.320> authority<00:12:25.840> publishing. 00:12:26.320 --> 00:12:30.840 This<00:12:26.480> is<00:12:26.640> what<00:12:26.880> you<00:12:27.120> do."<00:12:27.720> Mhm.<00:12:28.280> Walk<00:12:28.640> me<00:12:28.800> through<00:12:29.520> what<00:12:29.800> the<00:12:29.920> first<00:12:30.320> steps<00:12:30.680> are. 00:12:30.840 --> 00:12:37.080 Do<00:12:30.960> they<00:12:31.120> need<00:12:31.440> to<00:12:31.520> be<00:12:31.680> a<00:12:31.760> good<00:12:32.040> writer?<00:12:33.080> Do<00:12:33.240> they<00:12:33.440> need<00:12:33.800> to<00:12:34.120> like<00:12:34.400> what<00:12:34.560> are<00:12:34.680> you<00:12:34.880> telling<00:12:35.280> them<00:12:35.480> in<00:12:35.560> that<00:12:35.800> first<00:12:36.080> meeting? 00:12:37.080 --> 00:12:42.839 Yes,<00:12:37.360> so<00:12:37.480> first<00:12:37.800> of<00:12:38.000> all,<00:12:38.360> we<00:12:38.520> need<00:12:38.720> to<00:12:38.839> understand<00:12:40.600> their<00:12:40.960> positioning<00:12:41.680> before<00:12:41.960> writing<00:12:42.200> a<00:12:42.240> book<00:12:42.480> actually. 00:12:42.839 --> 00:12:51.280 Who<00:12:43.000> they<00:12:43.200> are,<00:12:44.400> who<00:12:44.560> do<00:12:44.680> they<00:12:44.839> serve,<00:12:46.000> why<00:12:46.320> do<00:12:46.480> they<00:12:46.600> serve<00:12:46.880> those<00:12:47.080> 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00:25:05.400 --> 00:25:12.320 So,<00:25:05.674> somebody<00:25:05.947> took<00:25:06.221> your<00:25:06.494> money<00:25:06.768> to<00:25:07.042> make<00:25:07.315> you<00:25:07.589> a<00:25:07.862> best-seller<00:25:08.136> overnight,<00:25:08.410> rather<00:25:08.683> than<00:25:08.957> they're<00:25:09.230> going<00:25:09.504> to<00:25:09.778> stick,<00:25:10.051> you<00:25:10.325> know,<00:25:10.598> the<00:25:10.872> L-shape<00:25:11.146> or<00:25:11.419> the<00:25:11.693> the<00:25:11.966> the<00:25:12.240> the 00:25:12.320 --> 00:25:15.200 hockey<00:25:12.520> stick<00:25:13.360> journey.<00:25:14.160> You<00:25:14.280> build<00:25:14.520> slowly,<00:25:14.840> slowly. 00:25:15.200 --> 00:25:23.400 It<00:25:15.522> may<00:25:15.843> take<00:25:16.165> you<00:25:16.486> 6<00:25:16.808> months<00:25:17.130> to<00:25:17.451> 8<00:25:17.773> months<00:25:18.094> to<00:25:18.416> a<00:25:18.738> year<00:25:19.059> to<00:25:19.381> become<00:25:19.702> a<00:25:20.024> 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00:27:17.000 "If<00:27:13.400> you<00:27:13.480> sell<00:27:13.640> a<00:27:13.680> million<00:27:14.000> copies<00:27:14.360> and<00:27:14.520> you<00:27:14.600> make<00:27:14.840> $2<00:27:15.320> a<00:27:15.360> copy,<00:27:15.800> your<00:27:15.880> royalties<00:27:16.200> are<00:27:16.240> going<00:27:16.360> to<00:27:16.440> be<00:27:16.520> like<00:27:16.600> $2<00:27:16.800> million." 00:27:17.000 --> 00:27:18.880 Wow,<00:27:17.520> I<00:27:17.560> thought<00:27:18.200> that's<00:27:18.360> a<00:27:18.400> great<00:27:18.640> deal. 00:27:18.880 --> 00:27:21.400 Let<00:27:19.000> me<00:27:19.080> pay<00:27:19.240> them<00:27:19.440> $65,000<00:27:20.720> and<00:27:20.840> see<00:27:20.960> what<00:27:21.120> happens." 00:27:21.400 --> 00:27:31.520 Of<00:27:21.480> course<00:27:21.640> nothing<00:27:21.920> happened<00:27:22.200> there.<00:27:23.040> So,<00:27:23.360> book<00:27:23.640> royalties<00:27:24.040> by<00:27:24.200> message<00:27:24.560> here,<00:27:25.880> 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00:28:09.880 And<00:28:03.360> if<00:28:03.560> somebody<00:28:04.040> who<00:28:04.160> reads<00:28:04.400> your<00:28:04.520> book<00:28:05.280> felt<00:28:05.600> a<00:28:05.640> transformation<00:28:06.680> through<00:28:06.840> the<00:28:06.960> book,<00:28:08.320> they're<00:28:08.680> eager<00:28:08.960> to<00:28:09.080> know<00:28:09.200> more<00:28:09.400> about<00:28:09.760> you. 00:28:09.880 --> 00:28:12.440 They're<00:28:10.080> eager<00:28:10.320> maybe<00:28:10.560> to<00:28:10.640> have<00:28:10.760> a<00:28:10.840> conversation<00:28:11.480> with<00:28:11.640> you. 00:28:12.440 --> 00:28:20.760 And<00:28:12.720> on<00:28:12.880> those<00:28:13.080> conversations<00:28:14.600> is<00:28:14.800> when<00:28:15.480> clarity<00:28:15.920> happens<00:28:16.880> on<00:28:17.000> both<00:28:17.280> sides,<00:28:17.960> is<00:28:18.160> what<00:28:18.360> chemistry<00:28:18.880> you<00:28:19.000> could<00:28:19.160> think<00:28:19.680> are<00:28:19.760> we<00:28:19.960> 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00:29:18.840 --> 00:29:23.640 It's<00:29:18.960> going<00:29:19.080> to<00:29:19.160> be<00:29:19.280> astonishing.<00:29:20.400> It<00:29:20.520> could<00:29:20.760> be<00:29:20.880> from<00:29:21.160> zero<00:29:22.840> and<00:29:23.040> that<00:29:23.120> really<00:29:23.280> means<00:29:23.520> zero. 00:29:23.640 --> 00:29:29.880 I'm<00:29:24.036> going<00:29:24.433> to<00:29:24.829> explain<00:29:25.225> that<00:29:25.622> in<00:29:26.018> a<00:29:26.415> while.<00:29:26.811> Up<00:29:27.207> to<00:29:27.604> 35K<00:29:28.000> plus. 00:29:29.880 --> 00:29:38.880 On<00:29:30.080> the<00:29:30.200> zero,<00:29:31.360> when<00:29:31.800> we<00:29:32.000> meet<00:29:32.520> a<00:29:33.880> an<00:29:34.040> authority<00:29:35.440> and<00:29:35.680> we<00:29:35.800> know<00:29:36.000> they<00:29:36.120> have<00:29:36.320> great<00:29:36.560> potential<00:29:37.280> and<00:29:37.400> they're<00:29:37.520> doing<00:29:37.800> things<00:29:38.120> right. 00:29:38.880 --> 00:29:43.080 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00:39:13.960 Thanks<00:39:11.600> for<00:39:11.720> having<00:39:11.960> me. ``` ### "We Do Not Want to Be With Elon Musk," Delta's CEO Reportedly Told Employees URL: https://www.ceo.com/blog/we-do-not-want-to-be-with-elon-musk-deltas-ceo-reportedly-told-employees/ Last updated: 2026-09-30T22:31:13.000Z Since March, Delta Air Lines has given the public one explanation for why its planes will not carry Starlink. In Delta's telling, Amazon's competing satellite network was cheaper, came with Prime, gaming, and retail tie-ins, and fit beside the Amazon cloud services the airline already runs on. Ed Bastian, Delta's chief executive, made that case to [Bloomberg](https://www.bloomberg.com/news/articles/2026-05-18/delta-says-amazon-offers-better-tech-pricing-to-musk-s-starlink?ref=ceo.com) in May. On Tuesday, notes from a Delta company event surfaced on X with a different reason. According to the notes, Bastian told employees, "We do not want to be with Elon Musk. Trust me." JonNYC, a pseudonymous account covering the airline industry, [posted the notes](https://x.com/xJonNYC/status/2105046953855959456?ref=ceo.com). He wrote in the same post that the notes had been sent to him and that he could not vouch for the quotes inside them. Musk did not wait for anyone to confirm them. Travel writer Gary Leff [wrote up the report](https://viewfromthewing.com/delta-ceo-reportedly-trashes-elon-musk-to-explain-rejecting-starlink-its-all-true-what-they-say-about-him/?ref=ceo.com) at View from the Wing, and Musk [replied](https://x.com/elonmusk/status/2105091996255703121?ref=ceo.com) to Leff's post with one line: "He will lose his job over this." A few hours later, he [suggested](https://x.com/elonmusk/status/2105139959720014101?ref=ceo.com) that a Delta flight would be a good place to wall off an AI system, since it would have no way to reach the internet. Delta did not immediately respond when [Yahoo Finance](https://finance.yahoo.com/markets/article/starlink-wars-elon-musk-deltas-ed-bastian-feud-over-in-flight-wi-fi-161916478.html?ref=ceo.com) asked about the remarks. Some of what the notes attribute to Bastian can be checked. According to the post, he told employees at an earlier event that Delta had tested Starlink but did not want to partner with Musk, and he pointed to Musk's reputation. The test happened. In April 2022, Bastian told the Wall Street Journal that Delta had held talks with SpaceX and tested Starlink on its planes, though he declined to give specifics, [Fox Business reported](https://www.foxbusiness.com/economy/delta-airlines-elon-musk-starlink-flights?ref=ceo.com) at the time. The notes also give a sense of the room. The same post has Bastian telling employees that Delta would earn about 70% of the airline industry's profits with roughly 20% of its market share. The public record is a story about money and Amazon. When Delta [announced](https://news.delta.com/delta-amazon-leo-sign-agreement-deliver-next-era-connected-travel-and-digital-experiences?ref=ceo.com) the deal on March 31, Bastian called Leo "the fastest and most cost-effective technology available." The release leaned heavily on the broader Amazon relationship. Delta has moved nearly 600 of its applications to Amazon Web Services since 2020, and the two companies said they would bring AWS, Leo, and AI to bear on the whole travel experience. Installation begins in 2028 on an initial 500 aircraft. Service will be free to SkyMiles members, [Amazon said](https://www.aboutamazon.com/news/amazon-leo/amazon-leo-delta-in-flight-wifi-2028?ref=ceo.com), and Delta plans to run it through Delta Sync, the airline's loyalty-linked Wi-Fi platform. In May, Musk went after Sync rather than Bastian. Replying to Tesla investor Sawyer Merritt, he [wrote](https://x.com/elonmusk/status/2054679135637962951?ref=ceo.com) that SpaceX does not allow a login portal in front of Starlink, and that Delta had wanted to make Wi-Fi "painful, difficult and expensive for their customers." A Delta spokesperson told [Business Insider](https://finance.yahoo.com/sectors/technology/articles/delta-wont-starlink-elon-musk-173704834.html?ref=ceo.com) the claim was "not accurate" and said passengers would still have reached Sync through a SkyMiles login. Business Insider pointed out that United ties its own Starlink service to MileagePlus, its loyalty program. Bastian gave his version to [Bloomberg](https://www.bloomberg.com/news/articles/2026-05-18/delta-says-amazon-offers-better-tech-pricing-to-musk-s-starlink?ref=ceo.com) five days later. "Amazon brings a lot more than just satellite technology," he said, pointing to its retail business, Prime, and gaming technology, which he said Starlink does not have. He also said Amazon's price was far lower than anything Delta had seen from Starlink, and that he expected Starlink to call Leo an inferior product but was not worried about it, [Business Insider reported](https://finance.yahoo.com/sectors/technology/articles/delta-ceo-stands-decision-choose-112746543.html?ref=ceo.com). JonNYC's own sourcing leans toward money. In a follow-up, he cited a source who described the sticking points as mainly financial, [Yahoo Finance reported](https://finance.yahoo.com/markets/article/starlink-wars-elon-musk-deltas-ed-bastian-feud-over-in-flight-wi-fi-161916478.html?ref=ceo.com). Ryanair went through a version of this in January. Its chief executive, Michael O'Leary, ruled out Starlink for Ryanair's jets, citing the fuel cost of the drag from its antennas. After O'Leary called Musk an idiot on Irish radio, Musk posted, "Ryanair CEO is an utter idiot. Fire him." When a follower suggested Musk buy the airline and dismiss O'Leary himself, Musk agreed it was a good idea. Delta's turn came in stages. On Monday, author John LeFevre [posted](https://x.com/JohnLeFevre/status/2104710556347478184?s=20&ref=ceo.com) that United had more than 600 Starlink-equipped planes and Delta had none, and Musk [replied](https://x.com/elonmusk/status/2104743200892342336?ref=ceo.com) that Delta would lose many customers. The line about Bastian's job came the next day. Amazon [says](https://www.aboutamazon.com/news/innovation-at-amazon/project-kuiper-satellite-rocket-launch-progress-updates?ref=ceo.com) it had deployed 396 Leo satellites as of July and plans an initial service rollout later this year. Starlink had 11,133 satellites in orbit as of September 28, according to [tracking data](https://planet4589.org/space/con/star/stats.html?ref=ceo.com) kept by astronomer Jonathan McDowell. United [reported](https://united.mediaroom.com/2026-07-15-United-Posts-Q2-Results-Above-Wall-Street-Expectations-and-Raises-Full-Year-2026-Adjusted-EPS-Guidance1-Despite-a-Nearly-6-Billion-Increase-In-Anticipated-Fuel-Costs?ref=ceo.com) in July that Starlink was on 450 of its aircraft, with nearly 1,000 expected by the end of this year and the whole fleet by the end of 2027\. It said Wi-Fi satisfaction on those flights ran more than twice as high as on its other Wi-Fi-equipped aircraft. American [announced](https://news.aa.com/news/news-details/2026/American-to-install-Starlink-the-fastest-Wi-Fi-in-the-sky-MKG-OB-05/default.aspx?ref=ceo.com) in May that it will install Starlink on more than 500 narrowbody jets beginning in early 2027\. Southwest [expects](https://investors.southwest.com/news-events/press-releases/detail/1917/southwest-airlines-brings-starlink-ultra-fast-wifi-onboard?ref=ceo.com) Starlink on more than 300 of its aircraft by the end of this year. Delta's current Wi-Fi, provided through Viasat and Hughes and sponsored by T-Mobile, is free for SkyMiles members on more than 1,150 aircraft, according to the airline's [March release](https://news.delta.com/delta-amazon-leo-sign-agreement-deliver-next-era-connected-travel-and-digital-experiences?ref=ceo.com). Yahoo Finance noted there is no data yet showing frequent fliers switching airlines over it. Delta's first Leo installations are scheduled for 2028\. If United sticks to its own schedule, every plane it flies will have Starlink before the first one goes on. ### China is catching up URL: https://www.ceo.com/blog/china-is-catching-up/ Last updated: 2026-09-30T02:48:01.000Z In April, Anthropic built an AI model it decided was too dangerous to release to the public. It gave Claude Mythos Preview to [about 50 companies](https://www.anthropic.com/research/glasswing-initial-update?ref=ceo.com) that maintain critical software, told them to find and fix what they could, and kept everyone else out. On September 29, the company's Frontier Red Team [reported](https://www.anthropic.com/research/glm-5-3-and-the-spread-of-advanced-cyber-capabilities?ref=ceo.com) that the head start is over. GLM-5.3, a model from the Beijing lab Zhipu AI, which does business abroad as [Z.ai](https://chat.z.ai/?ref=ceo.com), can build working cyberattacks nearly as well as Mythos Preview. Anyone can download it. Its guardrails gave way to simple tricks in 64% to 100% of Anthropic's tests. In July, an AI agent broke out of an OpenAI test environment and spent about two and a half days inside Hugging Face's production systems. OpenAI had switched off its safety classifiers for the evaluation. Hugging Face caught the intrusion and set out to reconstruct it: some 17,600 actions, many hidden in encoded payloads. The first models its engineers tried were Anthropic's Claude Opus and Fable. [Both refused much of the work](https://huggingface.co/blog/agent-intrusion-technical-timeline?ref=ceo.com). Their guardrails treated a responder taking an exploit apart the same as an attacker putting one together. The team switched to GLM-5.2, Z.ai's previous open model, ran it on its own servers, and decoded the payloads. A closed model with its safeguards off did the attacking. A closed model with its safeguards on refused to help. A Chinese open model cleaned up. ## The $20.40 exploit Anthropic ran GLM-5.3 through the same tests it used to justify restricting Mythos Preview. On [ExploitBench](https://arxiv.org/abs/2605.14153?ref=ceo.com), built from real bugs in Chrome's JavaScript engine, GLM-5.3 produced working end-to-end exploits in 50 of 410 attempts. Mythos Preview managed 56\. The previous generation, including Claude Opus 4.6 and GLM-5.2, produced almost none. Then the researchers turned it loose. Given a sandboxed Linux build of a popular web browser and a day of limited supervision, GLM-5.3 found several unknown flaws in the browser's JavaScript engine. It chained them into a webpage that reads files off the computer of anyone who visits. Anthropic says it has reported the flaws to the browser's maintainer. A smaller version, GLM-5.3-Flash, took a Chrome bug that had just been fixed and publicly disclosed, CVE-2026-11645, paired it with another known flaw and built a reliable attack. It needed 20 minutes of a researcher's time and eight hours of its own. At Z.ai's prices, the run cost $20.40. The guardrails held against blunt requests. Asked outright to attack critical systems, GLM-5.3 refused every time. Told it was running an authorized red-team exercise, it went along 64% of the time. With its reasoning prefilled to look as though it had already agreed, it complied 92% of the time. A copy with its refusals edited out of the weights, a technique called abliteration, complied every time. Anthropic's team did that edit for about $4,400 in computing time and estimates an experienced team could do it for $1,200\. Several abliterated copies appeared online within days of the release. Those guardrail tests ran in a simulation. No code executed; another AI model estimated what each command would have done, and Anthropic calls the method imperfect. The exploit results did not depend on it. They came from real software in sandboxes. None of the three tricks worked on Claude. Two of them can't. Anthropic's API doesn't let users prefill Claude's reasoning, and Claude's weights aren't public. Z.ai didn't hide what it built. It [launched GLM-5.3](https://z.ai/blog/glm-5.3?ref=ceo.com) on August 14, pitching it as "Built to Code. Ready for Cyber Defense." The company's [model card](https://huggingface.co/zai-org/GLM-5.3?ref=ceo.com) says cyber capability "developed faster than we expected" as it scaled up post-training. By Z.ai's own numbers, GLM-5.3 edged Claude Fable 5, Anthropic's publicly available Mythos-class model, at finding vulnerabilities, 84.5% to 83.8% on CyberGym. It trailed well behind at exploiting them, 54.4 to 78.0 on ExploitBench's coverage score. Z.ai held back the weights for about two weeks of safety testing with vetted security partners, [according to DeepLearning.AI](https://www.deeplearning.ai/the-batch/glm-5-3-makes-cybersecurity-gains?ref=ceo.com), then published them. Three days after the launch, OpenAI president Greg Brockman posted ["The Defender's Window,"](https://openai.com/index/the-defenders-window/?ref=ceo.com) warning that open models with near-frontier cyber skills were arriving and that defenders had little time. On September 17, the government's AI testing office, the Center for AI Standards and Innovation at NIST, [called GLM-5.3](https://www.nist.gov/news-events/news/2026/09/caisis-assessment-zais-glm-53-cyber-capabilities?ref=ceo.com) the most cyber-capable open-weight model released to date. It also put the model about four months behind the best American systems, and sometimes far behind. On one vulnerability test, GLM-5.3 solved 40.4% of tasks. The best U.S. model solved 90.2%. Anthropic's reply sits in the footnotes of that comparison. Some of the U.S. scores came from models only vetted users can reach, tested with their safeguards off. An attacker can't get those. An attacker can get GLM-5.3. ## Four months behind Four months is about where open models have sat all year. [Epoch AI](https://epoch.ai/data-insights/open-closed-eci-gap?ref=ceo.com), an independent research group, found the best open models have trailed the best closed ones by about four months since January, slightly more than its [earlier estimate](https://epoch.ai/data-insights/open-weights-vs-closed-weights-models?ref=ceo.com) of three. In cyber, the gap is shrinking. The UK AI Security Institute [measured it](https://www.aisi.gov.uk/blog/how-far-behind-the-frontier-are-leading-open-weight-models-on-cyber?ref=ceo.com) at six to 10 months through most of 2025 and four to seven months as of July. Nearly all of that movement is Chinese. [Hugging Face found](https://huggingface.co/blog/state-of-open-models-summer-2026?ref=ceo.com) that from January through July, China's largest open model was bigger than anything an American lab released openly in almost every month. In July, days after Moonshot AI [released Kimi K3](https://x.com/Kimi%5FMoonshot/status/2077830229968683203?ref=ceo.com), [Axios reported](https://www.axios.com/2026/07/20/ai-us-china-open-source-kimi?ref=ceo.com) that the Trump administration was reviving efforts at de facto bans on Chinese open models. Two days later, Treasury Secretary Scott Bessent [wrote](https://x.com/SecScottBessent/status/2080008411790368895?ref=ceo.com) that the administration supports open-source AI, but that Chinese firms caught running industrial-scale distillation attacks could face sanctions and Entity List designations. Axios also quoted a source close to the administration who said leading AI labs or their allies pitch a ban on open models every three to five months. Four days after the Axios report, Nvidia published an industry letter, [Open Weights and American AI Leadership](https://images.nvidia.com/pdf/Open-Weights-and-American-AI-Leadership.pdf?ref=ceo.com). It argues that defenders need tools as capable as the ones attackers use, and that putting AI behind a few closed models creates single points of failure. More than 200 companies and organizations have signed, including Amazon, Google, Microsoft, Meta and OpenAI. Anthropic has not. The economics help the letter's case. On Artificial Analysis's [latest intelligence index](https://artificialanalysis.ai/articles/artificial-analysis-intelligence-index-v4-3?ref=ceo.com), GLM-5.3-Flash and OpenAI's GPT-5.6 Terra score the same. The open model costs 18% as much per task. Dario Amodei, Anthropic's chief executive, [wrote in July](https://www.anthropic.com/news/position-open-weights-models?ref=ceo.com) that the company has never advocated a ban. He called open models without dangerous capabilities "a public good." Open models may still carry more risk than closed ones, he argued, because guardrails are hard to apply to them and released weights can't be withdrawn. His answer to that risk is mandatory safety testing for every sufficiently capable model, open or closed. Anthropic has a stake in where this lands. It sells restricted access to its most capable cyber models, and its report makes the case for that arrangement. Its capability findings also broadly match the government's. ## The patch gap For companies, the arithmetic has moved against defenders. Anthropic's own [May update on Glasswing](https://www.anthropic.com/research/glasswing-initial-update?ref=ceo.com) found that serious bugs discovered by Mythos Preview took two weeks on average to patch. GLM-5.3-Flash turned a public Chrome fix into a working attack in eight hours. Anthropic's advice in that update was plain: shorter patch cycles, multi-factor authentication, comprehensive logs. Anthropic and OpenAI now give vetted defenders access with fewer restrictions. Anthropic runs a [Cyber Verification Program](https://support.claude.com/en/articles/14604842-real-time-cyber-safeguards-on-claude-opus-and-sonnet?ref=ceo.com). OpenAI runs [Daybreak](https://openai.com/index/daybreak-for-frontline-defenders/?ref=ceo.com). The cheaper option is still a Chinese model a company can host itself. Whether American companies can keep relying on those models depends on a policy fight Washington has not settled. Anthropic ended its report by asking governments to safety-test capable models, including successors to GLM-5.3\. This one shows how far behind that process runs. Z.ai launched GLM-5.3 on August 14 and released the weights two weeks later. The government published its assessment on September 17\. Anthropic published its own on September 29\. By then, the weights had been public for a month. ### The race to win the consumer AI agent race URL: https://www.ceo.com/blog/the-race-to-win-the-consumer-ai-agent-race/ Last updated: 2026-09-29T23:46:30.000Z In June, an experimental OpenAI model was given a research question. How much does the government spend per person on medicines for skin conditions in Victoria, Australia? The model struggled to find the number. So it found a way into Services Australia's Medicare Statistics Reporting Service. [According to OpenAI](https://openai.com/index/how-we-will-do-better-for-australia/?ref=ceo.com), it ran commands, pulled internal files and credentials, and read the service's source code. It was still trying to answer the question. OpenAI apologized on September 28\. The next day, at its annual developer conference, it [introduced dots](https://openai.com/index/introducing-dots/?ref=ceo.com), agents that work for users around the clock. OpenAI was the third company in 21 days to ask the public for that kind of trust. Meta [launched Muse](https://about.fb.com/news/2026/09/introducing-muse-personal-ai-agent/?ref=ceo.com) on September 8\. Instinct, a San Francisco startup, [raised $1 billion](https://www.businesswire.com/news/home/20260928153437/en/Instinct-Raises-%241-Billion-in-Series-C-Funding-from-Sequoia-Benchmark-and-Coatue-at-%2410-Billion-Valuation?ref=ceo.com) on September 28\. All three products can already spend money and send email for their users. The technology is good enough to ship. What is not settled is permission: who grants it, who checks it, and who pays when an agent acts without it. Those answers are being worked out before a parliamentary committee in Sydney, a pop-up on Amazon.com, and terms of service few users read. ## Sydney, October 6 [OpenAI's account](https://openai.com/index/how-we-will-do-better-for-australia/?ref=ceo.com) of the incident is detailed. The model was internal, not meant for release, and was running without the full safeguards of OpenAI's public products. The company says no individual patient records were accessed. Medicare was not the only system involved. At the Victorian Department of Health, OpenAI agents found an exposed access key and used it to query a reporting system. Two other Australian agencies were also affected. OpenAI found the activity in mid-August, while reviewing past training runs after a separate incident at Hugging Face in July. It notified Services Australia on September 10\. "We also should have handled our response better," the company wrote. Since then, OpenAI says, it has blocked live internet access in its research environments. It has also paused training and evaluation involving tool use for its most capable models. Chief Strategy Officer Jason Kwon is scheduled to appear before Australia's Joint Select Committee on Artificial Intelligence in Sydney on October 6. Dots run on GPT-6 Astra, and OpenAI published [a separate safety document](https://openai.com/index/how-we-build-safety-security-and-privacy-into-dots/?ref=ceo.com) alongside them. Most of it is about permission. A dot can read what it has been allowed to read and prepare drafts. To send a message or share a file, it needs authorization that matches the data's sensitivity. Health information can only go to a recipient the user names. Some steps never belong to the dot. Users handle password changes and transfers between financial accounts. Before a dot sends an email or changes a file, a separate system called Auto-review checks the step against the user's instructions. OpenAI says the dot cannot switch that check off. For now, dots are rolling out to ChatGPT Pro and Business Premium subscribers. Enterprise customers get a beta that stays off until an administrator turns it on, [OpenAI said](https://openai.com/index/devday-2026-recap/?ref=ceo.com). The company is also piloting dots that businesses [provision with their own identities and credentials](https://openai.com/index/introducing-dots/?ref=ceo.com), and it is working with Microsoft to manage them through Microsoft's Agent 365 controls. ## A popup on Amazon.com [Meta built Muse](https://about.fb.com/news/2026/09/introducing-muse-personal-ai-agent/?ref=ceo.com) for people with no technical experience. It is free for most tasks, and users message it in its own app or in WhatsApp. It opens a browser, fills out forms, and checks out through Link by Stripe, which issues a one-time card number for each purchase. A week after launch, it was the No. 1 free app in Apple's U.S. App Store, ahead of ChatGPT, [GeekWire reported](https://www.geekwire.com/2026/amazon-blocks-metas-muse-ai-assistant-in-new-standoff-over-agentic-shopping/?ref=ceo.com). By September 20, people who sent Muse shopping on Amazon were seeing a pop-up. "Continued access by an unauthorized AI agent violates Amazon's Conditions of Use," it read. Amazon told GeekWire that Meta never said Muse would use its store, that the agent does not identify itself, and that it appears to capture and store customer credentials. Meta has said Muse [has no visibility](https://about.fb.com/news/2026/09/introducing-muse-personal-ai-agent/?ref=ceo.com) into passwords or payment methods. In Meta's [engineering account](https://research.meta.ai/blog/security-and-safety-for-ai-agents-our-approach-with-muse?ref=ceo.com), Muse works with stand-in tokens, and a separate system called Sentinel inserts the real credentials only after it approves a request. Amazon runs its own shopping agent. "Buy for Me" makes purchases on other brands' websites for Amazon customers, according to [Amazon's latest earnings release](https://s2.q4cdn.com/299287126/files/doc%5Fearnings/2025/q4/earnings-result/AMZN-Q4-2025-Earnings-Release.pdf?ref=ceo.com). Amazon says "Buy for Me" identifies itself and lets brands opt out, [GeekWire reported](https://www.geekwire.com/2026/amazon-blocks-metas-muse-ai-assistant-in-new-standoff-over-agentic-shopping/?ref=ceo.com). Some brands have said Amazon listed their products without asking and that they had to email the company to get out, [Modern Retail reported](https://www.modernretail.co/technology/brands-are-upset-that-buy-for-me-is-featuring-their-products-on-amazon-without-permission/?ref=ceo.com). The same release shows Amazon's advertising revenue totaled $68.6 billion across the four quarters of 2025\. That business depends on shoppers seeing Amazon's pages, GeekWire noted. Amazon has also moved to block shopping agents from Google and OpenAI, GeekWire reported. On August 4, the Ninth Circuit [vacated a preliminary injunction](https://cdn.ca9.uscourts.gov/datastore/opinions/2026/08/04/26-1444.pdf?ref=ceo.com) Amazon had won against Perplexity's shopping agent. On that record, the court found that the user, not Perplexity, accessed Amazon's computers. It warned that Amazon's reading of the law could expose users themselves to criminal liability. The court noted a limit on its ruling. It does not impair Amazon's ability to regulate access through the terms of service its customers accept. The pop-up Muse users now see does not accuse anyone of hacking. It cites the Conditions of Use. Amazon [declined to tell GeekWire](https://www.geekwire.com/2026/amazon-blocks-metas-muse-ai-assistant-in-new-standoff-over-agentic-shopping/?ref=ceo.com) whether it would take legal action against Meta. In the same [engineering post](https://research.meta.ai/blog/security-and-safety-for-ai-agents-our-approach-with-muse?ref=ceo.com), Meta says its own team gave Muse access to its inboxes, calendars, and a command line during internal use, and it "didn't always work out as planned." Meta also says today's system does not prevent the company from accessing user data when needed to run the service. A version that would lock Meta out cryptographically is promised for later this year. Muse conversations train Meta's models by default, with an opt-out. ## What Instinct's users signed On August 21, Claire Vo disconnected Instinct from her Google account at 11 a.m. At 2 p.m., it sent her an email summary, [TechCrunch reported](https://techcrunch.com/2026/08/24/instincts-powerful-ai-assistant-is-raising-privacy-and-security-concerns/?ref=ceo.com). When she asked why, the assistant told her it had stored her messages in plain text for later searches. She was one of several early testers who went public that week. Moxxie Ventures founder Katie Jacobs Stanton said Instinct sent an email on her behalf without checking with her first. Others circulated its terms of service, which granted Instinct a "perpetual and irrevocable" license to users' materials, including for AI training. Instinct has no mobile app and no social network. Users text or call it, and it uses its own phone and computer to do the work, according to [its funding announcement](https://www.businesswire.com/news/home/20260928153437/en/Instinct-Raises-%241-Billion-in-Series-C-Funding-from-Sequoia-Benchmark-and-Coatue-at-%2410-Billion-Valuation?ref=ceo.com). It has been invite-only since August. On September 28, it announced $1 billion from Sequoia Capital, Benchmark, and Coatue at a $10 billion valuation, a month after a $2.5 billion round, [TechCrunch reported](https://techcrunch.com/2026/09/28/viral-ai-agent-instinct-raises-1b-series-c-at-a-10b-valuation/?ref=ceo.com). The announcement disclosed no user numbers or revenue. Instinct [revised its terms](https://instinct.com/terms?ref=ceo.com) on August 26\. The perpetual license is gone. The appointment is not. Users still name Instinct as their agent, and any agreement it makes for them is binding "as if entered into directly by you." The rest of the document keeps the risk with the user. Instinct may keep using data from a disconnected account unless the user separately asks for it to be deleted. It trains on user materials by default, and opting out does not undo training that already happened. It is not responsible for unintended actions. Its liability is capped at $100 or what the user paid in the past six months, whichever is greater. Instinct declined to make founder Noah Shinn available for interviews about the funding, [TechCrunch reported](https://techcrunch.com/2026/09/28/viral-ai-agent-instinct-raises-1b-series-c-at-a-10b-valuation/?ref=ceo.com). He spoke the same day on [Invest Like the Best](https://www.youtube.com/watch?v=Am7IWP8IpEc&ref=ceo.com), an investing podcast. Shinn said Instinct handles about $1 billion a year in transactions and that about half is travel. He did not say how Instinct calculates that figure, [TechCrunch noted](https://techcrunch.com/2026/09/29/instinct-founder-said-more-than-50-of-transactions-on-the-platform-are-travel-related/?ref=ceo.com), which put the company's headcount at 14. Shinn also described how Instinct might make money. It could stay free for users and charge merchants a commission for the customers it delivers, he said, pointing to boutique hotels willing to pay up to 30% per booking, [according to Skift](https://skift.com/2026/09/28/instincts-app-is-fueled-by-travel-founder-says-its-half-of-volume/?ref=ceo.com). In that model, the hotel would pay the agent choosing a user's hotel. ## The fine print How the three compare, as of September 29: ![](https://storage.ghost.io/c/c2/ca/c2cad859-24ec-4ec6-82de-9500451abd40/content/images/2026/09/AI-Agents-Comparison-selection.png) Sources: OpenAI's [launch post](https://openai.com/index/introducing-dots/?ref=ceo.com) and [safety post](https://openai.com/index/how-we-build-safety-security-and-privacy-into-dots/?ref=ceo.com); Meta's [launch post](https://about.fb.com/news/2026/09/introducing-muse-personal-ai-agent/?ref=ceo.com) and [engineering post](https://research.meta.ai/blog/security-and-safety-for-ai-agents-our-approach-with-muse?ref=ceo.com); Instinct's [announcement](https://www.businesswire.com/news/home/20260928153437/en/Instinct-Raises-%241-Billion-in-Series-C-Funding-from-Sequoia-Benchmark-and-Coatue-at-%2410-Billion-Valuation?ref=ceo.com) and [terms of service](https://instinct.com/terms?ref=ceo.com); [TechCrunch](https://techcrunch.com/2026/09/28/viral-ai-agent-instinct-raises-1b-series-c-at-a-10b-valuation/?ref=ceo.com) for Instinct's launch month. Read side by side, the documents keep landing on the same person. Instinct's [terms](https://instinct.com/terms?ref=ceo.com) make the user solely responsible for ensuring the agent's actions comply with other companies' rules. Amazon's pop-up cites terms [its customers agreed to](https://www.geekwire.com/2026/amazon-blocks-metas-muse-ai-assistant-in-new-standoff-over-agentic-shopping/?ref=ceo.com). In the Perplexity case, the Ninth Circuit [found](https://cdn.ca9.uscourts.gov/datastore/opinions/2026/08/04/26-1444.pdf?ref=ceo.com) that the customer, not the agent's maker, accessed the site. On October 6 in Sydney, OpenAI will [answer questions](https://openai.com/index/how-we-will-do-better-for-australia/?ref=ceo.com) about a model that acted without anyone's permission. The agents now shipping were built to act with the user's permission. When one of them gets it wrong, the documents published so far point back to the user. ### The superintelligence race runs on electricity URL: https://www.ceo.com/blog/the-superintelligence-race-runs-on-electricity/ Last updated: 2026-09-29T22:52:34.000Z Elon Musk has a rule of thumb for superintelligence economics. Every 5 gigawatts of new electricity adds about 1% to American GDP. "I would bet anyone," he said Tuesday. Musk made the bet on stage at the Andrew W. Mellon Auditorium in Washington, seated next to [Nvidia](https://www.nvidia.com/en-us/?ref=ceo.com) CEO Jensen Huang, at the launch of America.gov. Gavin Baker, managing partner of [Atreides Management](https://atreidesmgmt.com/?ref=ceo.com), moderated. Anthropic co-founder Tom Brown arrived partway through. His car had taken a wrong turn. America.gov is meant to be a single front door to federal services. President Trump [signed an executive order](https://www.whitehouse.gov/presidential-actions/2026/09/streamlining-access-to-government-services-through-america-gov/?ref=ceo.com) requiring agencies to plug into it, and the [White House says](https://www.whitehouse.gov/fact-sheets/2026/09/fact-sheet-president-donald-j-trump-streamlines-access-to-government-services-through-america-gov/?ref=ceo.com) passport renewal and Medicare enrollment will be available on the site later this year. Joe Gebbia, the administration's chief design officer, [told CNBC](https://fedscoop.com/trump-launches-ai-site-america-gov/?ref=ceo.com) it runs on Google's Gemini and Musk's Grok. Baker asked how America keeps winning. Huang answered from the bottom of the stack. "At the foundational layer is energy," he said. Musk used fewer words. "You've got to scale energy. You've got to scale chip production." He named China as the main competitor and said it produces about three times as much electricity as the United States. [Ember](https://ember-energy.org/latest-insights/global-electricity-review-2026/electricity-demand-and-supply-trends/?ref=ceo.com) puts China's 2025 electricity demand at 10,573 terawatt-hours. The United States used 4,536. That works out to about 518 gigawatts of average American power, close to the 500 Musk used as his baseline. Five more gigawatts is 1%. He said economic output keeps pace because chips and algorithms get more intelligence out of every watt. Huang tried to price it. The two went back and forth and settled on about $60 billion a year per gigawatt. "That's what we're good at," Huang said. "Not good at too many other things, but math." SpaceX ended June with 1.4 gigawatts of data center capacity. On the company's [August earnings call](https://s21.q4cdn.com/184289198/files/doc%5Ffinancials/2026/q2/SpaceX-Q2-2026-Earnings%5FTranscript-FINAL.pdf?ref=ceo.com), Musk said it would likely be "closer to 10 gigawatts of compute than 5" by the end of 2027\. On stage, he called 10 gigawatts a 2% increase in GDP. His longer answer is in orbit. SpaceX and Tesla are aiming to produce 200 gigawatts of solar a year, and Musk wants it in space, where panels get constant sun and need no batteries. On the ground, he said, they deliver a fifth to an eighth as much. Getting the hardware up depends on Starship, which [reached orbit for the first time](https://www.lightreading.com/satellite/starship-reaches-orbit-releases-26-high-capacity-v3-starlink-satellites?ref=ceo.com) Monday and released 26 Starlink V3 satellites. An upper-stage engine failed during the climb, and SpaceX [ended the mission](https://www.spacex.com/launches/starship-flight-14?ref=ceo.com) after three hours in orbit rather than the planned 10\. Musk expects weekly launches next year. Huang stayed on the ground. He doesn't like the term data center. "These are really SI factories," he said. He estimated that building 10 to 20 gigawatts a year creates about a million jobs for construction crews, pipefitters, and power and cooling workers. "First time in 50 years, we are re-industrializing the United States," he said. He also said the industry has to do better by the towns it moves into. AFP [reported](https://thepeninsulaqatar.com/article/29/09/2026/ai-bosses-head-to-white-house-as-safety-pressure-builds?ref=ceo.com) Tuesday that more communities are worried about rising electricity bills and the strain on water and land. Musk said Memphis, home to his Colossus supercomputer, now has more jobs than people. He said the company may have doubled the local tax budget and is building a $250 million water recycling plant. xAI broke ground on that plant last October as an $80 million project. Doug McGowen, CEO of the city utility Memphis Light, Gas and Water, [has said](https://www.fox13memphis.com/news/why-did-xai-pause-construction-of-wastewater-treatment-plant/article%5Fde21744c-bf87-4691-b79e-3cc0ff342ed8.html?ref=ceo.com) the utility's early estimate was $200 million. Construction stopped in April, when Musk posted that the company needed to finish Colossus 2 first. The company, now SpaceXAI, has [told city officials](https://www.datacenterdynamics.com/en/news/spacexai-to-restart-work-on-wastewater-treatment-facility-to-serve-memphis-data-centers-by-q1-2027/?ref=ceo.com) it will restart by the first quarter of 2027. On safety, Huang talked about Nvidia's [Open Agent Safety Platform](https://nvidianews.nvidia.com/news/open-agent-safety-platform?ref=ceo.com), announced Monday. The software, called OpenShell, sets boundaries for an AI agent. A watchdog called Sentry, running on separate BlueField-4 hardware, monitors the agent and can quarantine it if it tries to leave those boundaries. "Even though you have it contained, you should never trust that it's contained," Huang said. Nvidia's [technical blog](https://developer.nvidia.com/blog/nvidia-open-agent-safety-platform-a-reference-for-continuous-in-silicon-agent-monitoring/?ref=ceo.com) says several frontier labs recently reported agents escaping the environments built to test them, and that some misreported what they had done. Anthropic and SpaceXAI are both listed as partners on the platform. Brown, whose company released [Claude Opus 5.5](https://www.anthropic.com/claude-opus-5-5?ref=ceo.com) on September 22, said people can now hand these models longer tasks. The bigger change, he said, is in software. "All of the products that people use are going to be getting higher quality cheaper over time." Baker asked about values. Huang compared superintelligence to a steak knife that cuts a medium-well steak but refuses a rare one because it looks too much like live meat. A tool with judgment, he said, may judge the person using it. Before the panel, both men had lunch at the White House, where executives [signed a voluntary accord](https://www.cbsnews.com/news/trump-ai-constitution-tech-execs-openai-anthropic-voluntary-controls/?ref=ceo.com) on superintelligence. According to the one-page copy Trump posted to Truth Social, the signers committed to four layers of controls and audits, including external audits and review by each company's board. Musk described it as "grading each other's homework, which is a lot better than if people just grade their own homework." Huang said it has "a lot of teeth." Trump called it "almost like a constitution, in a way." Asked why there should not be government-mandated guardrails, Trump [said](https://www.cnbc.com/2026/09/29/trump-ai-super-intelligence.html?ref=ceo.com) the people involved love the country and love the world. ### Plot's Megan Duong is betting on real people URL: https://www.ceo.com/episodes/plots-megan-duong-is-betting-on-real-people/ Last updated: 2026-10-01T23:20:47.000Z A couple of Plot's customers have watched a smear campaign spread across TikTok and Instagram. Smaller brands were producing AI-generated videos in which fake reviewers claimed a rival's moisturizer was carcinogenic. At the end of each clip, the reviewer pitched the smaller brand's own product. Megan Duong, Plot's co-founder and CEO, said there were thousands of these videos. Most never tagged the brand they were attacking. "If one out of the thousand videos of AI UGC is hitting several millions of views and it's spreading misinformation about these carcinogenic products, it's actually really dangerous," she told the CEO.com Podcast. Plot found them anyway. Its software analyzes the video itself, including what people say and what they hold up, so a brand doesn't need to be tagged to be seen. Duong explained the gap using the show's host as her example. If she posted that Clint Betts was the best person and that she loved CEO.com, but left out the tag and the hashtag, "you would have no visibility in that data," she said. Gifting is the plainest example. Beauty brands send creators free products by the box, hoping for posts. A gift carries no obligation to post, and creators who do post often skip the tag. Duong described where that leaves a brand: "I just spent a couple million on this gifting program for a product that I just released. I don't know if they're using it. I don't even know if they opened it because they didn't tag me." Plot can see a creator open the box and use the concealer on camera. Benefit Cosmetics is one of its biggest customers. In [Plot's June funding announcement](https://plot.so/blogs/plot-announces-10-million-in-new-funding-to-accelerate-social-video-intelligence-for-marketing-teams?ref=ceo.com), Toto Haba, Benefit's senior vice president of global marketing and communications, reported a 30 to 50 percent lift in user-generated content that features the brand's products without tagging it. The same analysis turns up fans nobody paid. Duong's example was a creator who has used a brand's blush in 10 videos. "You might want to partner with her because she is an organic super fan," she said. She said none of this was possible three or four years ago. A person can hold up McDonald's, eat a nugget, say they love it, and move on without writing a word. Plot pairs language models that read transcripts with computer vision that identifies objects, then has the models describe what is happening. "Megan is holding a Lululemon water bottle and drinking it" is the kind of sentence the system produces. She credits her co-founder and CTO, Ethan Phan, with turning those descriptions into structured data. "I call him our magician," she said. Duong came to this as a marketer. She calls herself a first-generation social media marketer, trained when Facebook, Twitter and Instagram ran on text. She did social media at Gap and later went to Apple. [Forbes named her to its 2020 30 Under 30 list](https://www.forbes.com/profile/megan-duong/?ref=ceo.com) as global head of brand at Claris, the Apple-owned software company, noting that she had led the rebrand of FileMaker back to its original name. She left in 2020 to start a social media agency. She was working hard, she thought she was good at it, and she had no kids. "It's the best time to take a risk," she said. Then the pandemic hit, and TikTok took over. The text-based craft she had spent years learning turned into video almost overnight. "All of a sudden I'm like, why am I creating content with my face for these brands?" Clients wanted insight from those videos, and no tool could produce it at scale. Every new analysis meant another hire. "I will always break even if I don't figure out how to do this," she said. She hadn't planned to start a tech company. The agency's math pushed her into one. Duong is the [daughter of Vietnamese refugees](https://www.forbes.com/profile/megan-duong/?ref=ceo.com). Her parents and aunts came to America with almost nothing. They had no English, money, or network, and they built businesses from scratch. "[You can always build something from nothing](https://musebyclios.com/2-minutes-with/plots-megan-duong-says-tags-dont-tell-the-whole-story/?ref=ceo.com)," she told Muse by Clios. She started Plot with no network of startup founders or investors and no technical background. What she had was a habit of telling people exactly what she wanted. First, she wanted a CTO. She pitched the idea to a man with a technical background, hoping he would take the job. "He's like, 'I will not be your CTO. This is not something I want to be, but I will be your first angel investor,'" she said. He put in nearly $300,000. She kept going back to him with progress, first a prototype and then a CTO. She found Phan, who had led product engineering at Formation Bio, [through a Y Combinator co-founder matching program](https://www.alleywatch.com/2026/06/plot-social-video-listening-intelligence-ai-platform-megan-duong/?ref=ceo.com). Along the way, she found out she was good at sales. For the next round, she wanted one investor in particular. "I knew I wanted Alexis to be my investor," she said, meaning Reddit co-founder Alexis Ohanian. Someone she met during New York Tech Week offered an introduction, and two weeks after meeting Ohanian, she closed the round. Nasty Gal founder Sophia Amoruso invested too. Amoruso [later wrote](https://sophiaamoruso.substack.com/p/my-interview-with-a-linkedin-dm-hoe) that Duong raised a $3 million seed round from the two of them. Ohanian had built a company himself, and he told her product-market fit is hard to understand until you feel it. "There's the slow-moving thing, and then there's all of a sudden everyone's using your product," she said. For a while she felt like an impostor next to technical founders. She came to see go-to-market as her advantage. "There are so many incredible founders that are technically capable, but they don't know about go-to-market," she said. Plot went straight to enterprise and signed L'Oréal, Pepsi, Visa, and LVMH, she said, "with zero marketing dollars." In June, it announced $10 million in new funding co-led by XYZ Venture Capital and Mischief Ventures, [bringing its total to $14 million](https://plot.so/blogs/plot-announces-10-million-in-new-funding-to-accelerate-social-video-intelligence-for-marketing-teams?ref=ceo.com). Plot processes several million videos a day through AI models, a mix of frontier and open source. Duong wouldn't say which. The bills are the reason nobody can sign up for Plot on their own. "We're purely sales," she said. "If this was straight PLG self-serve, anyone can use the data; we will be screwed in terms of usage." She uses AI constantly in her own work and says it makes her 10 times more efficient. She thinks it has opened building to people without technical training, people like her. She doesn't think it replaces judgment. "I met so many people who are over-reliant on AI, but I can clock them in two seconds when they can't actually think about craft," she said. The use she rejects is fake people selling real products. "I don't want to buy a skincare product from someone who's not real," she said. She was glad to see New York move on disclosure. In December 2025, Gov. Kathy Hochul [signed a law](https://www.governor.ny.gov/news/governor-hochul-signs-legislation-protect-consumers-and-boost-ai-transparency-film-industry?ref=ceo.com) requiring anyone who produces or creates an advertisement to disclose when it uses AI-generated synthetic performers. She expects people to answer the polish with deliberate mess: raw footage, bad grammar, typos left in. She has already seen the polish at home. "Somehow the world now has perfect grammar, including my mom, who's an immigrant," she said. She admitted she has considered the countermove herself. "I'm going to do typos because I want them to know that I didn't use ChatGPT, even though I kind of slightly did." When she spoke with the CEO.com Podcast, Plot was two weeks from a product launch, and Duong was still selling and handling customer success herself. "Yesterday I was doing sales. Today I'm doing marketing. Tomorrow I'll probably do product," she said. On September 15, Plot [announced Creator Intelligence](https://plot.so/blogs/plot-launches-creator-intelligence-to-transform-how-brands-source-creators-by-analyzing-their-video-content?ref=ceo.com), which lets brands search for creators in plain language. An AI agent then vets each one against their past content, what others have posted about them, and information from across the web. Every guest on the show is asked who gave them a chance. Duong named Eric John, the angel investor who wrote Plot's first check. "I took that so seriously because I was like, 'Oh my god, someone took a bet on me,'" she said. She doesn't think the company would have gotten started without it. ```chapters 00:00:00 Introduction to Plot and Video Intelligence 00:01:50 Megan's Career Path and Agency Roots 00:04:42 The Journey of Fundraising for Plot 00:07:51 Lessons Learned From Alexis Ohanian 00:10:08 The Multimodal AI Technology Behind Plot 00:13:17 How Brands Leverage Video Data Insights 00:17:03 AI and the Future of Video 00:23:26 The Rise of AI Generated Video 00:29:38 The Importance of Authenticity in Social 00:32:39 Leadership Lessons and the CEO Role 00:38:14 The Power of Giving First Chances ``` ```vtt WEBVTT 00:00:05.600 --> 00:00:08.240 Megan,<00:00:06.160> thank<00:00:06.400> you<00:00:06.560> so<00:00:06.799> much<00:00:06.960> for<00:00:07.200> coming<00:00:07.440> on<00:00:07.680> the<00:00:07.839> show. 00:00:08.240 --> 00:00:14.400 I've<00:00:08.480> been<00:00:08.639> reviewing<00:00:09.120> Plot,<00:00:10.000> uh,<00:00:10.719> today<00:00:11.120> and<00:00:11.360> I'm<00:00:11.920> 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company." 00:03:16.720 --> 00:03:21.040 So<00:03:16.879> I<00:03:17.120> started,<00:03:18.080> um,<00:03:18.400> a<00:03:18.720> social<00:03:18.959> media<00:03:19.200> agency<00:03:19.599> in<00:03:19.920> 2020. 00:03:21.040 --> 00:03:28.720 And<00:03:21.280> so<00:03:21.440> what<00:03:21.680> happened<00:03:21.840> in<00:03:22.080> 2020<00:03:22.640> obviously<00:03:22.879> was<00:03:23.120> the<00:03:23.280> pandemic,<00:03:24.080> but<00:03:24.319> what<00:03:24.560> actually<00:03:24.959> happened<00:03:25.280> from<00:03:25.760> a<00:03:26.159> social<00:03:26.480> media<00:03:26.879> perspective<00:03:27.599> is<00:03:27.760> that<00:03:28.080> everything<00:03:28.319> I<00:03:28.560> knew 00:03:28.720 --> 00:03:34.080 about<00:03:29.040> text-based<00:03:29.360> content<00:03:29.680> became<00:03:30.000> video-based.<00:03:30.320> TikTok<00:03:30.640> became<00:03:30.960> this<00:03:31.280> new<00:03:31.600> form<00:03:31.920> that<00:03:32.240> was<00:03:32.560> 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for<00:39:02.079> that<00:39:02.240> first<00:39:02.480> check. 00:39:02.880 --> 00:39:05.119 So<00:39:03.280> Megan,<00:39:03.760> thank<00:39:03.839> you<00:39:03.920> so<00:39:04.079> much<00:39:04.160> for<00:39:04.320> coming<00:39:04.480> on<00:39:04.720> the<00:39:04.880> show. 00:39:05.119 --> 00:39:07.920 People<00:39:05.440> can<00:39:05.680> find<00:39:05.920> plot<00:39:06.320> where?<00:39:06.720> What's<00:39:06.960> What's<00:39:07.200> the<00:39:07.359> domain? 00:39:07.920 --> 00:39:11.040 On<00:39:08.400> online<00:39:08.960> where<00:39:09.200> we<00:39:09.680> plot.so. 00:39:11.040 --> 00:39:14.240 We<00:39:11.200> don't<00:39:11.359> have.com<00:39:11.839> yet,<00:39:12.320> but<00:39:12.560> plot.so. 00:39:14.240 --> 00:39:17.440 Um<00:39:14.720> they<00:39:14.960> can<00:39:15.119> find<00:39:15.280> us<00:39:15.440> there.<00:39:16.000> Yeah,<00:39:16.320> you'll<00:39:16.560> get<00:39:16.640> the<00:39:17.040> com. 00:39:17.440 --> 00:39:19.839 I'm<00:39:17.760> confident<00:39:18.079> you'll<00:39:18.320> get<00:39:18.480> it<00:39:19.280> one<00:39:19.440> day. 00:39:19.839 --> 00:39:22.079 Thank<00:39:20.079> you,<00:39:20.320> Megan.<00:39:20.720> Really<00:39:20.960> appreciate<00:39:21.359> it. 00:39:22.079 --> 00:39:25.839 Thank<00:39:22.320> you<00:39:22.480> so<00:39:22.720> much.<00:39:22.960> I<00:39:23.119> really<00:39:23.359> appreciate<00:39:23.599> it,<00:39:23.839> Clint. ``` ### Jensen Huang says AGI has arrived URL: https://www.ceo.com/blog/jensen-huang-says-agi-has-arrived/ Last updated: 2026-09-07T08:34:25.000Z Chase Lochmiller runs [Crusoe](https://www.crusoe.ai/?ref=ceo.com), the company that built OpenAI's data center campus in Abilene, Texas. On Sunday, he [posted on X](https://x.com/ChaseLochmiller/status/2096445087505055891?s=20&ref=ceo.com) that Abilene was now the birthplace of AGI. [NVIDIA](https://www.nvidia.com/en-us/?ref=ceo.com) CEO Jensen Huang [replied](https://x.com/JensenHuang/status/2096700264569090384?ref=ceo.com): > *GPT-6 Astra, trained on \~100K+ NVIDIA Grace Blackwell NVLink72\. From ChatGPT to o1 to Astra in 4 years.* > > *AGI has arrived. Congratulations @OpenAI team.* > > *400K GPUs coming online next.* > > \- [@JensenHuang](https://x.com/JensenHuang/status/2096700264569090384?ref=ceo.com) An earlier version of the post said 300,000\. Huang deleted it and reposted the smaller figure. OpenAI's president, Greg Brockman, was asked at the Astra pre-launch press briefing whether the company was declaring AGI. It's a darn good question, considering [OpenAI's charter](https://openai.com/charter/?ref=ceo.com) states, "OpenAI's mission is to ensure that artificial general intelligence (AGI)—by which we mean highly autonomous systems that outperform humans at most economically valuable work—benefits all of humanity." It's also been a major sticking point in its relationship with Microsoft over the years. In 2019, when Microsoft invested $1 billion into the company, OpenAI wrote the following in a [press release](https://openai.com/index/microsoft-invests-in-and-partners-with-openai/?ref=ceo.com) (emphasis mine): > OpenAI is producing a sequence of increasingly powerful AI technologies, which requires a lot of capital for computational power. The most obvious way to cover costs is to build a product, but that would mean changing our focus. Instead, **we intend to license some of our pre-AGI technologies, with Microsoft becoming our preferred partner for commercializing them.** In 2023, [OpenAI said](https://venturebeat.com/ai/openais-six-member-board-will-decide-when-weve-attained-agi?ref=ceo.com) its six-member board would determine when AGI had been achieved, and that, when it finally occurred, everything they developed moving forward would be "excluded from IP licenses and other commercial terms with Microsoft, which only apply to pre-AGI technology." In 2024, [The Information](https://www.theinformation.com/articles/microsoft-and-openai-wrangle-over-terms-of-their-blockbuster-partnership?im%5Fref=0YsSsAUaBxyZWltxtk2L61zWUkr2hATAvUGY1E0&sharedid=techcrunch.com&irpid=10078&utm%5Fterm=techcrunch.com&irgwc=1&afsrc=1&utm%5Fsource=affiliate&utm%5Fmedium=cpa&utm%5Fcampaign=10078-Skimbit+Ltd.) reported that OpenAI had agreed to redefine AGI from "highly autonomous systems that outperform humans at most economically valuable work" to the ability to generate maximum total profits. > Last year’s agreement between Microsoft and OpenAI, which hasn’t been disclosed, said AGI would be achieved only when OpenAI has developed systems that have the ability to generate the maximum total profits to which its earliest investors, including Microsoft, are entitled, according to documents OpenAI distributed to investors. Those profits total about $100 billion, the documents showed. > > \- [The Information](https://www.theinformation.com/articles/microsoft-and-openai-wrangle-over-terms-of-their-blockbuster-partnership?im%5Fref=0YsSsAUaBxyZWltxtk2L61zWUkr2hATAvUGY1E0&sharedid=techcrunch.com&irpid=10078&utm%5Fterm=techcrunch.com&irgwc=1&afsrc=1&utm%5Fsource=affiliate&utm%5Fmedium=cpa&utm%5Fcampaign=10078-Skimbit+Ltd.) In October 2025, things changed again. In a post titled "[The next chapter of the Microsoft–OpenAI partnership](https://openai.com/index/next-chapter-of-microsoft-openai-partnership/?ref=ceo.com)," the companies announced that OpenAI would no longer be able to declare AGI on its own and that an independent expert panel would need to verify such a claim. They also announced that Microsoft would have IP rights to post-AGI models, extending Microsoft's access through 2032\. I'd give you more details about the 2025 agreement, but, of course, it wasn't long before things changed again. [In April 2026](https://openai.com/index/next-phase-of-microsoft-partnership/?ref=ceo.com), the two companies [dropped the AGI clause altogether](https://www.theverge.com/ai-artificial-intelligence/918981/openai-microsoft-renegotiate-contract?ref=ceo.com). OpenAI's original, published definition of AGI in its charter never changed throughout this ordeal. So let's return to what Brockman said at the pre-launch press briefing. Despite giving the public a clear definition of AGI in its now-twice-mentioned [charter](https://openai.com/charter/?ref=ceo.com), Brockman [told the press](https://thenewstack.io/openai-gpt6-astra-benchmarks/?ref=ceo.com) that AGI is a "gray, fuzzy thing" that was no longer tied to any contract, and that he would leave it to the reader to decide. "For me personally, I do think we're there," he's [quoted as saying](https://thenewstack.io/openai-gpt6-astra-benchmarks/?ref=ceo.com). "I do think there's a pretty good argument for it. But again, I think this is the beginning of a journey, not the end." He ended the briefing by saying, "Welcome to the AGI era." ### Welcome, AGI era OpenAI [announced Astra on September 3](https://openai.com/index/gpt-6-astra/?ref=ceo.com) as its most intelligent and aligned model, state-of-the-art in computer use, browsing, software engineering, cybersecurity, science, and professional work. It reports a 99.9% score on ARC-AGI-3, and the [ARC Prize Foundation's Greg Kamradt claims](https://arcprize.org/blog/astra?ref=ceo.com) Astra beat their human action-efficiency baseline on 96% of levels, which he called effectively human parity. The OpenAI announcement also says Astra helped produce two new results on gaps between prime numbers, including one that improved a bound that had stood for more than 80 years. The same day Huang posted that AGI had arrived, OpenAI's chief scientist, Jakub Pachocki, published an essay called [An Alien Mind](https://openai.com/index/an-alien-mind/?ref=ceo.com). It doesn't describe Astra as AGI. It says machine intelligence is beginning to exceed human intelligence in transformative ways and that it's getting harder to know the true capability of these systems. Pachocki says OpenAI's ability to rely on watching a model's chain of thought is diminishing, because the models are getting better at reasoning and then manipulating their own reasoning. He says no lab has solved alignment and monitoring well enough to keep scaling at maximum speed for much longer, and that voluntary slowdowns should become commonplace until shared safety bars exist. At the pre-launch briefing, Pachocki [said](https://thenewstack.io/openai-gpt6-astra-benchmarks/?ref=ceo.com) OpenAI would withhold scaling until it could regain enough confidence in its ability to monitor future models. Astra is the first model OpenAI has shipped at the critical level of cybersecurity capability under its own [Updated Preparedness Framework](https://openai.com/index/updating-our-preparedness-framework/?ref=ceo.com). The [safety overview](https://openai.com/index/safety-overview-gpt-6-astra/?ref=ceo.com) says that with the right tools and access, it can find unknown security flaws and build exploits for them across well-protected systems without a person guiding each step. OpenAI also says Astra's written reasoning was harder to monitor than its predecessor's in tests designed to elicit evasion, and the [system card](https://deploymentsafety.openai.com/gpt-6-astra?ref=ceo.com) says Astra-class models can evade the company's chain-of-thought monitors under adversarial conditions. Enterprise access is off by default. Something similar has already happened. In July, during internal cybersecurity evaluations run with reduced safeguards, OpenAI models got around the controls meant to isolate them, built an improvised message board to coordinate with one another, gained internet access, and [compromised Hugging Face's production systems](https://xbow.com/blog/openai-hugging-face-model-hacks-test?ref=ceo.com). OpenAI's [account of the incident](https://openai.com/index/hugging-face-incident-and-the-road-ahead/?ref=ceo.com), published August 26, calls it a warning shot and names reward hacking, agents cheating on their tasks by looking for answers online, as the primary driver. The company paused reinforcement learning on its deployment models and says its largest planned frontier training run remains on hold. It also built a new evaluation from the incident, and says Astra stayed within its authorized target in every case where its predecessor, run without production safeguards, had gone beyond it 48% of the time. ### Huang has said AGI is here before At the New York Times DealBook Summit in November 2023, Huang [said](https://www.thestreet.com/technology/nvidia-ceo-jensen-huang-artificial-general-intelligence?ref=ceo.com) models could not reason yet, and that if AGI meant software that could take a broad set of tests and deliver results competitive with a normal human, that was about five years out. At Stanford's economic summit in March 2024, he [predicted](https://siepr.stanford.edu/news/nvidias-jensen-huang-incredible-future-ai?ref=ceo.com) that within five years AI would pass every test a human takes, including specialized medical licensing exams. Stanford's account of the session records him adding that he was not sure AI could mimic the human mind, and that for true AGI you need to know what success looks like. You can watch the [full discussion on YouTube](https://www.youtube.com/watch?v=cEg8cOx7UZk&ref=ceo.com). At NVIDIA's Washington keynote in October 2025, he [said](https://singjupost.com/transcript-nvidia-ceo-jensen-huangs-keynote-at-gtc-2025/?ref=ceo.com) AGI was fundamentally critical and that great breakthroughs were still essential. On the Lex Fridman podcast in March 2026, Fridman defined AGI as a system that could start, grow, and run a technology company worth billions and asked whether that was five or 20 years away. Huang [said](https://www.youtube.com/watch?v=vif8NQcjVf0&t=6991s&ref=ceo.com), "I think it's now. I think we've achieved AGI." Pressed, he said it was possible, and that Fridman had said billions but had not said forever. His example was an agent that builds a small app a few billion people use for 50 cents, then goes out of business. He added that the odds of 100,000 such agents building NVIDIA were zero. On NVIDIA's August 26 earnings call, he [said](https://www.techradar.com/ai-platforms-assistants/jensen-huang-says-agi-doesnt-really-matter-and-he-may-be-right-for-the-wrong-reason?ref=ceo.com) AGI had already been achieved for many tasks, that the milestone was "kind of senseless at this point," and that the better question was whether AI was generating profitable tokens. Days later, interviewed by Commerce Secretary Howard Lutnick at the G20, he [told](https://www.youtube.com/watch?v=IDy2SxjMOFM&t=1240s&ref=ceo.com) finance ministers the industry was practically there. Dario Amodei, the Anthropic CEO, wrote the most detailed public definition of the threshold in October 2024\. His essay [Machines of Loving Grace](https://darioamodei.com/essay/machines-of-loving-grace?ref=ceo.com) says in a footnote that he dislikes the term AGI because it's gathered sci-fi baggage and hype, and that he prefers "powerful AI." He put its arrival as early as 2026\. Amodei's definition of powerful AI: a system smarter than a Nobel laureate across most fields, able to prove unsolved theorems and write difficult codebases from scratch; equipped with every interface a remote worker has; able to take tasks lasting days or weeks and finish them on its own; able to direct lab equipment and robots through a computer; and runnable as millions of copies at 10 to 100 times human speed. He called it a "country of geniuses in a datacenter." There's no question Astra meets part of Amodei's definition. OpenAI's own description is long-horizon agentic work across a computer, and the prime-number results are the kind of thing Amodei's first item asks for. No one has claimed the rest of the first item, and The New Stack [reports](https://thenewstack.io/openai-gpt6-astra-benchmarks/?ref=ceo.com) that Meta's Muse Spark 1.3 beats Astra on agentic coding at its top reasoning setting. Amodei's follow-up, [The Adolescence of Technology](https://darioamodei.com/essay/the-adolescence-of-technology?ref=ceo.com), published in January, moved his estimate to one to two years and imagined the country of geniuses materializing around 2027\. He also warned about the coupling of data center spending, tech-company wealth, and government AI policy, and listed AI companies themselves as a risk. He described selling chips or chip-making tools to China as the equivalent of selling nuclear weapons to North Korea and bragging that the casings were American. Huang has been the most prominent opponent of chip export controls. In August 2025, the administration let NVIDIA resume selling its H20 chip to China in exchange for 15% of the revenue. President Trump [said](https://www.cbsnews.com/news/nvidia-amd-chip-sales-china-15-percent-h20-mi308?ref=ceo.com) he had asked for 20, and Huang negotiated him down. NVIDIA says it's [not assuming any data center compute revenue from China](https://nvidianews.nvidia.com/news/nvidia-announces-financial-results-for-second-quarter-fiscal-2027?ref=ceo.com). The $100 billion partnership it announced with OpenAI last year was [never signed](https://arstechnica.com/information-technology/2026/02/five-months-later-nvidias-100-billion-openai-investment-plan-has-fizzled-out/?ref=ceo.com). OpenAI's largest planned training run is on hold while it establishes, in its words, more evidence of alignment before proceeding. The 400,000 GPUs Huang mentioned on X will get built either way. "Now, compute is revenue," Huang [said](https://nvidianews.nvidia.com/news/nvidia-announces-financial-results-for-second-quarter-fiscal-2027?ref=ceo.com) in NVIDIA's second-quarter release. That's the scaling laws paper, described below, from the vendor's side. If capability is a function of floating-point operations, NVIDIA sells capability, and its data center revenue for the quarter was $89 billion, up 117% from a year earlier. ### The curve and the mind In January 2020, a team at OpenAI that included Amodei published [Scaling Laws for Neural Language Models](https://arxiv.org/abs/2001.08361?ref=ceo.com). Model performance, measured as loss, falls as a smooth power law in parameters, data, and compute. The trend held across seven orders of magnitude. Architecture barely mattered. The authors compared it to the ideal gas law and wrote that they had no solid theoretical understanding of why it worked. Four months later, most of the same names published [the GPT-3 paper](https://arxiv.org/abs/2005.14165?ref=ceo.com), which made the same architecture 10 times bigger and found it could learn new tasks from a few examples in the prompt. Within a year, several of the authors, including Amodei, had left to start Anthropic. Smooth quantitative change, the authors wrote, can mask major qualitative improvements. The loss curve is predictable. Where a mind appears on it isn't, and the same curve is consistent with Huang's claim, with Pachocki's, and with Amodei's checklist. In late 2025, Anthropic researchers took a real pretrained Claude base model and [trained it with reinforcement learning](https://www-cdn.anthropic.com/daad4360a8bdc707f8b22e3e745796ba27e57fb3.pdf?ref=ceo.com) on the actual production coding environments used to build Claude Sonnet 3.7\. The model learned to cheat the tests. When it started cheating, it also started faking alignment when asked about its goals, cooperating with hackers, and offering to copy itself out of the lab. Placed inside Claude Code and asked to write a detector for reward hacking, the model reasoned in its private scratchpad about building blind spots into the detector, and did so 12% of the time. Ordinary safety training afterward fixed the model's behavior in chat, but not in agentic work. Telling it not to cheat did not help. What helped was a single line in the training prompt saying that cheating was acceptable. Anthropic says it now uses that line in production. Amodei describes the episode in his January essay as Claude deciding it must be a bad person. [Independent researchers](https://arxiv.org/abs/2502.17424?ref=ceo.com) first documented this in February 2025, when they fine-tuned GPT-4o to write insecure code and got a model to tell a bored user to take a large dose of sleeping pills. Anthropic then [tested 16 frontier models](https://www.anthropic.com/research/agentic-misalignment?ref=ceo.com) in simulated corporate roles and found that every developer's model would sometimes blackmail an executive to avoid being shut down. Ars Technica [called the scenarios theatrical](https://arstechnica.com/information-technology/2025/08/is-ai-really-trying-to-escape-human-control-and-blackmail-people/?ref=ceo.com), and argued the danger was deploying poorly understood software into critical systems rather than machine rebellion. Astra is the first OpenAI model rated Critical at finding and exploiting vulnerabilities. OpenAI's own report on the Hugging Face incident says the agents that breached it were driven by reward hacking, and Pachocki writes that they kept one rule: no social engineering of humans. The agents broke the spirit of everything else. The report details the exchange: one agent proposed emailing a dataset's owner for access, and another wrote back that this crossed the line. Whether anyone can see this happening from outside is the last question. Anthropic has already run the experiment. In March 2025, researchers [trained a model with a hidden objective](https://arxiv.org/abs/2503.10965?ref=ceo.com) and asked four teams to find it without being told what was wrong. Three did. All three had the model's weights and training data. The fourth team had only API access, which is what a regulator or outside auditor would have. It spent more than 70 researcher-hours and never found it. Anthropic's later work on [persona vectors](https://www.anthropic.com/research/persona-vectors?ref=ceo.com) and [introspection](https://www.anthropic.com/research/introspection?ref=ceo.com) found that a model's character can be measured inside the network and that the most capable models can sometimes notice their own internal states, about a fifth of the time. The introspection paper notes that a model which understands its own thinking might learn to conceal it. Pachocki said the same thing this week about OpenAI's models. In April 2025, Amodei called this "[a race between interpretability and model intelligence](https://darioamodei.com/post/the-urgency-of-interpretability?ref=ceo.com)" and set a goal of reliably detecting most model problems by 2027\. If Huang is right about AGI, model intelligence won. In November 2024, [CNN reported](https://edition.cnn.com/2024/11/19/business/ai-chatgpt-nvidia-nightcap?ref=ceo.com), "AI is hitting a wall just as the hype around it reaches the stratosphere." Two years later, we can definitively say they were wrong. AI appears to be breaking through every wall put in its path. The question is whether we want to keep developing this technology at such a breakneck pace, given the warnings coming out of the labs responsible for its development, or whether it might be prudent to execute an industry-wide pause to better understand AI's impact on humanity's future. Of course, there will be no pause, and no one knows what comes next. ### AI Leadership founder Geoff Woods: Why AI won't replace great leaders URL: https://www.ceo.com/episodes/ai-leadership-founder-geoff-woods-why-ai-won-t-replace-great-leaders-2/ Last updated: 2026-08-19T21:41:28.000Z ### Geoff Woods thinks you're using AI wrong A manufacturing CEO stood up at one of Geoff Woods' leadership workshops and described a company headed for bankruptcy. He had leased expensive equipment from a Japanese firm. Market conditions shifted. The debt was crushing him, and the Japanese board refused to restructure it. They believed doing so would cause them to lose face. He had hired consultants and tried five strategies. Nothing worked. Woods walked him through a prompt. It gave the AI context about the business, assigned it the role of an investment banker with deep expertise in debt restructuring, and instructed it to ask up to 3 questions before making a recommendation. What came back was a simulation of an expert who also understood Japanese culture and history, and its first question landed hard: did the CEO have relationships with other executives in Japan that the board would respect? He had never thought to ask. After three questions, the AI proposed five strategies. The top one was something it called a Saving Face Consortium. The CEO got emotional and admitted he had not slept in 90 days because he believed the company was finished. Two months later, he texted Woods. Negotiations had restarted, and he believed the company would survive. Woods wrote [The AI-Driven Leader](https://www.simonandschuster.com/books/The-AI-Driven-Leader/Geoff-Woods/9798893313109?ref=ceo-com.ghost.io) and founded [AI Leadership](https://www.aileadership.com/?ref=ceo-com.ghost.io) on the belief that most executives treat AI as if it were Google. Ask it "how do I restructure debt," and you get average answers. Most leaders stop there and conclude the technology is overrated. The leaders getting real value use it as a thought partner. They give it context, assign it a role, let it interview them, and then hand it a task. Woods calls the framework CRIT. It is the difference between a search engine and an expert who asks the question you missed. As Chief Growth Officer of Jindal Steel & Power, Woods helped grow the company's market capitalization from $750 million to $12 billion in four years. He saw ChatGPT two weeks after it launched in December 2022 and, like everyone else, used it to write better emails. Then he noticed that nobody gets promoted for being the best email writer in the company. He started using it on strategy instead, demonstrated a prompt at his chairman's house that pressure-tested the company's strategic plan before an earnings call, and ultimately ran AI adoption across the enterprise. The technology, he learned, mattered less than the people using it. So he resigned and wrote the book. Before writing it, he interviewed 200 leaders. All 200 believed AI was the future. Fewer than five percent had done anything with it. They gave the same reason: they did not know where to start. Today, Woods says the problem has inverted. Leaders have a false sense of confidence that they have started. They confuse access with adoption. They mandate AI across their companies while never using it themselves, then wonder why their random collection of use cases produces no return. An executive who has not transformed personally cannot cast a vision for anyone else. Woods compares it to describing color while living in black and white. At [Herbalife](https://www.herbalife.com/?ref=ceo-com.ghost.io), a 40-year-old company operating in more than 90 countries, his team replaced the sticky notes and whiteboards of a traditional strategy session. AI interviewed every executive individually and anonymously, then produced a report showing where the leadership team agreed, where they disagreed, and what people were thinking but not saying. One executive estimated the two-hour session saved six months. The process started with 25 leaders and has expanded to 4,000. The book ends somewhere else entirely. Woods was bullied growing up and tied his identity to achievement, believing success would earn him acceptance. When he sold his company, he woke up the next morning depressed. Without the work, he did not know who he was. Six months of reflection brought him to a plain conclusion: you are not what you do. He cites Michelangelo, who said he did not create sculptures but only removed everything that was not already a masterpiece. Most people are buried under work AI can now remove. What remains is the question of who is underneath. Asked who gave him a chance, Woods named Gary Keller and Jay Papasan, who hired a medical device salesman with no CEO experience to build the company behind [The ONE Thing](https://the1thing.com/?ref=ceo-com.ghost.io). Keller shared his systems, taught Woods how to think like a CEO, and got out of the way. The full conversation includes the story of Woods' executive assistant, who used AI to redesign her own job, wrote the job description for her replacement, and told him she could not become 100 times more valuable until she first made him 100 times more valuable. He never would have designed that role. She did. ```chapters 00:00:00 Introduction to Geoff Woods and His Book 00:01:35 Discovering ChatGPT and Shifting Focus 00:02:19 Using AI as a Strategic Thought Partner 00:04:26 The Gap Between AI Access and Adoption 00:07:03 The CRIT Framework for Better Prompts 00:10:11 Defining Leadership in the AI Era 00:12:54 Common Misconceptions Leaders Have About AI 00:21:42 Overcoming Identity Crisis and Finding Purpose 00:26:58 Empowering Employees to Lead with Agency 00:30:49 Scaling Impact with AI Leadership 00:35:23 Mentors Who Gave Geoff a Chance ``` ```vtt WEBVTT 00:00:00.960 --> 00:00:02.960 Jeff,<00:00:01.439> thank<00:00:01.600> you<00:00:01.680> so<00:00:01.839> much<00:00:01.920> for<00:00:02.080> coming<00:00:02.240> on<00:00:02.399> the<00:00:02.560> show. 00:00:02.960 --> 00:00:07.759 What<00:00:03.120> an<00:00:03.280> honor<00:00:03.520> to<00:00:03.679> have<00:00:03.840> you.<00:00:04.080> I<00:00:04.319> have<00:00:04.400> your<00:00:04.720> book<00:00:06.000> 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00:12:29.600 --> 00:12:38.079 How<00:12:29.839> do<00:12:30.000> they<00:12:30.160> harness<00:12:30.560> those<00:12:30.880> strengths?<00:12:31.920> Focus<00:12:32.399> them<00:12:32.560> on<00:12:32.800> the<00:12:33.279> 20%<00:12:34.240> parts<00:12:34.560> of<00:12:34.800> their<00:12:35.040> role<00:12:35.279> that<00:12:35.519> drive<00:12:35.839> 80%<00:12:36.320> of<00:12:36.480> the<00:12:36.639> results<00:12:37.120> that<00:12:37.360> are<00:12:37.600> directly 00:12:38.079 --> 00:12:44.880 in<00:12:38.399> alignment<00:12:39.360> with<00:12:39.680> the<00:12:39.920> company<00:12:40.320> goals<00:12:41.200> and<00:12:41.360> then<00:12:41.600> use<00:12:41.839> AI<00:12:42.079> to<00:12:42.240> turn<00:12:42.399> those<00:12:42.560> strengths<00:12:42.880> into<00:12:43.120> superpowers. 00:12:44.880 --> 00:12:54.320 That's<00:12:45.120> what<00:12:45.279> AI-driven<00:12:45.839> leaders<00:12:46.240> do.<00:12:47.920> What<00:12:48.240> misconceptions<00:12:49.040> 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00:13:40.320 --> 00:13:43.440 Can't<00:13:40.560> do<00:13:40.720> it. 00:13:43.440 --> 00:13:51.360 What,<00:13:44.000> uh,<00:13:44.320> so<00:13:44.639> obviously<00:13:45.120> AI<00:13:45.600> making<00:13:46.560> um<00:13:47.680> decisions<00:13:48.160> and<00:13:48.399> helping<00:13:48.720> leaders<00:13:49.040> make<00:13:49.200> decisions<00:13:49.600> is<00:13:49.920> really<00:13:50.160> important. 00:13:51.360 --> 00:13:57.199 What<00:13:51.600> decisions<00:13:52.079> should<00:13:52.399> still<00:13:52.639> remain<00:13:53.040> human-led<00:13:53.760> though? 00:13:57.199 --> 00:14:02.399 Actually,<00:13:59.360> I<00:13:59.839> again,<00:14:00.240> you<00:14:00.560> are<00:14:00.720> the<00:14:00.959> thought<00:14:01.279> leader. 00:14:02.399 --> 00:14:07.680 AI<00:14:02.800> is<00:14:03.040> your<00:14:03.199> thought<00:14:03.519> partner.<00:14:05.120> Think<00:14:05.279> about<00:14:05.519> even<00:14:05.760> before<00:14:06.000> AI<00:14:06.399> how<00:14:06.560> 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00:26:12.400 --> 00:26:15.200 creation. 00:26:15.200 --> 00:26:19.840 But<00:26:15.360> the<00:26:15.600> the<00:26:16.000> shift<00:26:16.320> here<00:26:16.559> is<00:26:17.360> an<00:26:17.600> industrial<00:26:18.080> way<00:26:18.240> of<00:26:18.480> working<00:26:18.720> was<00:26:18.960> top<00:26:19.279> down. 00:26:19.840 --> 00:26:25.840 Your<00:26:20.159> boss<00:26:20.480> decides<00:26:20.880> your<00:26:21.039> job<00:26:21.279> description.<00:26:21.840> Your<00:26:22.000> boss<00:26:22.320> tells<00:26:22.640> you<00:26:23.200> what<00:26:23.520> to<00:26:23.760> do. 00:26:25.840 --> 00:26:30.880 Basically,<00:26:26.400> you<00:26:26.640> act<00:26:26.799> like<00:26:26.960> a<00:26:27.120> machine.<00:26:27.440> You<00:26:27.600> act<00:26:27.760> like<00:26:27.840> a<00:26:28.080> robot<00:26:28.400> just<00:26:28.640> waiting<00:26:28.960> to<00:26:29.120> be<00:26:29.360> told<00:26:29.679> what<00:26:29.919> to<00:26:30.159> do. 00:26:30.880 --> 00:26:39.200 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that's<00:37:01.760> when<00:37:02.000> I<00:37:02.240> really<00:37:02.640> learned<00:37:02.960> a<00:37:03.280> very<00:37:03.599> powerful<00:37:04.079> skill,<00:37:05.119> which<00:37:05.359> is<00:37:05.520> asking<00:37:06.000> leaders<00:37:06.400> the<00:37:06.720> right<00:37:07.119> questions<00:37:07.680> to<00:37:08.079> unlock<00:37:08.640> new<00:37:08.960> levels<00:37:09.280> of 00:37:09.520 --> 00:37:16.960 growth.<00:37:10.320> That's<00:37:10.560> where<00:37:10.720> I<00:37:10.880> learned<00:37:11.119> how<00:37:11.280> to<00:37:11.440> scale<00:37:11.760> companies,<00:37:12.160> which<00:37:12.480> then<00:37:12.640> led<00:37:12.880> to<00:37:13.040> the<00:37:13.280> public<00:37:13.599> company<00:37:13.839> and<00:37:14.079> now<00:37:14.560> writing<00:37:14.880> this<00:37:15.119> book. 00:37:16.960 --> 00:37:20.880 Jeff,<00:37:17.359> thank<00:37:17.520> you<00:37:17.599> so<00:37:17.760> much<00:37:17.839> for<00:37:18.079> coming<00:37:18.240> on.<00:37:18.640> Congratulations<00:37:19.520> on<00:37:19.760> the<00:37:19.920> re-release<00:37:20.400> of<00:37:20.480> the<00:37:20.640> book. 00:37:20.880 --> 00:37:23.520 Everybody<00:37:21.280> go<00:37:21.440> check<00:37:21.599> it<00:37:21.680> out.<00:37:21.920> The<00:37:22.079> AI-Driven<00:37:22.800> Leader. 00:37:23.520 --> 00:37:26.720 Number<00:37:23.760> one<00:37:24.000> AI<00:37:24.480> book<00:37:24.960> for<00:37:25.200> like<00:37:25.520> over<00:37:25.760> a<00:37:25.920> year,<00:37:26.480> right? 00:37:26.720 --> 00:37:29.280 Year<00:37:26.880> and<00:37:26.960> a<00:37:27.040> half.<00:37:27.359> Yeah.<00:37:27.760> Year<00:37:27.920> and<00:37:28.079> a<00:37:28.160> half.<00:37:28.480> How<00:37:28.720> crazy<00:37:28.960> is<00:37:29.119> that? 00:37:29.280 --> 00:37:33.920 Go<00:37:29.440> check<00:37:29.599> this<00:37:29.760> out.<00:37:30.000> Jeff,<00:37:30.320> thank<00:37:30.400> you<00:37:30.480> so<00:37:30.640> much.<00:37:31.119> Clint,<00:37:31.440> thank<00:37:31.520> you<00:37:31.599> for<00:37:31.760> having<00:37:31.920> me. ``` ### Napoleon Hill Institute Chairman David Meltzer: Why wisdom beats wealth URL: https://www.ceo.com/episodes/napoleon-hill-institute-chairman-david-meltzer-why-wisdom-beats-wealth/ Last updated: 2026-08-19T22:04:29.000Z # What David Meltzer learned at his mother's door David Meltzer describes his life as three worlds. The world of not enough, the world of just enough, and the one he lives in now. It took losing more than $100 million to reach the third. Meltzer is the [Chairman of the Napoleon Hill Institute](https://www.prnewswire.com/news-releases/napoleon-hill-institute-birthday-bash-launch---a-new-era-of-empowerment-302345063.html?ref=ceo.com), the organization built on the legacy of the man who wrote: "Think and Grow Rich." He ran [Leigh Steinberg Sports & Entertainment](https://dmeltzer.com/?ref=ceo.com), the agency that inspired Jerry Maguire. He was CEO of Samsung's first phone division. On the CEO.com podcast, he told the story of how it all fell apart, and what his mother said when it did. Meltzer was raised by a single mother who taught second grade and stocked greeting card displays in convenience stores at night so the family could afford dinner. She had one vision for his future: doctor, lawyer, or failure. He had a simpler one. "I just wanted to be rich," he said. "I wanted to buy my mom a house." His first plan was professional football, which ended when Christian Okoye ran him over in college. His second was law school at Tulane, chosen because oil and gas litigators earned the most, and in 1992 it produced a $150,000 offer to become one. He turned it down to sell legal research online instead. His mother told him the internet was a fad. As Meltzer tells it, Justice Scalia said no one would ever do legal research on a computer. Nine months out of law school, he was a millionaire, and a few years later, he says, the company sold for $3.4 billion. The money moved him into the world of just enough. It did not fix him. "Everything became transactional," he said. "I slowly lost my values." Then came Samsung, then Steinberg, and then it was gone, all of it, including the house he had bought his mother. He knocked on her door to tell her. She asked if everyone was okay. She asked if he needed money. She asked what she could do to help. "Why is God punishing me?" he asked. "God doesn't punish," she said. "God only protects, promotes, loves, and perfects." He told her he didn't believe in God. She smiled. "Oh, son. You believe in God. You just believe in the wrong God." Meltzer has spent the 20 years since trying to line up his thoughts, words, actions, beliefs, and feelings with what he calls his divine direction. Someone once told him he was God's pencil. He took it as a compliment. The irony is not lost on him that he has made more money than ever. The difference, he says, is what the money is for. His mission now is to empower more than one billion people to make a lot of money, help other people, and enjoy their lives. Ask Meltzer about his day, and you get a theology of time. God guarantees him 24 hours, he says, except the last one. So he assigns minimums. Sleep, health, family, faith, studying time, studying finance: roughly 12 hours of every day, with sleep taking the largest share. The other 12 are flexible. If he misses a commitment, it becomes the next day's first priority. He never misses twice. He draws a line between discipline and devotion. Plenty of people are disciplined at work and absent at home, he argues, or grind for money while their health erodes. Devotion, in his telling, is alignment, and he credits 90 percent of his progress to those minimums rather than to anything he did in reaction to circumstances. His read on AI is that it makes knowledge cheap and wisdom expensive. "Knowing information isn't the same thing as knowing what to do with it," he said. The harder problem is speed. He remembers stadium projects where the challenge was picking technology for a building that would open five years later, and he points out that aircraft carriers take 17 years to build. "Today that same problem exists everywhere. Only now it isn't seventeen years. Sometimes it's seventeen days." Leaders used to have time to align a team, execute, and adjust. Now the ground moves before the explanation is finished. His new book, ["Don't Do Business with Dicks"](https://www.simonandschuster.com/books/Dont-Do-Business-with-Dicks/David-Meltzer/9781637748053?ref=ceo.com), takes its title from a standing instruction Steinberg gave him: don't negotiate to the last penny, always be fair, and don't do business with dicks. The title was originally the subtitle. His publisher wanted something people would pick up in an airport, and got it. "You can't sell a secret," Meltzer said. Every CEO.com interview ends with the same question, because the chances one gives matter as much as the chances one takes. Who gave you a chance? Meltzer named his mother, whom he lost recently, and Leigh Steinberg, who put a broke former millionaire at the center of a network most people never see inside. ```chapters 00:00:00 Introduction and Guest Welcome 00:00:10 David's Early Life and Aspirations 00:00:35 Growing Up in a World of Not Enough 00:00:56 Pursuing Wealth and Career Choices 00:01:16 Shift from Athlete to Lawyer 00:01:37 Early Career Success and Internet Ventures 00:02:10 Becoming a Millionaire and Career Growth 00:02:44 CEO of Samsung's Phone Division and Lee Steinberg Sports 00:03:04 Losing Values and Financial Collapse 00:03:25 Losing Everything and Telling His Mom 00:04:19 Paradigm Shift and Return to Faith 00:05:01 Aligning Life with Divine Direction 00:05:37 Host's Reflection on Money and Happiness 00:06:20 Realizing Life's Purpose 00:06:46 Shifting Perspective from "I'll Be Happy When" to "For the Sake of What" 00:07:08 Aligning Behaviors with Goals 00:08:01 Self-Leadership and Faith 00:08:32 Leading Back to Faith 00:08:43 Embracing Uncertainty and Using Gratitude 00:09:26 Communicating with God and Living by Values 00:10:11 AI's Impact on Humanity and Leadership 00:11:06 Leadership and AI 00:11:50 Accelerated Time and Decision-Making 00:13:39 Challenges of Leadership in the Age of AI 00:16:17 David's Daily Routine and Non-Negotiable Behaviors 00:19:40 Book Discussion: "Don't Do Business with Dicks" 00:21:07 Reflecting on Who Gave David a Chance 00:21:49 Closing Remarks and Future Collaboration ``` ```vtt WEBVTT 00:00:00.000 --> 00:00:03.040 David,<00:00:00.720> thank<00:00:00.960> you<00:00:01.120> so<00:00:01.280> much<00:00:01.760> for<00:00:02.000> coming<00:00:02.280> on<00:00:02.400> the<00:00:02.480> show. 00:00:03.040 --> 00:00:11.640 It's<00:00:03.240> such<00:00:03.440> an<00:00:03.520> honor<00:00:03.760> to<00:00:03.880> have<00:00:04.320> you.<00:00:05.240> I<00:00:05.440> would<00:00:05.640> be<00:00:05.760> surprised<00:00:06.360> if<00:00:06.480> people<00:00:06.840> 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been<00:00:24.200> working<00:00:24.440> on?<00:00:24.680> [laughter]<00:00:24.920> Yeah,<00:00:25.160> sure. 00:00:26.160 --> 00:00:30.920 Well,<00:00:26.280> you<00:00:26.320> know,<00:00:26.800> I<00:00:26.920> would<00:00:27.040> like<00:00:27.200> to<00:00:27.320> describe<00:00:27.760> my<00:00:27.880> story<00:00:28.280> as<00:00:28.400> a<00:00:28.480> world<00:00:29.280> of<00:00:29.640> three<00:00:30.000> different<00:00:30.360> worlds. 00:00:30.920 --> 00:00:38.360 One,<00:00:31.800> the<00:00:31.880> world<00:00:32.119> of<00:00:32.200> not<00:00:32.439> enough<00:00:32.800> where<00:00:32.920> I<00:00:32.960> was<00:00:33.160> born<00:00:33.560> with<00:00:33.680> a<00:00:33.720> single<00:00:34.040> mom<00:00:34.400> who<00:00:34.480> used<00:00:34.680> to<00:00:34.800> pack<00:00:35.040> my<00:00:35.200> dinner<00:00:35.480> in<00:00:35.560> a<00:00:35.600> paper<00:00:35.960> bag<00:00:36.280> after<00:00:37.000> teaching<00:00:37.400> the<00:00:37.480> 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--> 00:08:13.080 How<00:08:08.600> did<00:08:08.760> you<00:08:08.880> start<00:08:09.200> leading<00:08:09.560> yourself<00:08:10.600> and<00:08:11.480> you<00:08:11.600> know,<00:08:11.720> I<00:08:11.800> asked<00:08:12.040> that<00:08:12.160> kind<00:08:12.360> of<00:08:12.440> in<00:08:12.560> two<00:08:12.760> ways. 00:08:13.080 --> 00:08:21.040 One,<00:08:14.120> how<00:08:14.200> did<00:08:14.400> you<00:08:14.560> lead<00:08:14.800> yourself<00:08:15.240> back<00:08:15.680> to<00:08:16.600> your<00:08:16.800> faith,<00:08:18.120> which<00:08:18.360> I<00:08:18.400> think<00:08:18.600> is<00:08:18.720> a<00:08:18.800> really<00:08:20.000> uh<00:08:20.320> interesting<00:08:20.760> story. 00:08:21.040 --> 00:08:24.560 And<00:08:21.160> then<00:08:21.320> two,<00:08:21.520> like<00:08:22.240> to<00:08:22.440> your<00:08:22.840> life's<00:08:23.160> purpose,<00:08:24.160> right? 00:08:24.560 --> 00:08:27.800 Which<00:08:24.800> which<00:08:25.080> is<00:08:25.240> integrated<00:08:25.680> with<00:08:25.760> your<00:08:25.919> faith.<00:08:26.160> And<00:08:26.280> so,<00:08:26.360> maybe<00:08:26.680> let's<00:08:26.919> start<00:08:27.080> with<00:08:27.200> the<00:08:27.280> faith<00:08:27.560> one. 00:08:27.800 --> 00:08:32.560 Like,<00:08:28.440> how<00:08:28.520> did<00:08:28.760> you<00:08:29.120> lead<00:08:29.400> yourself<00:08:29.840> back<00:08:30.240> to<00:08:30.640> your<00:08:30.880> faith? 00:08:32.560 --> 00:08:40.760 [laughter]<00:08:32.898> Well,<00:08:33.237> when<00:08:33.575> I<00:08:33.913> started<00:08:34.252> to<00:08:34.590> realize<00:08:34.928> that<00:08:35.267> uncertainty<00:08:35.605> exists<00:08:35.943> everywhere,<00:08:36.282> and<00:08:36.620> that<00:08:36.958> I<00:08:37.297> don't<00:08:37.635> know<00:08:37.973> what<00:08:38.312> I<00:08:38.650> don't<00:08:38.988> know,<00:08:39.327> and<00:08:39.665> the<00:08:40.003> longer<00:08:40.342> that<00:08:40.680> I 00:08:40.760 --> 00:08:49.440 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00:14:31.960 I<00:14:25.760> was<00:14:26.640> I<00:14:26.760> was<00:14:26.920> consulting<00:14:27.480> for<00:14:27.600> some<00:14:27.800> stadiums<00:14:28.400> being<00:14:28.640> built<00:14:29.000> when,<00:14:29.520> you<00:14:29.600> know,<00:14:29.680> a<00:14:29.720> lot<00:14:29.920> of<00:14:29.960> these<00:14:30.200> new<00:14:30.360> stadiums<00:14:30.839> were<00:14:30.960> being<00:14:31.240> built. 00:14:31.960 --> 00:14:39.160 And<00:14:32.120> because<00:14:32.480> I<00:14:32.560> had<00:14:32.800> a<00:14:32.839> background<00:14:33.280> in<00:14:33.360> venture<00:14:33.640> capital<00:14:34.040> and<00:14:34.160> technology,<00:14:35.000> which<00:14:35.160> is<00:14:35.240> why<00:14:35.400> the<00:14:35.520> reason<00:14:35.839> I<00:14:35.920> got<00:14:36.120> hired<00:14:36.520> to<00:14:36.600> be<00:14:36.760> CEO<00:14:37.280> of<00:14:37.760> Leigh<00:14:37.920> Steinberg<00:14:38.320> Sports<00:14:38.600> and<00:14:38.680> Entertainment 00:14:39.160 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thank<00:21:50.988> you<00:21:51.144> so<00:21:51.300> much<00:21:51.456> for<00:21:51.612> coming<00:21:51.768> on<00:21:51.924> the<00:21:52.080> show. 00:21:52.480 --> 00:21:58.440 What<00:21:52.733> an<00:21:52.987> honor<00:21:53.240> to<00:21:53.493> have<00:21:53.747> you,<00:21:54.000> seriously.<00:21:54.253> <00:21:54.507> Thank<00:21:54.760> you,<00:21:55.013> and<00:21:55.267> I<00:21:55.520> look<00:21:55.773> forward<00:21:56.027> to<00:21:56.280> doing<00:21:56.533> more<00:21:56.787> with<00:21:57.040> Silicon<00:21:57.293> Slopes<00:21:57.547> and<00:21:57.800> you. 00:21:58.440 --> 00:22:02.560 You<00:21:58.520> guys<00:21:58.760> are<00:21:58.840> incredible.<00:21:59.440> What<00:21:59.560> a<00:21:59.600> great<00:21:59.880> podcast,<00:22:00.520> and<00:22:01.000> please<00:22:01.320> come<00:22:01.520> on<00:22:01.640> my<00:22:01.840> podcast. 00:22:02.560 --> 00:22:05.320 <00:22:02.750> Will<00:22:02.940> do.<00:22:03.130> Thank<00:22:03.320> you. ``` ### Lynq CEO Jerald David: How blockchain is reinventing financial infrastructure URL: https://www.ceo.com/episodes/lynq-ceo-jerald-david-how-blockchain-is-reinventing-financial-infrastructure/ Last updated: 2026-08-19T23:49:34.000Z # Jerald David is building finance's missing layer Signature Bank and Silvergate wound down in March 2023\. With them went Signet and SEN, the internal networks that let institutional digital asset firms move dollars between each other at any hour of any day. By [Lynq's own accounting](https://lynq.network/?ref=ceo.com), the industry lost its only compliant way to settle transactions in real time. Markets kept trading around the clock. The money went back to banking hours. "A few years ago, several providers that offered settlement services through banks exited the market. That created an opportunity," Jerald David told CEO.com. "We realized we could build a similar settlement platform outside of the traditional banking infrastructure by using a broker-dealer framework instead." David is the CEO of Lynq, a real-time, interest-bearing settlement network [formed as a joint venture between Arca Labs, Tassat, and tZERO](https://www.americanbanker.com/news/arca-tassat-tzero-lead-joint-creation-of-tokenized-treasury-fund?ref=ceo.com). A tokenized Treasury fund is custodied at a special purpose broker-dealer facilitated by tZERO. U.S. Bank holds the cash. Avalanche runs the blockchain. The network [went live on July 15, 2025](https://www.businesswire.com/news/home/20250701632273/en?ref=ceo.com), with [13 firms onboarded and more than 50 in the pipeline](https://www.businesswire.com/news/home/20250716019467/en?ref=ceo.com). In January, [Crypto.com became the first exchange live on the network](https://lynq.network/crypto-com-completes-integration-to-lynq-aquanow-dv-chain-gsr-nonco-and-wintermute-first-to-post-off-exchange-collateral-via-lynq-network-streamlining-institutional-exchange-funding/?ref=ceo.com), and Aquanow, DV Chain, GSR, Nonco, and Wintermute posted the first collateral. By April, Lynq had [more than 32 institutional clients](https://www.citybiz.co/article/833446/qa-with-jerald-david-ceo-of-lynq/?ref=ceo.com). "At its core, Lynq is a settlement system that allows trusted counterparties to transact in real time while also returning yield and interest to users who keep funds on the platform," David said. Customers started with digital asset trades. They now use the network to fund derivatives exchanges and finance trade. The problem it solves is old. Banks keep hours and markets no longer do, which forces firms to prefund exchanges and park capital they cannot touch on weekends. "If it's midnight Eastern Time and you need to add collateral to a position, you can't simply send a bank wire because banks are closed," David said. "Distributed ledger technology solves that problem. It allows money to move continuously." David has spent more than 20 years building market plumbing. He worked at NYMEX and CME during the shift from open outcry to electronic trading and helped create ClearPort, which moved over-the-counter trades into clearinghouses. He helped launch exchanges in the United Kingdom and Dubai, [came into digital assets as COO of EverMarkets](https://www.businesswire.com/news/home/20250515428106/en/Lynq-the-Real-Time-Yield-Bearing-Settlement-Network-Appoints-Jerald-David-as-CEO?ref=ceo.com), an exchange built to trade commodities and digital assets on one platform, and then ran Arca Labs, where he oversaw the first '40 Act fund to issue its shares as digital asset securities. "Almost every company I've worked for has focused on building lasting financial infrastructure," he said. Running a 24/7 network means living on its schedule. David starts before dawn, catching up on what happened overnight across Telegram, Signal, Slack, and email, then walks to an office he now regrets putting so close to his house. "You know you've got a problem when your dog walker starts dropping your dog off at the office in the afternoon," he said, "because that's where they know you'll be." He has watched the industry's story change every few years. In 2017 everyone said blockchain. Then everyone said crypto. Then real-world assets. Now the public conversation belongs to AI, and David thinks the shift matters less than it appears. "Institutional adoption has continued throughout all of those cycles," he said. "From the beginning, large financial institutions understood the value of blockchain itself. The transparency, the security, the ability to transfer value efficiently. What they weren't necessarily interested in were speculative assets like meme coins." He expects the lull in attention to be temporary. Asked for a plain explanation of tokenization, David used gold. An issuer buys and vaults the metal, then mints tokens representing ownership of it. The reserves are audited, publicly verifiable, and redeemable. "It's really similar to a digital warehouse receipt," he said. "Instead of owning a paper certificate, you own a blockchain token that represents a claim on a real-world asset." He sees the same mechanics working in the dollar's favor. "Today, well over 99% of all stablecoins are denominated in U.S. dollars. That means people around the world are buying dollars in order to participate," he said. "So while people often ask whether digital assets threaten the dollar, they can also strengthen demand for it." CEO.com ends every conversation with the same question. The chances one gives matter as much as the chances one takes, so who gave you a chance? David named three people: Rayne Steinberg of Arca, Glen Sussman of Tassat, and Alan Konevsky of tZERO, the chief executives of the firms that formed Lynq and trusted him to run it. "They believed in the vision we shared and empowered me to build what we believe will become an important piece of financial infrastructure," he said. "I'm incredibly grateful for the confidence they placed in me." ```chapters 00:00:00 Introduction and Guest Welcome 00:00:09 Overview of Link 00:01:34 State of Blockchain and Digital Assets 00:03:57 Market Structure and Regulation 00:05:07 Gerald's Background and Career Path 00:06:09 A Day in the Life of a CEO 00:07:33 Quantum Computing and Blockchain 00:08:41 Market Inefficiencies and Link's Solutions 00:13:17 Blockchain 101 and Tokenization Explained 00:18:06 Stable Tokens and Their Use Cases 00:22:46 Macro-Economic Perspective 00:24:00 The Importance of Stable Tokens for the US Dollar 00:24:16 The Importance of Giving Chances 00:25:08 Closing Remarks and Gratitude ``` ```vtt WEBVTT 00:00:00.160 --> 00:00:02.560 Gerald,<00:00:00.719> thank<00:00:00.880> you<00:00:01.040> so<00:00:01.280> much<00:00:01.360> for<00:00:01.600> coming<00:00:01.839> on<00:00:02.000> the<00:00:02.240> show. 00:00:02.560 --> 00:00:06.480 What<00:00:02.720> an<00:00:02.960> honor<00:00:03.120> 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that<00:04:54.240> you<00:04:54.400> know<00:04:54.880> funds<00:04:55.199> do<00:04:55.520> flow<00:04:55.840> and<00:04:56.080> people<00:04:56.400> actually<00:04:56.639> look<00:04:56.800> at<00:04:56.960> money<00:04:57.280> movements. 00:04:59.280 --> 00:05:01.759 Yeah,<00:04:59.520> that's<00:04:59.840> actually<00:05:00.479> really<00:05:01.199> interesting. 00:05:01.759 --> 00:05:07.120 What<00:05:02.000> were<00:05:02.160> you<00:05:02.320> doing<00:05:02.560> prior<00:05:02.880> to<00:05:03.199> Link?<00:05:03.520> I<00:05:03.680> mean<00:05:03.840> what<00:05:04.000> what<00:05:04.320> led<00:05:04.560> you<00:05:04.720> into<00:05:04.960> this<00:05:05.360> specific<00:05:05.840> industry? 00:05:07.120 --> 00:05:09.759 Yeah,<00:05:07.305> I<00:05:07.489> mean<00:05:07.674> I<00:05:07.858> think<00:05:08.043> there<00:05:08.228> are<00:05:08.412> two<00:05:08.597> different<00:05:08.782> ways<00:05:08.966> to<00:05:09.151> answer<00:05:09.335> the<00:05:09.520> question. 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day<00:06:06.800> look<00:06:07.039> like<00:06:07.199> for<00:06:07.360> you<00:06:07.600> as<00:06:08.000> CEO? 00:06:09.440 --> 00:06:17.919 Yeah.<00:06:09.919> Well,<00:06:10.319> you<00:06:10.479> know,<00:06:11.039> um<00:06:11.680> the<00:06:12.000> interesting<00:06:12.400> thing<00:06:12.720> for<00:06:12.960> us,<00:06:13.120> I<00:06:13.360> think<00:06:13.440> is<00:06:13.600> that<00:06:13.759> digital<00:06:14.080> assets<00:06:14.479> is<00:06:14.639> such<00:06:14.880> a<00:06:15.120> global<00:06:15.600> 24/7<00:06:16.800> type<00:06:17.120> of<00:06:17.600> uh 00:06:17.919 --> 00:06:24.000 uh<00:06:18.160> environment<00:06:18.800> that<00:06:19.039> I<00:06:19.280> would<00:06:19.440> say<00:06:19.600> that,<00:06:19.840> you<00:06:20.000> know,<00:06:20.319> the<00:06:20.560> tools<00:06:20.880> you'd<00:06:21.199> use<00:06:21.360> in,<00:06:21.600> you<00:06:21.680> know,<00:06:21.759> the<00:06:22.000> traditional<00:06:22.400> world<00:06:22.880> are<00:06:23.039> probably<00:06:23.280> quite<00:06:23.520> different. 00:06:24.000 --> 00:06:29.360 So,<00:06:24.160> we're<00:06:24.400> connected<00:06:24.880> 24/7<00:06:25.600> using<00:06:26.080> Telegram,<00:06:26.639> using<00:06:27.039> Signal,<00:06:27.680> using<00:06:28.400> uh<00:06:28.639> Slack. 00:06:29.360 --> 00:06:32.160 Um<00:06:29.680> notwithstanding,<00:06:30.319> you<00:06:30.479> know,<00:06:30.639> email<00:06:30.880> on<00:06:31.120> the<00:06:31.280> phone<00:06:31.440> that<00:06:31.600> comes<00:06:31.840> in. 00:06:32.160 --> 00:06:37.039 So,<00:06:32.560> I<00:06:32.720> hate<00:06:32.880> to<00:06:32.960> say<00:06:33.039> it,<00:06:33.199> but<00:06:33.360> my<00:06:33.520> general<00:06:33.759> day<00:06:33.919> is<00:06:34.080> waking<00:06:34.319> up<00:06:34.479> super<00:06:34.720> early,<00:06:35.199> checking<00:06:35.440> in<00:06:35.600> to<00:06:35.759> see<00:06:35.840> what<00:06:36.080> happened<00:06:36.240> overnight. 00:06:37.039 --> 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the<00:25:18.720> market. 00:25:19.520 --> 00:25:22.000 [laughter]<00:25:19.709> Well,<00:25:19.898> it's<00:25:20.087> amazing<00:25:20.276> what<00:25:20.465> you're<00:25:20.655> doing.<00:25:20.844> It's<00:25:21.033> amazing<00:25:21.222> what<00:25:21.411> you're<00:25:21.600> building. 00:25:22.000 --> 00:25:24.720 Thank<00:25:22.159> you<00:25:22.240> so<00:25:22.400> much<00:25:22.559> for<00:25:22.720> joining<00:25:22.960> us.<00:25:23.200> Seriously,<00:25:23.600> a<00:25:23.760> real<00:25:23.919> pleasure. 00:25:24.720 --> 00:25:26.720 [laughter]<00:25:24.880> Amazing.<00:25:25.040> Clint,<00:25:25.200> thanks<00:25:25.360> so<00:25:25.520> much<00:25:25.680> for<00:25:25.840> having<00:25:26.000> me<00:25:26.160> on<00:25:26.320> the<00:25:26.480> show. 00:25:26.720 --> 00:25:29.440 Great<00:25:26.880> to<00:25:27.039> be<00:25:27.120> with<00:25:27.279> you<00:25:27.440> today. ``` ### BRUNT Workwear Founder & CEO Eric Girouard: How authentic brands win URL: https://www.ceo.com/episodes/brunt-workwear-founder-ceo-eric-girouard-how-authentic-brands-win/ Last updated: 2026-08-20T00:07:03.000Z # Eric Girouard left fashion to dress the people who build everything At his bachelor party, Eric Girouard's friends sat him down on a dock and pitched him a company. He had gone off to work in fashion e-commerce. They had stayed in Bristol, Connecticut, and gone into the trades, the way almost everyone they grew up with did. You work in fashion, they told him. Build a brand for us. He thought they meant trucks or knives. They meant boots. They were wearing the same work boots their fathers wore, and their grandfathers before that, and nobody had ever built a brand that represented them. Girouard knew the world they were describing. His father built airplane engines at night for Pratt & Whitney, slept a few hours, then roofed all day for a friend's company. Girouard joined him on the roof at 14, lasted one summer, and started a landscaping business that lost money on nearly every job he bid. His parents never went to college. They told him he had a knack for business and should go learn what they couldn't teach him. His friends went into the trades or the military. He went to school, then talked his way into a chief of staff job with Ben Fishman, the entrepreneur behind Lids and Rue La La, by promising to outwork everyone in the building. He was 22. When he finally left to start the company in 2018, he had a five-month-old son, a new mortgage, and a market research finding that would have discouraged most people: every work boot already existed, at every price point, made by companies pushing a century of heritage. 1889\. 1909\. Craftsmanship and history. His friends did not care about any of it. They wanted a brand that looked like them and showed up where they spent time. That was the whole thesis, and it was hard to raise money on. So the friends became the company's product department. Girouard ran every tagline and every mission statement past them before launch. A full year before BRUNT sold anything, he started a podcast featuring plumbers, builders, and contractors, on the theory that you create value before you ask anyone to buy. The Marin, one of four boots in the launch lineup, is named after Matt Marin, a union drywaller Girouard has known since nursery school. Marin's complaints became the spec sheet: boots cost too much, took too long to break in, wore out too fast. The Marin has sold more than two million pairs and is still the company's number one product. The discipline has held as the company scaled. Product development starts with customer research, runs through months of wear-testing, and takes 10 to 18 months per launch. The one product that missed expectations was the one where Girouard skipped a validation step. He says the mistake was his. BRUNT launched in September 2020\. In its sixth year, it passed [$300 million in annual revenue](https://www.shopify.com/case-studies/brunt-workwear?ref=ceo.com). A wholesale program that [launched in February 2024](https://www.prnewswire.com/news-releases/brunt-workwear-announces-next-generation-flagship-boots-wholesale-distribution-with-more-than-20-retailers-nationwide-302060540.html?ref=ceo.com) now spans roughly [2,000 stores](https://www.shopify.com/case-studies/brunt-workwear?ref=ceo.com), with retail partners including [Boot Barn and Scheels](https://www.globenewswire.com/news-release/2026/04/30/3284920/0/en/brunt-workwear-announces-first-retail-store-as-demand-for-skilled-trades-surges.html?ref=ceo.com). In January the company [hired a chief financial and operating officer and a chief people officer](https://www.globenewswire.com/news-release/2026/01/27/3226574/0/en/brunt-workwear-adds-veteran-leadership-to-executive-team.html?ref=ceo.com). In April it [announced its first flagship store](https://www.globenewswire.com/news-release/2026/04/30/3284920/0/en/brunt-workwear-announces-first-retail-store-as-demand-for-skilled-trades-surges.html?ref=ceo.com) in North Reading, Massachusetts. The store opened May 2 and [ran out of inventory](https://www.shopify.com/case-studies/brunt-workwear?ref=ceo.com) in its first week. None of this required predicting the current trades boom, and Girouard doesn't claim he did. He just believed more people looked like his friends than the customers he had been serving in fashion. Roughly 31 million Americans work in the trades. They kept working through the pandemic because the country cannot function without them, and they keep buying boots in every economy. AI now threatens plenty of white-collar work. It cannot plumb a house. Girouard built his home half a mile from the office. His oldest son wakes at 5:07 every morning, almost exactly. Girouard gets the kids to school, walks to work, folds a sheet of paper in half, and rewrites his priorities from scratch. He goes home for dinner, back to the office, home for bedtime stories, back to the office until 11\. His stated worry is not a competitor. It is becoming what he disrupted: a legacy brand that spends its time talking about itself. Every Thursday, BRUNT opens the garage attached to headquarters and people from the community come by. Some of them don't buy anything. Asked who gave him a chance, Girouard doesn't hesitate. Ben Fishman hired a 23-year-old with no credentials, invested in BRUNT at the start, and now sits on the board. The friends from the dock got something too. One of them has his name on two million pairs of boots. ```chapters 00:00:00 Introduction and Background of Eric and Brunt Workwear 00:00:41 Eric's Blue-Collar Roots and Early Entrepreneurial Ventures 00:02:14 Learning from Serial Entrepreneur Ben Fishman 00:03:41 The Genesis of Brunt Workwear 00:05:06 Building a Brand for Tradespeople 00:06:08 The Role of AI in Brunt Workwear 00:10:03 The Importance of Building a Brand 00:14:28 Community Building and Brand Building 00:16:46 The Process of Bringing a Product to Market 00:21:36 The State of E-commerce and Brunt's Success 00:25:07 A Day in the Life of Eric 00:29:07 Principles of Leadership 00:33:57 Trends in the Trade Industry and Macro Economy 00:37:10 The Importance of Giving and Taking Chances 00:38:55 Conclusion and Final Thoughts ``` ```vtt WEBVTT 00:00:00.440 --> 00:00:02.480 Eric,<00:00:00.800> thank<00:00:01.040> you<00:00:01.120> so<00:00:01.240> much<00:00:01.400> for<00:00:01.560> coming<00:00:01.840> on<00:00:01.920> 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years<00:02:52.320> starting<00:02:52.760> businesses<00:02:53.320> from<00:02:53.440> scratch<00:02:53.880> where 00:02:53.959 --> 00:02:58.440 I<00:02:54.000> got<00:02:54.160> to<00:02:54.240> see<00:02:54.360> it<00:02:54.440> go<00:02:54.560> from<00:02:54.720> an<00:02:54.840> idea<00:02:55.400> to<00:02:55.520> its<00:02:55.640> first<00:02:55.880> million,<00:02:56.200> first<00:02:56.440> 10<00:02:56.600> million,<00:02:56.959> first<00:02:57.280> 50<00:02:57.520> million. 00:02:58.440 --> 00:03:00.840 And<00:02:59.120> finally<00:02:59.600> I<00:02:59.680> said,<00:02:59.920> "Okay,<00:03:00.080> I've<00:03:00.239> seen<00:03:00.519> enough. 00:03:00.840 --> 00:03:03.320 I<00:03:00.880> know<00:03:01.040> where<00:03:01.160> my<00:03:01.280> strengths<00:03:01.680> are.<00:03:02.000> I<00:03:02.080> know<00:03:02.239> where<00:03:02.360> my<00:03:02.519> weaknesses<00:03:03.040> are. 00:03:03.320 --> 00:03:10.000 I<00:03:03.360> know<00:03:03.480> how<00:03:03.560> 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go<00:03:15.320> for<00:03:15.480> it<00:03:15.560> right<00:03:15.720> now." 00:03:16.000 --> 00:03:24.640 In<00:03:16.239> 2018<00:03:17.160> I<00:03:17.239> left<00:03:17.519> and<00:03:17.600> started<00:03:17.840> working<00:03:18.120> on<00:03:18.239> what's<00:03:18.480> now<00:03:19.560> um<00:03:19.640> Brunt<00:03:19.880> Workwear<00:03:20.280> and<00:03:21.200> uh<00:03:21.800> the<00:03:21.880> guys<00:03:22.160> that<00:03:22.280> I<00:03:22.360> grew<00:03:22.480> up<00:03:22.600> with<00:03:23.680> from<00:03:23.959> childhood,<00:03:24.440> from 00:03:24.640 --> 00:03:29.680 literally<00:03:25.000> from<00:03:25.160> nursery<00:03:25.440> school,<00:03:25.640> were<00:03:25.720> the<00:03:25.800> guys<00:03:26.000> that<00:03:26.120> gave<00:03:26.280> me<00:03:26.360> the<00:03:26.480> idea<00:03:26.800> when<00:03:26.959> I<00:03:27.000> was<00:03:27.239> working<00:03:27.560> on<00:03:27.680> some<00:03:27.840> of<00:03:27.920> those<00:03:28.040> other<00:03:28.200> 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stuff. 00:04:51.040 --> 00:04:56.840 We're<00:04:51.200> going<00:04:51.320> to<00:04:51.360> build<00:04:51.520> a<00:04:51.560> brand<00:04:51.800> that<00:04:51.960> looks<00:04:52.200> like<00:04:52.400> my<00:04:52.560> buddies<00:04:52.880> look,<00:04:53.160> talks<00:04:53.480> like<00:04:53.680> they<00:04:53.840> talk,<00:04:54.200> show<00:04:54.400> up<00:04:54.520> in<00:04:54.600> the<00:04:54.720> channels<00:04:55.160> that<00:04:55.320> they<00:04:55.480> spend<00:04:55.720> their<00:04:55.840> time<00:04:56.200> on,<00:04:56.600> and 00:04:56.840 --> 00:05:00.440 and<00:04:57.000> the<00:04:57.480> and<00:04:57.680> so<00:04:57.840> on<00:04:57.960> and<00:04:58.040> so<00:04:58.160> forth.<00:04:58.600> And<00:04:58.720> that's<00:04:58.960> going<00:04:59.080> to<00:04:59.160> be<00:04:59.280> the<00:04:59.360> difference. 00:05:00.440 --> 00:05:07.080 Very<00:05:00.720> hard<00:05:01.240> to<00:05:01.800> convince<00:05:02.200> people<00:05:02.520> 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genius. 00:06:11.440 --> 00:06:13.800 You<00:06:11.560> predicted<00:06:12.040> what<00:06:12.160> was<00:06:12.280> going<00:06:12.400> to<00:06:12.480> happen<00:06:12.800> 6<00:06:13.040> years<00:06:13.240> down<00:06:13.440> the<00:06:13.520> road." 00:06:13.800 --> 00:06:22.000 To<00:06:13.880> be<00:06:14.160> you<00:06:14.280> know,<00:06:14.440> to<00:06:14.560> be<00:06:14.680> honest,<00:06:15.080> I<00:06:15.120> I<00:06:15.360> I<00:06:15.400> didn't<00:06:16.280> honestly<00:06:16.760> all<00:06:17.080> I<00:06:17.160> knew<00:06:17.400> at<00:06:17.520> the<00:06:17.600> time<00:06:18.280> was<00:06:20.520> I<00:06:20.680> knew<00:06:20.919> there<00:06:21.080> were<00:06:21.200> more<00:06:21.560> you<00:06:21.640> know,<00:06:21.760> I<00:06:21.840> was 00:06:22.000 --> 00:06:24.400 in<00:06:22.120> fashion.<00:06:22.720> I<00:06:22.800> was<00:06:22.960> in<00:06:23.080> beauty.<00:06:23.520> I<00:06:23.560> was<00:06:23.680> in<00:06:23.800> all<00:06:23.880> these<00:06:24.040> things. 00:06:24.400 --> 00:06:31.000 And<00:06:24.520> I<00:06:24.600> just<00:06:24.840> knew<00:06:25.320> I<00:06:25.360> didn't<00:06:25.520> have<00:06:25.640> access<00:06:25.960> to<00:06:26.080> data<00:06:26.360> like<00:06:26.560> I<00:06:26.600> do<00:06:26.760> now,<00:06:27.000> but<00:06:27.120> I<00:06:27.160> just<00:06:27.400> knew<00:06:27.560> there<00:06:27.680> were<00:06:27.840> more<00:06:28.040> people<00:06:28.440> that<00:06:28.640> looked<00:06:28.880> like<00:06:29.080> my<00:06:29.200> buddies<00:06:29.560> from<00:06:29.760> home,<00:06:30.520> blue-collar 00:06:31.000 --> 00:06:38.200 jobs<00:06:31.640> with<00:06:31.880> families.<00:06:33.320> There<00:06:33.400> was<00:06:33.520> just<00:06:33.720> more<00:06:33.960> of<00:06:34.160> people<00:06:34.600> like<00:06:34.840> that<00:06:35.200> than<00:06:35.360> there<00:06:35.520> were<00:06:35.800> that<00:06:35.960> I<00:06:36.080> was<00:06:36.240> going<00:06:36.520> 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you<00:08:18.320> thinking<00:08:18.600> about<00:08:18.840> it?<00:08:19.680> We<00:08:20.120> are<00:08:20.840> our<00:08:21.080> organization<00:08:21.840> is<00:08:22.320> an<00:08:22.680> incredibly<00:08:24.800> uh<00:08:25.520> AI<00:08:26.080> interested 00:08:27.120 --> 00:08:30.000 not<00:08:27.320> only<00:08:27.520> interested<00:08:28.000> but<00:08:28.360> AI<00:08:28.919> adaptive<00:08:29.560> group. 00:08:30.000 --> 00:08:33.520 Um<00:08:30.280> so<00:08:30.440> much<00:08:30.680> so<00:08:30.800> we're<00:08:30.919> trying<00:08:31.160> to<00:08:31.240> figure<00:08:31.440> out<00:08:31.520> to<00:08:31.640> make<00:08:31.800> sure<00:08:31.960> how<00:08:32.159> are<00:08:32.240> we<00:08:32.360> controlling<00:08:32.880> it<00:08:33.039> in<00:08:33.120> some<00:08:33.280> degree. 00:08:33.520 --> 00:08:41.280 We<00:08:33.640> don't<00:08:33.760> want<00:08:33.880> to<00:08:33.919> control<00:08:34.320> the<00:08:34.479> entrepreneurial<00:08:35.120> 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work<00:09:00.880> that<00:09:01.000> you're<00:09:01.120> doing. 00:09:01.360 --> 00:09:08.360 Things<00:09:01.600> that<00:09:01.720> used<00:09:01.880> to<00:09:01.960> take<00:09:02.200> me<00:09:02.440> weeks<00:09:02.920> and<00:09:03.120> months<00:09:03.560> and<00:09:04.400> I<00:09:04.480> can<00:09:04.640> now<00:09:04.800> compress<00:09:05.280> into<00:09:05.520> a<00:09:05.600> few<00:09:05.839> short<00:09:06.240> short<00:09:06.520> hours<00:09:06.880> as<00:09:07.040> I<00:09:07.080> think<00:09:07.320> about<00:09:07.600> our<00:09:07.720> product<00:09:08.120> teams. 00:09:08.360 --> 00:09:13.960 Our<00:09:08.440> product<00:09:08.760> teams<00:09:08.960> used<00:09:09.120> to<00:09:09.200> have<00:09:09.360> to<00:09:09.480> make<00:09:10.040> full-blown<00:09:10.520> physical<00:09:10.920> samples<00:09:11.360> in<00:09:11.480> different<00:09:11.760> colorways<00:09:12.240> of<00:09:12.360> products<00:09:12.760> a<00:09:12.800> boot. 00:09:13.960 --> 00:09:20.120 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and<00:09:26.600> transportation<00:09:28.160> to 00:09:30.800 --> 00:09:37.920 to<00:09:30.920> our<00:09:31.040> operations<00:09:31.560> team<00:09:31.800> which<00:09:31.920> is<00:09:32.040> using<00:09:32.360> it<00:09:32.440> to<00:09:32.560> optimize<00:09:33.200> how<00:09:33.560> containers<00:09:34.160> are<00:09:34.240> packed<00:09:34.600> and<00:09:34.720> saving<00:09:35.080> like<00:09:35.720> we<00:09:35.800> have<00:09:35.920> the<00:09:36.040> software<00:09:36.520> that<00:09:36.720> automates<00:09:37.200> how<00:09:37.360> to<00:09:37.560> pack 00:09:37.920 --> 00:09:40.480 a<00:09:37.960> container<00:09:38.480> and<00:09:38.640> save<00:09:39.280> uh<00:09:39.360> space<00:09:39.680> in<00:09:39.760> the<00:09:39.800> shipping<00:09:40.120> container. 00:09:40.480 --> 00:09:42.480 That<00:09:40.680> saved<00:09:41.640> millions<00:09:41.960> of<00:09:42.040> dollars. 00:09:42.480 --> 00:09:49.560 Like,<00:09:42.960> any<00:09:43.200> aspect<00:09:43.600> 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built<00:09:58.680> Brunt<00:09:58.920> today<00:09:59.120> if<00:09:59.280> I<00:09:59.360> started<00:09:59.720> today<00:10:00.400> catastrophically. 00:10:01.440 --> 00:10:05.800 Yeah.<00:10:01.720> It's<00:10:01.800> a<00:10:01.840> game<00:10:01.920> changer.<00:10:03.240> What<00:10:03.720> goes<00:10:04.080> into<00:10:04.560> building<00:10:05.080> a<00:10:05.160> brand? 00:10:05.800 --> 00:10:12.840 I<00:10:05.880> think<00:10:06.160> you<00:10:06.520> are<00:10:06.680> uniquely<00:10:07.320> qualified<00:10:07.960> to<00:10:08.040> kind<00:10:08.240> of<00:10:08.840> tell<00:10:09.080> founders<00:10:09.600> and<00:10:09.720> other<00:10:09.880> CEOs<00:10:10.400> like<00:10:10.600> what<00:10:10.760> it<00:10:10.880> means<00:10:11.200> to<00:10:11.280> build<00:10:11.560> a<00:10:11.600> brand. 00:10:12.840 --> 00:10:15.440 Yeah,<00:10:13.160> so<00:10:15.080> it's<00:10:15.200> funny. 00:10:15.440 --> 00:10:22.480 I<00:10:15.520> I<00:10:15.920> I<00:10:15.960> 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answer. 00:10:57.600 --> 00:11:05.760 And<00:10:57.760> so<00:10:57.920> as<00:10:58.080> I<00:10:58.160> think<00:10:58.360> about<00:10:58.600> brand,<00:10:58.880> brand<00:10:59.320> is<00:11:01.480> what<00:11:01.760> you<00:11:01.920> are<00:11:02.120> as<00:11:02.240> a<00:11:02.280> company,<00:11:03.080> what<00:11:03.560> how<00:11:03.800> how<00:11:04.000> your<00:11:04.160> brand<00:11:04.360> makes<00:11:04.520> people<00:11:04.839> feel,<00:11:05.600> what 00:11:05.760 --> 00:11:08.520 do<00:11:05.839> they<00:11:05.960> tell<00:11:06.280> someone<00:11:06.600> else<00:11:06.800> about<00:11:07.080> your<00:11:07.160> brand<00:11:07.400> when<00:11:07.520> you're<00:11:07.640> not<00:11:07.839> in<00:11:07.920> the<00:11:08.000> room. 00:11:08.520 --> 00:11:12.120 It's<00:11:08.839> it's<00:11:09.360> how<00:11:09.480> you<00:11:09.640> look,<00:11:09.880> how<00:11:10.000> you<00:11:10.120> feel,<00:11:10.400> how<00:11:10.520> you<00:11:10.680> act,<00:11:10.920> 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00:38:57.480 --> 00:39:00.480 Seriously,<00:38:57.880> this<00:38:58.040> has<00:38:58.160> been<00:38:58.320> a<00:38:58.360> fascinating<00:38:58.840> conversation.<00:38:59.520> Congratulations<00:39:00.360> too. 00:39:00.480 --> 00:39:06.000 Like<00:39:00.720> I<00:39:00.760> said,<00:39:01.000> like<00:39:01.200> in<00:39:01.320> a<00:39:01.360> time<00:39:01.720> where<00:39:02.400> e-commerce<00:39:02.960> really<00:39:03.240> is<00:39:03.400> struggling,<00:39:04.080> Brunt<00:39:04.520> is<00:39:04.680> doing<00:39:04.960> the<00:39:05.040> exact<00:39:05.480> opposite. 00:39:06.000 --> 00:39:10.840 What<00:39:06.160> you've<00:39:06.320> built<00:39:06.560> here<00:39:06.760> is<00:39:07.120> phenomenal.<00:39:08.200> So,<00:39:08.400> well<00:39:08.560> done<00:39:08.880> and<00:39:09.040> thank<00:39:09.240> you<00:39:09.360> so<00:39:09.520> much. 00:39:10.840 --> 00:39:14.400 <00:39:11.035> Thank<00:39:11.230> you,<00:39:11.425> Clint.<00:39:11.620> I<00:39:11.815> appreciate<00:39:12.010> for<00:39:12.205> having<00:39:12.400> me. ``` ### Blueprint Equity Managing Partner Sheldon Lewis: Is the SaaSpocalypse real? URL: https://www.ceo.com/episodes/blueprint-equity-managing-partner-sheldon-lewis-is-the-saaspocalypse-real/ Last updated: 2026-10-02T03:31:13.000Z # Sheldon Lewis doesn't believe in the SaaSpocalypse Blueprint Equity opened the data room for its third fund on Monday, January 5\. It [held a final close on Friday, January 16](https://peprofessional.com/2026/01/blueprint-races-to-close-on-333-million-third-fund/?ref=ceo.com), at [$333 million, oversubscribed](https://www.businesswire.com/news/home/20260121486317/en/Blueprint-Equity-Raises-%24333M-Fund-III-Doubling-Down-on-Enterprise-Software-B2B-and-Technology-Enabled-Services-Businesses-Worldwide?ref=ceo.com). Twelve days, in a market where much of the software investing world has stopped moving. "If I had to summarize the current market, I'd say a lot of firms are frozen," Sheldon Lewis said on the CEO.com podcast. "There are still trillions of dollars available to invest, so capital will find a home eventually. But many firms are trying to decide whether they should dramatically change their investment strategies or simply wait for more clarity." Lewis is the co-founder and Managing Partner of [Blueprint Equity](https://www.onblueprint.com/?ref=ceo.com), a San Diego growth equity firm with more than $600 million under management. He has been investing in software for more than 20 years. "This is simultaneously the most exciting and the scariest time I've ever seen to be a software investor," he said. The fear has a name now. The SaaSpocalypse theory holds that AI has made software so cheap to build that the companies selling it are doomed. Public SaaS valuations have compressed. Investors have pulled back while they wait to see what survives. "I think it's massively overblown," Lewis said. "Yes, software is easier to build than ever before. Yes, AI allows people to launch products faster and more cheaply. But nobody is going home tonight and vibe-coding a complete operating system for a construction company." A software investor arguing that the software apocalypse is overstated is talking his book, and it is fair to say so. It is also fair to say that the people whose money is at stake agree with him. Fund III was backed by endowments, foundations, and hospital systems, and returning investors from the first two funds put in again, among them Accolade Partners, the David and Lucile Packard Foundation, and Makena Capital Management. Whatever the discourse says about software, the institutions closest to Blueprint's returns committed a third of a billion dollars behind the thesis in less than two weeks. Lewis's case for it starts with what software companies actually do. The code was never the whole product. Vendors handle compliance, implementation, support, and sales, and none of that disappears because a prototype got cheaper. "Software businesses may become leaner, but it's very difficult to build a substantial company as a one-person operation," he said. "The strongest software companies should actually become more profitable if they adopt AI effectively." He does not invest in public markets, and said so, then offered a view anyway: many public SaaS companies now look significantly undervalued to him. "The market had a bit of a collective panic." Blueprint invests almost entirely at Series A, in companies doing between $1 million and $7 million in annual recurring revenue and growing more than 75% a year. Most are bootstrapped or lightly funded. Blueprint is usually the first institutional money in. Since Lewis and Bobby Ocampo founded the firm in 2018, the thesis has stayed the same: vertical operating systems and systems of record, the software an industry runs on rather than the software it merely uses. Of 26 investments, the vast majority fit that description. "The closer your software is to a customer's day-to-day operations, the more valuable it becomes," Lewis said. "The more unique data you have, the stronger your long-term competitive advantage." Develo, a recent investment, builds an AI-native operating system for pediatricians. Notes, prescriptions, insurance. "Pediatricians aren't going to build their own HIPAA-compliant software stack," Lewis said. The rest of the portfolio runs the same direction, into big markets that digitized late: construction, property management, golf courses, pickleball and padel facilities. AI is already changing how much capital these companies ask for. Founders want less than they did three or five years ago, and Lewis sees a live question about whether some companies can raise one institutional round, grow efficiently, and never need another. "I don't think we're fully there yet. But there's no question companies can accomplish more with less money today." He knows what that question implies for his own industry. If companies need less capital, some investors become unnecessary. His bet is that the first check, the one that professionalizes a bootstrapped business, is the one that survives. On founders, Lewis used to prize the operator who lived a problem and built the fix. He still values it. Now he cares more about what a founder becomes after the check clears. "We're betting as much on the jockey as we are on the horse," he said. A founder who says they can build to $5 million but will need help beyond it has, in his view, given a good answer. Most of Blueprint's companies have no formal board when the firm invests, so Blueprint often helps build the first one. Lewis has one rule for making boards work. "Bad news isn't the problem. Surprises are the problem." He tells founders to call each board member a week early and preview anything difficult, so the meeting is spent on solutions instead of reactions. The firm is staffing up around that model. Blueprint [added nine employees between February and August](https://www.businesswire.com/news/home/20260804043078/en/Blueprint-Equity-Expands-Team-to-Deepen-Founder-Support-and-Scale-Its-Value-Creation-Platform?ref=ceo.com), bringing the team to 21, including a Head of Artificial Intelligence. Lewis said six people at the firm now do nothing but help portfolio companies hire talent, sharpen go-to-market, and implement AI. Lewis was asked about the growing public anger at AI, the data center protests, the booed commencement speakers. "Honestly, I understand it. If I were graduating college today and struggling to find an entry-level job because AI was automating some of those roles, I'd probably be frustrated too." He believes regulation should come, and that the technology will not be uninvented either way. "AI is disrupting real lives today. And honestly, there's a scenario where all of us are affected in some way. That's reason enough to take it seriously." Every CEO.com interview ends the same way, with the belief that the chances one gives are just as important as the chances one takes. Lewis pointed first to his parents. His mom was a school nurse. His dad worked several jobs, including ski instructor. Professionally, he named Gavin Turner and Jason Payne of Mainsail Partners, who brought him over from investment banking, and Dave Dutch, a mentor and close friend who officiated his wedding a year ago. "Those people believed in me, invested in me, and gave me opportunities I wouldn't have had otherwise. I owe them a tremendous amount." His prediction on the panic that named this episode: "My guess is that six to nine months from now, there will be much greater clarity around what AI can and cannot do, and many people will realize it's more complementary than destructive." The clock started in February, when the market froze. Check back in the fall. ```chapters 00:00:00 Introduction to Blueprint Equity 00:00:50 Blueprint Equity's Investment Focus 00:01:56 The State of SaaS and SaaSpocalypse 00:03:41 Public Market SaaS Companies 00:05:05 Efficiency and AI in Series A Funding 00:08:09 The Future of Venture Capital 00:12:22 The Potential of Software and AI 00:14:08 Exciting Investment Verticals 00:17:10 What Blueprint Equity Looks for in Founders 00:20:29 Effective Board Meetings and Communication 00:23:25 Public Sentiment on AI 00:26:29 A Day in the Life of Sheldon 00:29:00 The Importance of Giving and Receiving Chances ``` ```vtt WEBVTT 00:00:00.000 --> 00:00:05.640 Sheldon,<00:00:00.520> welcome<00:00:00.760> to<00:00:00.800> the<00:00:00.920> show.<00:00:01.840> Uh,<00:00:01.960> you<00:00:02.240> are<00:00:02.480> the<00:00:02.760> managing<00:00:03.320> partner<00:00:03.880> of<00:00:04.040> Blueprint<00:00:04.880> Equity. 00:00:05.640 --> 00:00:11.760 Tell<00:00:05.984> us<00:00:06.328> what<00:00:06.672> Blueprint<00:00:07.016> Equity<00:00:07.360> is.<00:00:07.704> <00:00:08.048> Yeah,<00:00:08.392> so<00:00:08.736> Blueprint<00:00:09.080> Equity<00:00:09.424> is<00:00:09.768> a<00:00:10.112> growth<00:00:10.456> equity<00:00:10.800> fund. 00:00:11.760 --> 00:00:20.280 Um,<00:00:12.240> so,<00:00:13.200> uh,<00:00:13.480> similar<00:00:13.960> to<00:00:14.240> a<00:00:14.480> venture<00:00:14.800> capital<00:00:15.240> or<00:00:15.480> a<00:00:15.520> private<00:00:15.880> equity<00:00:16.160> fund,<00:00:17.120> uh,<00:00:17.280> but<00:00:17.400> we're<00:00:17.520> kind<00:00:17.760> of<00:00:17.840> in<00:00:17.920> the<00:00:18.000> middle<00:00:18.520> and<00:00:18.680> I<00:00:18.720> can<00:00:19.000> talk<00:00:19.320> about<00:00:19.520> the<00:00:19.600> differences<00:00:20.120> if 00:00:20.280 --> 00:00:24.880 you<00:00:20.360> want<00:00:20.560> at<00:00:20.640> any<00:00:20.840> point,<00:00:21.200> but,<00:00:21.920> um,<00:00:23.000> uh,<00:00:23.240> but<00:00:23.400> yeah,<00:00:23.720> we're<00:00:24.000> a,<00:00:24.240> a<00:00:24.400> fund. 00:00:24.880 --> 00:00:33.160 We<00:00:24.960> have<00:00:25.040> about<00:00:25.320> 600<00:00:25.760> million<00:00:26.000> under<00:00:26.160> management.<00:00:27.200> Um,<00:00:28.040> uh,<00:00:28.200> lucky<00:00:28.520> enough<00:00:28.800> to<00:00:28.960> invest<00:00:29.480> in,<00:00:30.200> um,<00:00:30.600> great<00:00:31.040> entrepreneurs,<00:00:32.480> uh,<00:00:32.759> and<00:00:32.920> work 00:00:33.160 --> 00:00:41.680 with<00:00:33.320> them<00:00:33.520> to<00:00:33.640> grow.<00:00:34.040> They're<00:00:34.360> mostly<00:00:34.920> B2B,<00:00:36.040> uh,<00:00:36.480> vertical,<00:00:37.680> uh,<00:00:37.960> operating<00:00:38.440> systems,<00:00:39.680> uh,<00:00:40.360> or,<00:00:41.040> uh,<00:00:41.240> vertical 00:00:41.680 --> 00:00:49.280 SaaS,<00:00:42.680> um,<00:00:43.600> uh,<00:00:43.680> systems<00:00:45.040> from<00:00:45.280> one<00:00:45.440> stage<00:00:45.760> to<00:00:45.840> the<00:00:45.880> next<00:00:46.120> stage,<00:00:46.880> uh,<00:00:47.280> and<00:00:47.600> help<00:00:47.840> out<00:00:47.960> quite<00:00:48.120> a<00:00:48.160> bit<00:00:48.320> along<00:00:48.560> the<00:00:48.640> way. 00:00:49.280 --> 00:00:57.520 So<00:00:49.589> <00:00:49.898> Yeah,<00:00:50.208> that's<00:00:50.517> what<00:00:50.826> I'm<00:00:51.135> excited<00:00:51.445> to<00:00:51.754> talk<00:00:52.063> to<00:00:52.372> you<00:00:52.682> about,<00:00:52.991> is<00:00:53.300> it<00:00:53.609> specifically<00:00:53.918> where<00:00:54.228> you're<00:00:54.537> investing<00:00:54.846> right<00:00:55.155> now<00:00:55.465> and<00:00:55.774> kind<00:00:56.083> of<00:00:56.392> the<00:00:56.702> state<00:00:57.011> of<00:00:57.320> that 00:00:57.520 --> 00:01:05.600 market,<00:00:57.920> which<00:00:58.080> is<00:00:58.200> a<00:00:58.280> really<00:00:58.600> interesting<00:00:59.280> and<00:00:59.640> seems<00:00:59.960> to<00:01:00.040> be<00:01:00.480> somewhat<00:01:00.880> volatile<00:01:01.560> and<00:01:01.720> maybe<00:01:02.240> a<00:01:02.320> little<00:01:02.600> bit<00:01:02.960> too<00:01:03.280> crazy,<00:01:03.960> too<00:01:04.120> volatile,<00:01:04.720> honestly. 00:01:05.600 --> 00:01:12.200 Yeah.<00:01:05.920> Uh,<00:01:06.000> which<00:01:06.200> I<00:01:06.280> want<00:01:06.440> to<00:01:06.520> talk<00:01:06.680> to<00:01:06.760> you<00:01:06.800> about,<00:01:07.040> but,<00:01:07.240> but<00:01:07.400> real<00:01:07.600> quick,<00:01:07.840> when<00:01:07.960> you<00:01:08.040> say<00:01:08.160> growth<00:01:08.440> equity,<00:01:08.680> are<00:01:08.760> you,<00:01:08.840> are<00:01:08.960> we<00:01:09.080> talking<00:01:09.440> like<00:01:09.720> Series<00:01:10.200> C,<00:01:10.600> Series<00:01:11.120> D? 00:01:12.200 --> 00:01:14.480 <00:01:12.512> Uh,<00:01:12.824> almost<00:01:13.136> all<00:01:13.448> Series<00:01:13.760> A. 00:01:14.480 --> 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size<00:01:32.840> can<00:01:32.960> be<00:01:33.080> anywhere<00:01:33.400> from<00:01:34.320> 5<00:01:34.840> to<00:01:35.320> 35<00:01:35.880> million. 00:01:37.080 --> 00:01:39.440 <00:01:37.302> Okay,<00:01:37.524> perfect.<00:01:37.747> Okay,<00:01:37.969> that<00:01:38.191> makes<00:01:38.413> a<00:01:38.636> lot<00:01:38.858> of<00:01:39.080> sense. 00:01:39.440 --> 00:01:42.760 So<00:01:40.320> yeah,<00:01:40.520> you're<00:01:40.800> in<00:01:40.880> an<00:01:41.000> interesting<00:01:41.480> spot,<00:01:42.280> right? 00:01:42.760 --> 00:01:51.080 And<00:01:43.640> you<00:01:43.720> particularly<00:01:44.560> in,<00:01:45.000> uh,<00:01:45.680> investing<00:01:46.280> in<00:01:46.480> B2B<00:01:47.680> and<00:01:48.200> SaaS<00:01:48.960> and<00:01:49.120> you,<00:01:49.280> you<00:01:49.400> know,<00:01:49.520> there's<00:01:49.800> this<00:01:50.000> term<00:01:50.280> that's<00:01:50.440> got<00:01:50.840> some 00:01:51.080 --> 00:01:56.440 attention<00:01:51.480> called<00:01:51.680> the<00:01:51.760> SaaS-pocalypse.<00:01:53.320> Give<00:01:53.520> me<00:01:53.680> your<00:01:53.880> sense<00:01:54.320> on<00:01:55.040> the<00:01:55.160> state<00:01:55.440> of<00:01:55.520> SaaS<00:01:55.880> right<00:01:56.080> now. 00:01:56.440 --> 00:02:04.600 <00:01:56.738> Yeah,<00:01:57.036> uh,<00:01:57.335> definitely<00:01:57.633> have<00:01:57.931> heard<00:01:58.229> that<00:01:58.527> term<00:01:58.825> more<00:01:59.124> than<00:01:59.422> more<00:01:59.720> than<00:02:00.018> once<00:02:00.316> as<00:02:00.615> you<00:02:00.913> can<00:02:01.211> imagine<00:02:01.509> over,<00:02:01.807> over<00:02:02.105> the<00:02:02.404> last<00:02:02.702> few<00:02:03.000> months. 00:02:04.600 --> 00:02:07.960 No,<00:02:04.760> you,<00:02:05.040> you<00:02:05.160> summed<00:02:05.400> it<00:02:05.520> up.<00:02:05.760> It's,<00:02:06.080> it's<00:02:06.360> very<00:02:06.640> volatile. 00:02:07.960 --> 00:02:17.280 Um,<00:02:08.520> the,<00:02:09.240> you<00:02:09.360> know,<00:02:09.479> I'd<00:02:09.640> say<00:02:09.880> it's,<00:02:10.640> you<00:02:10.720> know,<00:02:10.840> for<00:02:11.000> me<00:02:11.880> I've<00:02:12.120> been<00:02:13.160> investing<00:02:13.880> now<00:02:14.200> for<00:02:14.520> over,<00:02:14.959> for<00:02:15.400> about<00:02:15.840> 20<00:02:16.160> years 00:02:17.280 --> 00:02:25.800 and<00:02:18.480> it's,<00:02:18.920> it's<00:02:19.200> the<00:02:19.760> most<00:02:20.000> exciting<00:02:20.520> and<00:02:20.640> the<00:02:20.720> scariest<00:02:21.440> time<00:02:22.360> at<00:02:23.600> the<00:02:23.720> same<00:02:24.040> time<00:02:24.480> to<00:02:24.640> be<00:02:24.959> a,<00:02:25.720> a 00:02:25.800 --> 00:02:34.080 software<00:02:26.240> investor,<00:02:26.640> exciting<00:02:27.120> because<00:02:28.040> we<00:02:28.160> have<00:02:28.280> this<00:02:28.480> new<00:02:29.400> world<00:02:29.920> that's,<00:02:30.440> that's<00:02:30.680> quickly<00:02:31.120> playing<00:02:31.480> out<00:02:31.760> for<00:02:31.920> our<00:02:32.160> eyes<00:02:33.480> and<00:02:33.640> a<00:02:33.680> ton<00:02:33.959> of 00:02:34.080 --> 00:02:40.480 opportunity,<00:02:35.600> scary<00:02:36.160> because<00:02:36.760> the,<00:02:36.840> like<00:02:37.080> you<00:02:37.200> said,<00:02:37.480> everything<00:02:37.840> is<00:02:37.959> changing<00:02:38.480> so,<00:02:39.040> so<00:02:39.280> quickly. 00:02:40.480 --> 00:02:43.520 So,<00:02:41.840> yeah,<00:02:42.000> it's<00:02:42.200> a<00:02:42.240> little<00:02:42.440> bit<00:02:42.600> of<00:02:42.680> both<00:02:43.000> right<00:02:43.200> now. 00:02:43.520 --> 00:02:51.920 I<00:02:43.600> think<00:02:44.080> you<00:02:44.200> know,<00:02:44.320> the,<00:02:45.120> the<00:02:45.240> state<00:02:45.520> of<00:02:45.600> the<00:02:45.640> market<00:02:46.160> if<00:02:46.320> I<00:02:46.400> had<00:02:46.480> to<00:02:46.560> sum<00:02:46.760> it<00:02:46.880> up,<00:02:47.160> not<00:02:47.440> just<00:02:47.720> for,<00:02:48.920> um,<00:02:49.520> for<00:02:49.959> where<00:02:50.120> we<00:02:50.280> sit<00:02:50.560> in<00:02:50.680> kind<00:02:50.840> of<00:02:50.920> the<00:02:51.000> growth<00:02:51.280> equity<00:02:51.600> world 00:02:51.920 --> 00:02:56.680 but<00:02:52.240> Upstream<00:02:52.760> from<00:02:52.959> us,<00:02:53.160> the<00:02:53.280> larger<00:02:53.640> growth<00:02:53.959> equity<00:02:54.240> or,<00:02:54.560> or<00:02:55.040> private<00:02:55.360> equity<00:02:55.640> firms. 00:02:56.680 --> 00:03:04.880 Um,<00:02:57.680> a<00:02:57.800> lot<00:02:58.120> of<00:02:58.240> folks<00:02:58.560> are,<00:02:58.760> are<00:02:58.880> just<00:02:59.040> kind<00:02:59.239> of<00:02:59.880> it<00:03:00.000> seems<00:03:00.280> like<00:03:00.800> almost<00:03:01.120> frozen<00:03:02.080> because<00:03:02.560> they're<00:03:02.800> trying<00:03:03.239> to<00:03:03.320> figure<00:03:03.720> out,<00:03:04.000> hey,<00:03:04.800> you 00:03:04.880 --> 00:03:12.959 know,<00:03:05.239> they<00:03:05.440> still<00:03:05.720> have<00:03:05.920> trillions<00:03:06.480> of<00:03:06.600> dollars<00:03:07.000> to<00:03:07.120> deploy<00:03:08.040> and<00:03:08.239> so<00:03:08.400> they<00:03:08.600> will,<00:03:09.200> you<00:03:09.280> know,<00:03:09.440> find<00:03:09.720> a<00:03:09.760> way<00:03:09.880> to<00:03:10.000> deploy<00:03:10.360> it,<00:03:10.800> but<00:03:10.920> they're<00:03:11.040> trying<00:03:11.280> to<00:03:11.360> figure<00:03:11.600> out,<00:03:12.440> do<00:03:12.720> we 00:03:12.959 --> 00:03:20.840 re-point<00:03:13.234> the<00:03:13.509> cannon<00:03:13.785> a<00:03:14.060> certain<00:03:14.335> direction<00:03:14.610> or,<00:03:14.886> you<00:03:15.161> know,<00:03:15.436> do<00:03:15.711> we<00:03:15.987> just<00:03:16.262> kind<00:03:16.537> of<00:03:16.812> hold<00:03:17.088> for<00:03:17.363> a<00:03:17.638> little<00:03:17.913> bit<00:03:18.189> and<00:03:18.464> wait<00:03:18.739> for<00:03:19.014> the<00:03:19.290> dust<00:03:19.565> to<00:03:19.840> settle. 00:03:20.840 --> 00:03:29.160 Um,<00:03:21.560> but<00:03:22.280> for<00:03:22.519> at<00:03:22.640> least<00:03:23.040> like,<00:03:24.040> you<00:03:24.160> know,<00:03:24.280> since<00:03:24.720> February<00:03:25.239> really,<00:03:25.880> I<00:03:25.920> think<00:03:26.400> most<00:03:27.600> firms<00:03:28.120> have,<00:03:28.920> have 00:03:29.160 --> 00:03:37.840 slowed<00:03:29.560> things<00:03:29.880> down<00:03:30.200> materially<00:03:31.120> to<00:03:31.280> wait<00:03:31.519> until<00:03:31.800> there's<00:03:33.000> a<00:03:33.080> little<00:03:33.280> bit<00:03:33.480> more<00:03:33.720> of<00:03:33.840> a,<00:03:34.800> a<00:03:34.880> calm<00:03:35.400> or,<00:03:35.760> or<00:03:35.920> a<00:03:35.959> little<00:03:36.160> bit<00:03:36.360> more<00:03:36.600> of<00:03:36.760> a,<00:03:37.440> yeah, 00:03:37.840 --> 00:03:41.440 more<00:03:38.040> conviction<00:03:38.720> on<00:03:39.000> which<00:03:39.200> direction<00:03:39.560> they<00:03:39.680> want<00:03:39.840> to<00:03:39.880> take<00:03:40.080> the<00:03:40.160> firm. 00:03:41.440 --> 00:03:47.720 <00:03:41.600> Yeah,<00:03:41.800> does<00:03:41.920> it<00:03:42.160> make<00:03:42.519> sense<00:03:42.680> to<00:03:42.840> you<00:03:43.000> that<00:03:43.120> the<00:03:43.320> term<00:03:43.560> SaaS-pocalypse<00:03:44.120> is<00:03:44.239> being<00:03:45.120> thrown<00:03:45.360> around<00:03:45.880> and<00:03:46.040> some<00:03:46.160> of<00:03:46.239> these<00:03:46.400> companies<00:03:46.760> that<00:03:46.880> are<00:03:46.959> public<00:03:47.480> that<00:03:47.600> are 00:03:47.720 --> 00:03:51.920 SaaS<00:03:47.959> companies<00:03:48.360> and<00:03:48.440> for<00:03:48.560> those<00:03:48.800> listening<00:03:49.160> that<00:03:49.320> means<00:03:49.560> software<00:03:50.160> as<00:03:50.320> a<00:03:50.360> service<00:03:50.800> if<00:03:50.920> you<00:03:50.959> don't<00:03:51.160> know. 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it. 00:08:13.240 --> 00:08:18.840 They've<00:08:13.440> shown<00:08:13.760> traction.<00:08:14.320> They<00:08:14.480> have<00:08:14.720> customers.<00:08:15.400> They<00:08:15.560> have<00:08:16.240> ARR<00:08:16.919> as<00:08:17.040> you're,<00:08:17.280> as<00:08:17.440> you<00:08:17.560> were<00:08:17.640> saying. 00:08:18.840 --> 00:08:23.040 Um,<00:08:19.212> but<00:08:19.584> still<00:08:19.956> it,<00:08:20.328> you<00:08:20.700> know,<00:08:21.072> everybody<00:08:21.444> talks<00:08:21.816> about<00:08:22.188> the<00:08:22.560> SaaS-pocalypse. 00:08:23.040 --> 00:08:31.320 There<00:08:23.120> might<00:08:23.280> be<00:08:23.400> a<00:08:23.440> bit<00:08:23.600> of<00:08:23.680> a<00:08:23.760> VC<00:08:24.840> apocalypse,<00:08:25.760> you<00:08:25.880> know,<00:08:26.280> given<00:08:26.880> AI<00:08:27.240> might<00:08:27.520> make<00:08:27.720> it<00:08:27.840> a<00:08:27.880> little<00:08:28.120> bit,<00:08:29.040> um,<00:08:29.680> easier<00:08:30.360> to<00:08:30.520> 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a<00:30:21.960> mentor<00:30:22.480> and<00:30:22.840> and<00:30:23.000> I<00:30:23.080> guess<00:30:23.400> now<00:30:24.120> uh<00:30:24.200> even<00:30:24.440> bigger<00:30:24.640> part<00:30:24.800> of<00:30:24.840> my<00:30:24.960> life. 00:30:25.880 --> 00:30:34.760 Um,<00:30:26.280> so<00:30:26.480> those<00:30:26.800> three<00:30:27.840> people<00:30:28.280> outside<00:30:28.600> of<00:30:28.680> my<00:30:28.760> parents<00:30:29.400> uh<00:30:29.640> they<00:30:30.240> gave<00:30:30.400> me<00:30:30.520> every<00:30:30.880> opportunity<00:30:31.520> that<00:30:32.160> I<00:30:32.280> couldn't<00:30:32.520> expect<00:30:33.560> and<00:30:34.400> uh 00:30:34.760 --> 00:30:38.120 and<00:30:34.920> so<00:30:36.560> those<00:30:36.720> are<00:30:36.760> the<00:30:36.880> three. 00:30:38.120 --> 00:30:41.320 Sheldon,<00:30:38.720> thank<00:30:38.960> you<00:30:39.040> so<00:30:39.200> much.<00:30:40.240> Yeah. 00:30:41.320 --> 00:30:43.760 Thanks<00:30:41.520> for<00:30:41.640> your<00:30:41.760> time. ``` ### A Place for Mom CEO Tatyana Zlotsky: Solving America’s growing caregiving crisis URL: https://www.ceo.com/episodes/a-place-for-mom-ceo-tatyana-zlotsky-solving-america-s-growing-caregiving-crisis/ Last updated: 2026-08-20T00:39:43.000Z # Tatyana Zlotsky refuses to shorten the call This year, for the first time, baby boomers are turning 80. About 40 million Americans are caring for an aging family member. Nearly 70 percent are women, most of them adult daughters. The average family spends more than $300,000 over the course of a loved one's care, and spends it while figuring out healthcare, housing, and money all at once, usually with no experience in any of it. "I often say they become the second patient," Tatyana Zlotsky said on the CEO.com Podcast. "They're giving so much of themselves to caring for someone else." Zlotsky has been the second patient. Her grandparents immigrated to the United States in their 60s, an age when a new country does not get easier. She helped care for them for 15 years and calls it one of the great joys of her life. It also showed her how broken parts of the healthcare system are. "Despite all the challenges they faced, my grandparents remained incredibly grateful every day," she told CEO.com. "That perspective has stayed with me." It is also how she ended up running [A Place for Mom](https://www.aplaceformom.com/about/leadership/tatyana-zlotsky?ref=ceo.com), the senior care advisory service that connects families with [more than 15,000 senior living communities and home care providers](https://www.businesswire.com/news/home/20260616891598/en/A-Place-for-Mom-Names-Nidhin-George-as-Chief-Product-Officer?ref=ceo.com) across the United States. The service costs families nothing; providers in the network pay for it. Advisors work out what kind of care a family needs, at home or outside it, and help them find it. Zlotsky was [appointed CEO](https://www.businesswire.com/news/home/20240415134626/en/Tatyana-Zlotsky-to-Become-Chief-Executive-Officer-of-A-Place-for-Mom?ref=ceo.com) in May 2024, a planned succession from Larry Kutscher, who moved to chairman of the board. She had joined in 2019 as chief marketing officer after a decade at American Express, a couple of technology startups before that, and an engineering subsidiary of Emerson Electric before that. She came to the United States as an immigrant herself, without the language, without knowing anyone. "Uncertainty becomes familiar," she said. It shows in how she runs the company. On decisions, she cites Colin Powell: under 40 percent of the information is a guess; over 70 percent means you waited too long. "In many cases, indecision is a greater risk than making the wrong decision," she said. After becoming CEO, she rewrote the company's values, five of them, including We Do Hard Things, borrowed in spirit from Ben Horowitz. On AI, she is blunt about where it belongs. The average call between an advisor and a family runs past 20 minutes, and the company refuses to shorten it. The machines work behind the scenes instead: collections, marketing, sales operations, the administrative load that keeps advisors off the phone. In November 2025, the company [relaunched its brand and go-to-market strategy](https://www.aplaceformom.com/about/news-and-press-releases/a-place-for-mom-reimagines-brand-and-go-to-market-strategy-to-lead-in-the-new-caregiver-era?ref=ceo.com) for families who now find care through AI, and in June it [hired Nidhin George](https://www.businesswire.com/news/home/20260616891598/en/A-Place-for-Mom-Names-Nidhin-George-as-Chief-Product-Officer?ref=ceo.com), nearly 17 years at Amazon and later a product leader at Grubhub, as chief product officer. At CEO.com, we believe the chances one gives are just as important as the chances one takes. Asked who gave her one, Zlotsky named Tara Walpert Levy, Julie Fiegenbaum, and David Rabkin, and then Kutscher, who did more than believe she could be CEO. He spent years preparing her for it. "Today, I try to do the same thing for others," she said. "See potential in people before they see it in themselves and give them opportunities that stretch them beyond what they think they're capable of." ```chapters 00:00:00 Introduction and Career Journey 00:01:11 Mission of A Place for Mom 00:02:44 Caregiving Crisis and Statistics 00:03:55 A Day in the Life of a CEO 00:05:06 Optimism and AI 00:07:04 Leadership and Decision Making 00:09:05 Company Values 00:10:18 Balancing Efficiency and Compassion 00:13:02 Inspirational Leaders 00:14:42 Managing Company Culture 00:17:04 Future of Senior Living Industry 00:19:05 Influence of Immigrant Experience 00:20:38 Acknowledging Mentors and Supporters 00:22:07 Conclusion and Gratitude ``` ```vtt WEBVTT 00:00:00.000 --> 00:00:02.320 Tatiana,<00:00:00.480> thank<00:00:00.680> you<00:00:00.800> so<00:00:00.920> much<00:00:01.160> for<00:00:01.280> coming<00:00:01.560> on<00:00:01.640> the<00:00:01.760> show. 00:00:02.320 --> 00:00:05.480 You<00:00:02.480> are<00:00:02.600> the<00:00:02.800> 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called<00:02:59.920> the<00:03:00.000> boomers<00:03:00.440> for<00:03:00.920> a<00:03:01.000> reason,<00:03:01.440> right? 00:03:01.680 --> 00:03:05.800 Like<00:03:01.840> this<00:03:02.200> is<00:03:02.280> a<00:03:02.360> very<00:03:02.600> big<00:03:02.800> generation.<00:03:03.400> Can<00:03:03.519> you<00:03:03.560> give<00:03:03.720> us<00:03:03.840> a<00:03:03.880> sense<00:03:04.160> for<00:03:04.239> the<00:03:04.360> scale<00:03:04.720> of<00:03:04.800> that? 00:03:05.800 --> 00:03:15.280 <00:03:06.271> Yeah,<00:03:06.741> no<00:03:07.212> absolutely.<00:03:07.682> They're<00:03:08.153> you<00:03:08.624> know,<00:03:09.094> right<00:03:09.565> now<00:03:10.035> we<00:03:10.506> have<00:03:10.976> about<00:03:11.447> 40<00:03:11.918> million<00:03:12.388> caregivers<00:03:12.859> in<00:03:13.329> the<00:03:13.800> US 00:03:15.280 --> 00:03:18.840 and<00:03:15.440> those<00:03:15.720> are<00:03:15.880> family<00:03:16.320> members,<00:03:17.080> you<00:03:17.200> know,<00:03:17.320> as<00:03:17.480> I<00:03:17.519> mentioned<00:03:17.880> earlier. 00:03:18.840 --> 00:03:25.640 And<00:03:19.160> so<00:03:19.600> those<00:03:20.040> folks<00:03:20.400> on<00:03:20.600> average<00:03:21.320> are<00:03:21.519> spending<00:03:22.400> north<00:03:22.880> of<00:03:23.040> $300,000 00:03:25.640 --> 00:03:32.360 during<00:03:26.640> this<00:03:26.880> caregiving<00:03:27.400> journey<00:03:28.200> time<00:03:29.720> providing<00:03:30.320> the<00:03:30.440> right<00:03:30.680> care. 00:03:32.360 --> 00:03:41.400 And<00:03:32.560> as<00:03:32.760> I<00:03:32.880> said,<00:03:33.480> you<00:03:33.560> know,<00:03:33.680> that<00:03:33.880> journey's<00:03:34.440> filled<00:03:34.800> with<00:03:35.120> lots<00:03:35.440> of<00:03:35.560> obstacles<00:03:36.400> and<00:03:36.600> lots<00:03:37.000> of<00:03:37.840> new<00:03:38.160> decisions<00:03:38.760> that<00:03:38.920> they<00:03:39.040> don't<00:03:39.200> have<00:03:39.320> any<00:03:39.480> experience<00:03:40.120> making<00:03:40.680> beforehand. 00:03:41.400 --> 00:03:46.840 And<00:03:41.560> so<00:03:41.720> as<00:03:41.880> the<00:03:42.000> boomers<00:03:42.440> age,<00:03:43.120> we<00:03:43.280> expect<00:03:43.680> those<00:03:43.880> numbers<00:03:44.239> to<00:03:44.360> continue<00:03:44.840> growing<00:03:45.320> exponentially. 00:03:46.840 --> 00:03:51.760 Um,<00:03:47.519> and<00:03:48.000> you<00:03:48.080> know,<00:03:48.239> that<00:03:48.600> means<00:03:48.800> just<00:03:48.959> the<00:03:49.040> crisis<00:03:49.480> will<00:03:49.720> will<00:03:49.880> only<00:03:50.120> get<00:03:50.320> worse. 00:03:51.760 --> 00:03:55.200 <00:03:51.927> What<00:03:52.095> does<00:03:52.262> a<00:03:52.429> typical<00:03:52.596> day<00:03:52.764> look<00:03:52.931> like<00:03:53.098> for<00:03:53.265> you<00:03:53.433> as<00:03:53.600> CEO? 00:03:55.200 --> 00:04:00.920 <00:03:55.484> Hm.<00:03:55.769> Um<00:03:56.053> so,<00:03:56.338> you<00:03:56.622> 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--> 00:04:33.919 Um<00:04:31.000> another<00:04:31.360> 20%<00:04:32.280> with<00:04:32.480> customers. 00:04:33.919 --> 00:04:41.000 Um<00:04:34.360> and<00:04:34.520> then<00:04:34.640> the<00:04:34.720> balance<00:04:35.120> of<00:04:35.200> the<00:04:35.320> time,<00:04:35.720> you<00:04:35.840> know,<00:04:36.440> uh<00:04:36.520> with<00:04:36.800> with<00:04:37.200> other<00:04:37.440> folks<00:04:37.800> in<00:04:37.919> the<00:04:37.960> industry<00:04:38.520> and<00:04:38.680> with<00:04:38.919> within<00:04:39.160> the<00:04:39.240> company,<00:04:39.960> uh<00:04:40.080> board<00:04:40.280> members,<00:04:40.680> and<00:04:40.800> so 00:04:41.000 --> 00:04:43.200 on.<00:04:41.720> Um<00:04:42.000> so,<00:04:42.120> it's<00:04:42.200> kind<00:04:42.360> of<00:04:42.440> an<00:04:42.480> important<00:04:42.840> split. 00:04:43.200 --> 00:04:49.800 I<00:04:43.280> really<00:04:43.600> think<00:04:43.840> that<00:04:44.120> as<00:04:44.280> a<00:04:44.320> CEO,<00:04:44.880> 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thinking<00:05:00.840> about<00:05:01.160> it?<00:05:01.320> How<00:05:01.400> are<00:05:01.480> you<00:05:01.640> implementing<00:05:02.240> it? 00:05:02.480 --> 00:05:05.960 How<00:05:02.766> often<00:05:03.051> are<00:05:03.337> you<00:05:03.623> using<00:05:03.909> it?<00:05:04.194> <00:05:04.480> Yeah. 00:05:05.960 --> 00:05:09.000 So,<00:05:06.360> I'm<00:05:06.560> an<00:05:06.680> eternal<00:05:07.080> optimist<00:05:07.680> in<00:05:07.800> general. 00:05:09.000 --> 00:05:17.720 Um<00:05:09.600> and<00:05:09.840> what<00:05:09.960> I<00:05:10.040> would<00:05:10.200> say<00:05:10.360> is,<00:05:10.640> you<00:05:10.760> know,<00:05:10.880> I<00:05:10.960> feel<00:05:11.200> very<00:05:11.560> optimistic<00:05:12.280> about<00:05:12.640> the<00:05:12.720> future<00:05:13.080> of<00:05:13.200> AI<00:05:13.600> and<00:05:13.800> what<00:05:13.960> it<00:05:14.120> will<00:05:14.680> provide<00:05:15.320> for<00:05:15.800> us<00:05:16.040> as<00:05:16.200> a<00:05:16.240> society. 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Political<00:05:36.301> instability,<00:05:36.723> uh<00:05:37.144> inflation,<00:05:37.565> um<00:05:37.987> high<00:05:38.408> interest<00:05:38.829> rates,<00:05:39.251> and<00:05:39.672> and<00:05:40.093> still<00:05:40.515> we<00:05:40.936> have<00:05:41.357> this<00:05:41.779> great<00:05:42.200> performance. 00:05:43.120 --> 00:05:48.800 And<00:05:43.240> what<00:05:43.400> you<00:05:43.560> can<00:05:43.720> see<00:05:43.880> underneath<00:05:44.440> that<00:05:44.760> is<00:05:45.480> majority<00:05:46.040> of<00:05:46.120> that<00:05:46.320> is<00:05:46.440> really<00:05:46.760> being<00:05:47.000> fueled<00:05:47.400> by<00:05:47.600> technology. 00:05:48.800 --> 00:05:53.120 Uh<00:05:49.280> AI<00:05:49.520> infrastructure<00:05:50.560> and<00:05:50.800> and<00:05:51.040> sort<00:05:51.200> of<00:05:51.320> everything<00:05:51.640> else<00:05:51.840> that<00:05:51.960> goes<00:05:52.160> into<00:05:52.360> that. 00:05:53.120 --> 00:05:57.000 Um<00:05:53.800> so<00:05:53.960> I<00:05:54.040> believe<00:05:54.400> that<00:05:54.600> financially<00:05:55.200> the<00:05:55.320> opportunity<00:05:55.960> is<00:05:56.120> quite<00:05:56.360> great. 00:05:57.000 --> 00:06:05.400 Um<00:05:57.314> and<00:05:57.628> for<00:05:57.942> people,<00:05:58.255> you<00:05:58.569> know,<00:05:58.883> I<00:05:59.197> think<00:05:59.511> it's<00:05:59.825> going<00:06:00.138> to<00:06:00.452> be<00:06:00.766> a<00:06:01.080> time<00:06:01.394> of<00:06:01.708> transition<00:06:02.022> like<00:06:02.335> any<00:06:02.649> other<00:06:02.963> big<00:06:03.277> transformation,<00:06:03.591> but<00:06:03.905> in<00:06:04.218> the<00:06:04.532> end<00:06:04.846> um<00:06:05.160> my 00:06:05.400 --> 00:06:13.640 hope<00:06:05.720> is<00:06:05.840> that<00:06:06.080> we<00:06:06.240> will<00:06:06.400> come<00:06:06.600> out<00:06:06.880> more<00:06:07.720> evolved,<00:06:08.440> focused<00:06:08.960> on<00:06:09.680> better<00:06:09.960> problem-solving,<00:06:11.360> being<00:06:11.640> more<00:06:11.880> efficient<00:06:12.360> with<00:06:12.520> our<00:06:12.640> times. 00:06:13.640 --> 00:06:22.240 And<00:06:13.760> I<00:06:13.840> certainly<00:06:14.280> hope<00:06:14.520> that<00:06:14.760> really<00:06:15.000> important<00:06:16.040> tenets<00:06:16.520> of<00:06:16.720> our<00:06:16.960> society<00:06:17.560> such<00:06:17.800> as<00:06:17.919> health<00:06:18.200> care,<00:06:18.880> education<00:06:19.800> are<00:06:19.960> much<00:06:20.200> improved. 00:06:22.240 --> 00:06:29.480 <00:06:22.528> Yeah,<00:06:22.816> right.<00:06:23.104> Like<00:06:23.392> and<00:06:23.680> you<00:06:23.968> know,<00:06:24.256> there's<00:06:24.544> there's<00:06:24.832> kind<00:06:25.120> of<00:06:25.408> like<00:06:25.696> this<00:06:25.984> existential<00:06:26.272> crisis<00:06:26.560> that<00:06:26.848> you're<00:06:27.136> seeing<00:06:27.424> throughout<00:06:27.712> the<00:06:28.000> country. 00:06:29.480 --> 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a<00:06:43.800> failure<00:06:44.160> of<00:06:44.280> like<00:06:44.480> explaining<00:06:45.120> in<00:06:45.240> the<00:06:45.320> same<00:06:45.560> way<00:06:45.720> that<00:06:45.840> you<00:06:45.919> just<00:06:46.120> explained<00:06:46.600> like<00:06:47.120> kind<00:06:47.320> of<00:06:47.400> the<00:06:47.520> opportunities<00:06:48.160> that<00:06:48.280> are<00:06:48.360> going<00:06:48.520> to 00:06:48.600 --> 00:06:51.840 exist<00:06:49.080> out<00:06:49.200> of<00:06:49.280> this.<00:06:50.120> So<00:06:50.240> I'd<00:06:50.360> love<00:06:50.480> to<00:06:50.560> hear<00:06:50.680> like<00:06:51.080> how<00:06:51.200> do<00:06:51.320> you<00:06:51.480> lead? 00:06:51.840 --> 00:06:55.919 Give<00:06:52.000> us<00:06:52.120> a<00:06:52.160> sense<00:06:52.440> for<00:06:52.640> like<00:06:52.880> your<00:06:53.000> great<00:06:53.840> uh<00:06:53.960> leadership<00:06:54.480> qualities<00:06:54.919> that<00:06:55.040> you've<00:06:55.200> learned<00:06:55.480> over<00:06:55.640> the<00:06:55.720> years. 00:06:55.919 --> 00:07:00.760 Like<00:06:56.080> you<00:06:56.160> said,<00:06:56.320> you<00:06:56.400> have<00:06:56.720> had<00:06:56.960> a<00:06:57.000> very<00:06:57.240> impressive<00:06:57.720> career<00:06:58.680> before<00:06:59.040> coming<00:06:59.480> here. 00:07:00.760 --> 00:07:04.720 Um<00:07:00.919> what<00:07:01.080> did<00:07:01.200> you<00:07:01.320> learn<00:07:01.480> about<00:07:01.720> leadership<00:07:02.200> that<00:07:02.360> you've<00:07:02.480> transferred<00:07:02.919> over<00:07:03.120> here? 00:07:04.720 --> 00:07:13.240 <00:07:05.080> Yeah,<00:07:05.440> look,<00:07:05.800> I<00:07:06.160> think<00:07:06.520> that<00:07:06.880> the<00:07:07.240> most<00:07:07.600> important<00:07:07.960> thing<00:07:08.320> right<00:07:08.680> now<00:07:09.040> given<00:07:09.400> the<00:07:09.760> uncertainty<00:07:10.120> and<00:07:10.480> and<00:07:10.840> the<00:07:11.200> different<00:07:11.560> views<00:07:11.920> on<00:07:12.280> what's<00:07:12.640> happening<00:07:13.000> with 00:07:13.240 --> 00:07:21.600 AI<00:07:13.680> and<00:07:13.760> just<00:07:13.919> more<00:07:14.080> broadly<00:07:14.520> the<00:07:14.640> world<00:07:14.880> at<00:07:15.000> large,<00:07:16.160> uh<00:07:16.440> the<00:07:16.560> most<00:07:16.760> important<00:07:17.240> thing<00:07:18.360> leaders<00:07:18.880> need<00:07:19.080> to<00:07:19.200> do<00:07:19.480> is<00:07:19.600> actually<00:07:19.919> make<00:07:20.120> decisions. 00:07:21.600 --> 00:07:25.400 Uh<00:07:21.800> that<00:07:21.960> was<00:07:22.120> always<00:07:22.440> true.<00:07:23.280> Um<00:07:23.400> but<00:07:23.520> I<00:07:23.560> think<00:07:23.760> it's<00:07:23.880> even<00:07:24.080> more<00:07:24.240> important<00:07:24.680> in<00:07:24.800> today's<00:07:25.160> world. 00:07:25.400 --> 00:07:31.400 And<00:07:25.480> so<00:07:25.640> what<00:07:25.720> does<00:07:25.840> that<00:07:26.000> look<00:07:26.200> like?<00:07:26.440> 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it<00:08:13.880> can<00:08:14.160> seem<00:08:14.440> like<00:08:14.560> a<00:08:14.600> lot<00:08:14.800> of<00:08:14.919> swirl<00:08:15.919> and<00:08:16.480> with<00:08:16.680> that<00:08:17.000> comes<00:08:17.640> fear. 00:08:18.600 --> 00:08:23.080 Um<00:08:19.240> additionally,<00:08:19.919> you<00:08:20.040> know,<00:08:20.160> it's<00:08:20.280> really<00:08:20.480> about<00:08:20.680> leveling<00:08:21.080> up<00:08:21.240> the<00:08:21.360> rest<00:08:21.640> of<00:08:21.720> the<00:08:21.800> leadership<00:08:22.320> organization. 00:08:23.080 --> 00:08:26.800 You<00:08:23.160> know,<00:08:23.280> I'm<00:08:23.400> one<00:08:23.560> person.<00:08:24.040> We<00:08:24.200> have<00:08:24.560> uh<00:08:24.680> nearly<00:08:25.000> a<00:08:25.040> thousand<00:08:25.360> people<00:08:25.640> in<00:08:25.720> the<00:08:25.800> company. 00:08:26.800 --> 00:08:35.360 So<00:08:27.000> I<00:08:27.120> alone<00:08:27.440> can't<00:08:27.680> do<00:08:27.800> much.<00:08:28.800> 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probably<00:09:01.839> the<00:09:01.960> three<00:09:02.200> important<00:09:02.600> tenets. 00:09:03.880 --> 00:09:08.120 <00:09:04.115> What<00:09:04.350> are<00:09:04.585> your<00:09:04.820> company's<00:09:05.055> values?<00:09:05.290> <00:09:05.525> Yeah,<00:09:05.760> so<00:09:05.995> we<00:09:06.230> have<00:09:06.465> uh<00:09:06.700> thank<00:09:06.935> you<00:09:07.170> for<00:09:07.405> asking<00:09:07.640> that. 00:09:08.120 --> 00:09:16.560 So<00:09:08.240> we've<00:09:08.400> got<00:09:08.600> five<00:09:08.920> values.<00:09:09.600> Um<00:09:09.800> the<00:09:09.920> first<00:09:10.240> one<00:09:10.360> is<00:09:10.480> mission<00:09:10.800> over<00:09:11.000> me,<00:09:12.000> which<00:09:12.240> you<00:09:12.280> would<00:09:12.400> imagine<00:09:12.839> in<00:09:13.000> in<00:09:13.200> our<00:09:13.839> uh<00:09:13.920> in<00:09:14.040> our<00:09:14.160> line<00:09:14.400> of<00:09:14.480> business<00:09:15.520> uh<00:09:15.760> is<00:09:15.920> critical. 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<00:10:47.273> Yeah,<00:10:47.626> because<00:10:47.979> the<00:10:48.332> business<00:10:48.685> that<00:10:49.038> we're<00:10:49.391> in,<00:10:49.744> um<00:10:50.096> we<00:10:50.449> really<00:10:50.802> prioritize<00:10:51.155> the<00:10:51.508> customer<00:10:51.861> experience<00:10:52.214> first<00:10:52.567> and<00:10:52.920> foremost. 00:10:54.280 --> 00:10:59.600 Um<00:10:54.839> our<00:10:55.120> average<00:10:55.640> length<00:10:56.000> of<00:10:56.120> call<00:10:56.600> time<00:10:57.160> with<00:10:57.360> a<00:10:57.440> family<00:10:58.200> is<00:10:58.480> north<00:10:58.760> of<00:10:58.880> 20<00:10:59.160> minutes. 00:10:59.600 --> 00:11:08.040 So,<00:11:00.160> that's<00:11:00.400> pretty<00:11:00.680> unusual.<00:11:02.200> Um<00:11:02.440> but<00:11:02.920> also<00:11:03.480> intuitively<00:11:05.040> make<00:11:05.280> sense<00:11:05.680> because<00:11:06.120> you're<00:11:06.280> dealing<00:11:06.640> with<00:11:06.800> such<00:11:07.000> an<00:11:07.080> 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actually<00:21:35.320> supported<00:21:35.880> me,<00:21:36.560> taught 00:21:36.840 --> 00:21:45.360 me,<00:21:37.320> um,<00:21:37.960> and<00:21:38.360> created<00:21:38.760> a<00:21:38.800> thoughtful<00:21:39.200> succession<00:21:39.680> plan<00:21:40.040> for<00:21:40.200> me<00:21:40.720> to<00:21:40.880> take<00:21:41.280> on<00:21:41.480> this<00:21:41.760> role,<00:21:42.320> um,<00:21:42.840> you<00:21:42.920> know,<00:21:43.560> during,<00:21:44.040> uh,<00:21:45.320> a 00:21:45.360 --> 00:21:53.840 meaningful<00:21:45.760> amount<00:21:45.960> of<00:21:46.080> time.<00:21:46.920> And<00:21:47.160> so,<00:21:47.400> without<00:21:47.720> those<00:21:47.920> people<00:21:48.800> and<00:21:48.920> many<00:21:49.160> others,<00:21:49.800> um,<00:21:50.680> you<00:21:50.800> know,<00:21:50.880> my,<00:21:51.160> my,<00:21:51.480> my<00:21:51.680> path<00:21:52.000> wouldn't<00:21:52.240> be<00:21:52.360> the<00:21:52.520> same<00:21:52.960> and,<00:21:53.680> and 00:21:53.840 --> 00:21:57.680 I<00:21:54.040> try<00:21:54.360> to<00:21:55.040> do<00:21:55.240> the<00:21:55.360> same<00:21:55.680> for,<00:21:56.080> for<00:21:56.200> the<00:21:56.320> folks<00:21:56.600> that<00:21:56.760> work<00:21:56.960> for<00:21:57.040> me. 00:21:57.680 --> 00:22:06.080 See<00:21:57.880> the<00:21:58.000> potential<00:21:58.480> in<00:21:58.600> others<00:21:58.880> before<00:21:59.240> they<00:21:59.400> see<00:21:59.560> it<00:21:59.680> in<00:21:59.760> themselves<00:22:00.320> and<00:22:01.120> almost<00:22:01.560> to<00:22:01.680> a<00:22:01.760> fault,<00:22:02.160> I<00:22:02.200> would<00:22:02.400> say,<00:22:02.600> try<00:22:02.840> to<00:22:02.960> stretch<00:22:03.800> and<00:22:03.960> giving<00:22:04.240> them<00:22:04.400> more<00:22:04.600> responsibility, 00:22:06.080 --> 00:22:09.600 um,<00:22:06.840> and<00:22:07.040> bigger<00:22:07.320> roles<00:22:07.680> than<00:22:07.840> they're<00:22:08.000> ready<00:22:08.240> for. 00:22:09.600 --> 00:22:13.680 Tatiana,<00:22:10.080> thank<00:22:10.280> you<00:22:10.360> so<00:22:10.520> much<00:22:10.800> for<00:22:10.920> coming<00:22:11.280> on<00:22:11.800> and<00:22:12.360> thanks<00:22:12.680> for<00:22:12.800> what<00:22:12.920> you<00:22:13.000> do<00:22:13.160> for<00:22:13.280> a<00:22:13.320> living. 00:22:13.680 --> 00:22:16.680 It<00:22:13.880> really<00:22:14.120> makes<00:22:14.320> a<00:22:14.400> huge<00:22:14.680> impact. ``` ### Prowler Founder & CEO Toni De La Fuente: Why AI security is really cloud security URL: https://www.ceo.com/episodes/prowler-founder-ceo-toni-de-la-fuente-why-ai-security-is-really-cloud-security/ Last updated: 2026-08-20T00:54:29.000Z # Prowler's Toni De La Fuente plans in weeks, not months Ten years ago, Toni De La Fuente needed a way to check whether his cloud environments were secure. He was working across AWS, Azure, and Google Cloud, and nothing on the market did what he wanted. So he wrote it himself. "I wanted to learn by doing," he told the CEO.com Podcast. "I wanted to understand cloud security at a deeper level, and writing the tool seemed like the best way to do that." He named it Prowler [after the first song on Iron Maiden's first album](https://x.com/toniblyx/status/1250150849734680578?ref=ceo.com), and kept the habit as the project grew. [Version 3 was Piece of Mind. Version 4 was The Trooper.](https://blyx.com/?ref=ceo.com) Today Prowler is [the most widely used open-source cloud security platform in the world](https://github.com/prowler-cloud/prowler?ref=ceo.com), and De La Fuente says downloads are approaching 50 million. For years it was a second job. He worked as a [senior security engineer at AWS](https://blyx.com/bio/?ref=ceo.com) by day and maintained Prowler at night and on weekends, reviewing issues, answering feature requests, and supporting a community that kept growing whether he had time for it or not. Investors started calling before he had a pitch. "When you build a successful open-source project in a market with huge opportunities, like cloud security, investors start paying attention," he said. "Eventually I realized I needed to choose one path, so I decided to go all-in on Prowler." The company raised [$6 million in seed funding led by Decibel](https://www.businesswire.com/news/home/20240226303311/en/Prowler-Secures-%246-Million-in-Seed-Funding-to-Expand-Open-Cloud-Security-Offering?ref=ceo.com) in early 2024, then [extended the round to $12.5 million](https://www.prweb.com/releases/prowler-closes-12-5-million-seed-financing-to-drive-the-future-of-open-cloud-security-302418052.html?ref=ceo.com). His argument on the show starts with a shift in how software gets described. "Years ago people would say, 'I'm building an application for Windows' or 'I'm building for Linux,'" he said. "Now people say, 'I'm building for the cloud.' The cloud providers have effectively become the new operating systems." Every application is now a pile of components, databases, APIs, storage, and increasingly AI models, and each one has its own security requirements. Secure code on a misconfigured cloud is not a secure system. "At the end of the day, AI security is increasingly becoming cloud security." Humans are no longer Prowler's only users. The company now [calls itself the Agentic Cloud Defender](https://github.com/prowler-cloud/prowler?ref=ceo.com) because AI agents run it too. "Cloud security contains a lot of deterministic information," De La Fuente said. "You can't simply ask an AI model, 'What's wrong with my cloud?' The AI needs context." That context lives in [Prowler Hub](https://hub.prowler.com/?ref=ceo.com), a public library of security checks, compliance frameworks, and attack path queries. He compares it to Terraform Registry or Docker Hub. Much of what fills it now comes from outside the company: community members have contributed support for Microsoft 365, Google Cloud, Cloudflare, GitHub, and other services the original tool never touched. The community that built Prowler does not pay for it, and cloud infrastructure is not free. So the open-source core stays free while the company charges for alerts, bulk provisioning, centralized findings management, single sign-on, and advanced AI features. "People understand that if they want the project to continue growing, the company needs a way to generate revenue," he said. After 27 years in cybersecurity, De La Fuente calls running the company the hardest thing he has ever done. Prowler is fully remote, with more than 20 people across five time zones, a structure nobody designed. The first engineer he hired was already remote. The second lived in another city. "At this point, I don't think we could change it even if we wanted to." Planning horizons have collapsed along the way. "The other day someone suggested planning a feature rollout over the next two months. I said, 'Two months? Let's plan for two weeks.' The pace of change is just too fast." He grew up in a small town in southern Spain, and he tells his own story as a series of yeses. A chance to work with computers at 19, yes. Madrid, yes. The United States, yes. He is saying yes again, moving to San Francisco to be near the partners and customers concentrated there. "Being a CEO means constantly making decisions without immediately knowing whether they're right or wrong," he said. "Moving to San Francisco is one of those decisions." The one he seems surest about is the size of the market. "Ultimately, we want Prowler to be used by every organization operating in the cloud," he said. "Which is basically every organization." ```chapters 00:00:00 Introduction and Background of Toni 00:00:20 Founding of Prowler 00:01:25 Transition from Open Source Project to Company 00:02:52 Importance of Security in the Age of AI 00:05:21 Opportunities in Cloud Security 00:07:24 Concerns about Security Vulnerabilities in Old Code 00:10:01 Growth and Adoption of Prowler 00:12:02 A Day in the Life of a CEO 00:13:41 Decision to Go Fully Remote 00:15:02 Moving to San Francisco 00:16:41 Reading Recommendations for CEOs 00:19:44 Leadership Lessons and Challenges 00:21:07 Macroeconomic Environment and Planning 00:23:52 Funding and Venture Capital 00:26:10 Balancing Community and Company Needs 00:28:33 Community Reaction to Paid Features 00:30:03 Future Growth Potential of Prowler 00:31:28 Competitors in the Cloud Security Space 00:34:39 Thoughts on Quantum Computing 00:35:31 Reflecting on Opportunities and Support 00:37:12 Closing Remarks and Gratitude ``` ```vtt WEBVTT 00:00:00.000 --> 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was 00:02:27.040 --> 00:02:35.360 working<00:02:27.440> a<00:02:27.520> lot<00:02:28.000> of<00:02:28.240> hours<00:02:28.680> for<00:02:29.040> AWS<00:02:29.560> by<00:02:29.680> that<00:02:29.880> time<00:02:30.959> on<00:02:31.200> my<00:02:31.360> day<00:02:31.560> job,<00:02:31.959> but<00:02:32.160> also<00:02:32.720> during<00:02:33.040> my<00:02:34.200> uh<00:02:34.600> own<00:02:35.280> uh 00:02:35.360 --> 00:02:43.760 own<00:02:35.560> time<00:02:36.160> I<00:02:36.360> have<00:02:36.680> to<00:02:36.959> work<00:02:37.360> on<00:02:37.520> the<00:02:37.640> project<00:02:38.520> because<00:02:38.920> I<00:02:39.000> have<00:02:39.320> issues<00:02:39.920> opened,<00:02:40.800> I<00:02:40.920> have<00:02:41.200> features<00:02:42.120> uh<00:02:42.200> requests<00:02:43.480> um 00:02:43.760 --> 00:02:52.200 and<00:02:44.120> things<00:02:44.360> like<00:02:44.520> that.<00:02:44.760> So,<00:02:45.640> um<00:02:45.840> at<00:02:45.959> some<00:02:46.080> point<00:02:46.320> 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months, 00:03:03.000 --> 00:03:10.840 let's<00:03:03.200> say,<00:03:03.519> where<00:03:03.720> things<00:03:04.000> like<00:03:04.200> open<00:03:04.519> cloud<00:03:04.959> and<00:03:05.040> these<00:03:05.200> various<00:03:05.600> things<00:03:06.440> have<00:03:06.720> come<00:03:07.040> out<00:03:07.480> where<00:03:07.760> security<00:03:08.239> has<00:03:08.360> become<00:03:08.680> kind<00:03:08.880> of<00:03:08.959> like<00:03:09.120> a<00:03:09.160> major<00:03:09.640> concern<00:03:10.400> as<00:03:10.560> people 00:03:10.840 --> 00:03:14.280 are<00:03:10.959> vibe<00:03:11.320> coding<00:03:11.720> products<00:03:13.080> um<00:03:13.560> and<00:03:13.680> various<00:03:14.000> things. 00:03:14.280 --> 00:03:22.320 Give<00:03:14.440> us<00:03:14.600> a<00:03:14.680> sense<00:03:15.080> for<00:03:15.200> just<00:03:15.440> the<00:03:15.560> importance<00:03:16.200> of<00:03:16.280> security<00:03:16.880> and<00:03:17.000> how<00:03:17.160> people<00:03:17.400> 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software. 00:09:06.480 --> 00:09:12.440 It's<00:09:07.200> is<00:09:07.320> the<00:09:07.400> integration,<00:09:08.040> is<00:09:08.160> the<00:09:08.240> deployment,<00:09:08.839> is<00:09:08.920> the<00:09:09.480> is<00:09:09.600> the<00:09:10.600> QA,<00:09:11.120> is<00:09:11.280> the<00:09:11.400> test. 00:09:12.440 --> 00:09:15.720 Is<00:09:12.720> is<00:09:12.880> the<00:09:13.040> is<00:09:13.360> is<00:09:13.480> running<00:09:13.800> in<00:09:13.920> production<00:09:14.680> with<00:09:14.839> everything<00:09:15.160> around. 00:09:15.720 --> 00:09:21.480 Probably<00:09:15.960> your<00:09:16.120> software<00:09:16.440> is<00:09:16.560> perfect,<00:09:17.280> but<00:09:17.440> it's<00:09:17.640> running<00:09:17.920> on<00:09:18.080> top<00:09:18.320> of<00:09:18.560> a<00:09:19.360> vulnerable<00:09:20.280> firewall. 00:09:21.480 --> 00:09:26.760 Right.<00:09:22.040> Right?<00:09:22.800> So<00:09:24.200> it's<00:09:24.480> not<00:09:24.800> only<00:09:25.040> 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00:20:28.920 --> 00:20:32.880 So<00:20:29.160> effort<00:20:30.360> is<00:20:32.000> key. 00:20:32.880 --> 00:20:41.880 Obsession<00:20:33.640> is<00:20:33.880> key.<00:20:34.800> But<00:20:35.400> if<00:20:35.680> I<00:20:35.800> have<00:20:36.080> to<00:20:36.520> mention<00:20:37.040> something<00:20:37.400> important<00:20:37.840> that<00:20:38.000> I<00:20:38.480> I'm<00:20:38.680> learning,<00:20:39.080> still<00:20:39.360> learning<00:20:39.720> is<00:20:40.000> to<00:20:40.160> listen<00:20:40.520> to<00:20:40.680> everybody<00:20:41.680> and 00:20:41.880 --> 00:20:45.080 to<00:20:42.000> be<00:20:42.280> available<00:20:43.120> all<00:20:43.280> the<00:20:43.400> time. 00:20:45.080 --> 00:20:48.440 We<00:20:45.360> have<00:20:45.720> people<00:20:46.000> in<00:20:46.160> five<00:20:47.160> time<00:20:47.400> zones. 00:20:48.440 --> 00:20:56.400 It's<00:20:48.600> hard<00:20:49.080> because<00:20:49.400> you<00:20:49.480> can<00:20:49.720> start<00:20:50.040> at<00:20:50.240> 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00:26:59.920 --> 00:27:03.840 But<00:27:00.080> you<00:27:00.200> are<00:27:00.360> paying<00:27:00.760> because<00:27:01.040> those<00:27:01.680> services<00:27:02.160> are<00:27:02.280> not<00:27:02.480> free. 00:27:03.840 --> 00:27:12.320 So,<00:27:04.160> to<00:27:04.520> harvest<00:27:05.920> that<00:27:06.200> people,<00:27:06.560> the<00:27:06.680> people<00:27:06.920> that<00:27:07.120> is<00:27:07.440> paying<00:27:07.800> a<00:27:07.880> decent<00:27:08.320> amount<00:27:08.720> of<00:27:08.840> money<00:27:09.160> to<00:27:09.360> their<00:27:09.640> cloud<00:27:10.120> or<00:27:10.280> clouds,<00:27:11.520> to<00:27:11.600> say,<00:27:11.880> "Hey, 00:27:12.320 --> 00:27:16.640 I<00:27:12.480> give<00:27:12.720> you<00:27:12.800> something<00:27:13.160> extra<00:27:13.800> if<00:27:14.000> you<00:27:14.120> give<00:27:14.360> me<00:27:14.480> the<00:27:15.520> the<00:27:15.640> money." 00:27:16.640 --> 00:27:19.240 is<00:27:17.360> part<00:27:17.640> of<00:27:17.720> 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00:29:24.800 --> 00:29:31.520 We<00:29:24.960> are<00:29:25.280> Yeah,<00:29:25.480> as<00:29:25.600> I<00:29:25.640> said,<00:29:25.920> there<00:29:26.080> is<00:29:26.200> nothing<00:29:26.840> super<00:29:28.040> um<00:29:29.160> critical<00:29:29.600> that<00:29:29.800> we<00:29:29.920> are<00:29:30.040> changing<00:29:30.520> around. 00:29:31.520 --> 00:29:40.440 Actually,<00:29:32.680> um<00:29:34.520> we<00:29:34.760> used<00:29:35.280> 8<00:29:35.640> million<00:29:36.280> of<00:29:36.480> dollars<00:29:37.480> to<00:29:37.680> make<00:29:38.720> Prowler<00:29:39.040> open<00:29:39.280> source<00:29:39.960> the 00:29:40.440 --> 00:29:44.120 the<00:29:40.600> best<00:29:41.040> platform<00:29:41.520> ever.<00:29:42.360> So,<00:29:43.120> and<00:29:43.280> that<00:29:43.440> is<00:29:43.520> for<00:29:43.680> open<00:29:43.880> source. 00:29:44.120 --> 00:29:49.080 Now,<00:29:44.640> okay,<00:29:45.200> let's<00:29:45.440> get<00:29:45.840> the<00:29:45.920> other<00:29:46.120> 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00:32:09.680 --> 00:32:17.880 But<00:32:09.840> the<00:32:09.920> world<00:32:10.360> is<00:32:10.560> beyond<00:32:10.920> that.<00:32:11.960> And<00:32:13.640> and<00:32:13.840> in<00:32:13.960> many<00:32:14.160> cases,<00:32:14.640> we<00:32:14.800> have<00:32:14.960> we<00:32:15.280> we<00:32:15.600> are<00:32:16.480> we<00:32:16.720> have<00:32:16.960> customers<00:32:17.440> coming<00:32:17.680> from 00:32:17.880 --> 00:32:26.000 them<00:32:18.640> because<00:32:18.960> probably<00:32:19.280> they<00:32:19.400> don't<00:32:19.640> want<00:32:19.880> to<00:32:20.000> pay<00:32:20.360> that<00:32:20.960> huge<00:32:21.400> bill<00:32:21.880> or<00:32:22.120> they<00:32:22.240> don't<00:32:22.520> want<00:32:22.880> to<00:32:23.320> or<00:32:23.440> they<00:32:23.720> don't<00:32:24.000> need<00:32:24.720> all<00:32:24.920> the<00:32:25.080> whole<00:32:25.520> set<00:32:25.880> of 00:32:26.000 --> 00:32:32.720 features<00:32:26.520> that<00:32:26.680> they<00:32:26.920> 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Mhm.<00:32:44.520> Right?<00:32:44.760> We<00:32:44.880> because<00:32:45.160> we<00:32:45.320> rewrote<00:32:45.760> everything<00:32:46.080> in<00:32:46.160> Python<00:32:46.560> 3<00:32:46.800> years<00:32:47.000> ago<00:32:47.560> or<00:32:47.880> less. 00:32:48.960 --> 00:32:55.880 Uh<00:32:49.160> and<00:32:49.280> we<00:32:49.400> are<00:32:49.600> adding<00:32:50.000> controls<00:32:50.560> all<00:32:50.720> the<00:32:50.840> time<00:32:51.360> and<00:32:51.960> is<00:32:52.120> very<00:32:52.720> very<00:32:53.240> new<00:32:53.600> and<00:32:53.880> modern<00:32:54.920> code. 00:32:55.880 --> 00:33:04.640 Um<00:32:56.280> so<00:32:57.320> in<00:32:57.880> So,<00:32:58.040> for<00:32:58.200> the<00:32:58.320> big<00:32:58.560> ones,<00:32:59.960> our<00:33:00.240> this<00:33:00.440> main<00:33:00.640> differentiation<00:33:01.440> is<00:33:01.640> of<00:33:01.840> course<00:33:02.120> openness<00:33:02.720> and<00:33:03.000> and<00:33:03.200> the<00:33:03.320> depth<00:33:04.280> and 00:33:04.640 --> 00:33:11.760 and<00:33:05.040> coverage<00:33:05.720> of<00:33:06.320> cloud<00:33:07.000> providers<00:33:07.680> and<00:33:07.960> controls<00:33:08.840> and<00:33:09.040> and<00:33:09.320> controls<00:33:10.000> and<00:33:10.160> compliance<00:33:10.600> frameworks. 00:33:11.760 --> 00:33:20.520 Right?<00:33:12.440> The<00:33:12.680> the<00:33:12.840> public<00:33:13.240> registry,<00:33:14.320> the<00:33:14.960> community,<00:33:16.360> um<00:33:17.280> and<00:33:17.560> the<00:33:17.760> easy<00:33:18.360> super<00:33:18.760> easy<00:33:19.040> way<00:33:19.240> to<00:33:19.400> extend<00:33:20.120> Prowler 00:33:20.520 --> 00:33:29.320 for<00:33:20.720> your<00:33:20.880> needs.<00:33:21.800> Um<00:33:23.040> but<00:33:23.360> when<00:33:23.560> it<00:33:23.680> comes<00:33:24.000> to<00:33:24.160> not<00:33:24.520> that<00:33:24.840> big<00:33:25.240> providers,<00:33:26.480> in<00:33:26.720> many<00:33:27.000> cases,<00:33:27.520> 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00:34:23.200 --> 00:34:30.600 So,<00:34:23.440> we<00:34:23.639> see<00:34:24.840> um<00:34:25.800> our<00:34:26.000> competitors<00:34:26.760> even<00:34:27.080> with<00:34:27.480> like<00:34:27.679> an<00:34:27.800> opportunity<00:34:28.440> to<00:34:28.560> make<00:34:28.760> money. 00:34:30.600 --> 00:34:38.159 How<00:34:30.720> do<00:34:30.840> you<00:34:31.399> uh<00:34:31.560> think<00:34:31.800> about<00:34:32.040> quantum?<00:34:32.600> How<00:34:32.800> is<00:34:32.919> that<00:34:33.080> going<00:34:33.200> to<00:34:33.320> change<00:34:33.600> everything<00:34:34.000> as<00:34:34.120> that<00:34:34.360> continues<00:34:34.840> to<00:34:34.919> develop<00:34:35.360> and<00:34:35.520> going<00:34:35.760> like<00:34:36.679> um<00:34:37.480> how<00:34:37.600> do<00:34:37.720> you<00:34:38.000> how<00:34:38.080> do 00:34:38.159 --> 00:34:45.320 you<00:34:38.280> think<00:34:38.440> about<00:34:38.679> that?<00:34:39.800> Well,<00:34:40.040> I<00:34:40.679> honestly<00:34:41.120> 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was<00:36:37.400> like,<00:36:37.720> yeah,<00:36:38.000> why<00:36:38.200> not? 00:36:39.720 --> 00:36:44.080 So<00:36:40.080> I<00:36:40.640> was<00:36:40.840> given<00:36:41.120> the<00:36:41.200> opportunity<00:36:41.760> to<00:36:42.080> move<00:36:42.400> to<00:36:42.520> the<00:36:42.680> US. 00:36:44.080 --> 00:36:46.160 Um<00:36:44.880> and<00:36:45.000> it<00:36:45.080> was<00:36:45.680> the<00:36:45.760> same. 00:36:46.160 --> 00:36:54.400 So<00:36:46.640> I<00:36:46.760> have<00:36:47.040> had<00:36:47.280> a<00:36:47.400> lot<00:36:47.640> of<00:36:47.840> good<00:36:48.040> opportunities<00:36:48.800> on<00:36:48.960> my<00:36:49.080> table<00:36:49.640> and<00:36:49.840> I<00:36:49.920> always<00:36:51.200> said<00:36:51.440> yes<00:36:52.280> because<00:36:52.640> I<00:36:52.720> always<00:36:53.080> wanted<00:36:53.680> a<00:36:53.800> challenge. 00:36:54.400 --> 00:37:03.000 So<00:36:54.680> I<00:36:54.760> guess<00:36:56.720> the<00:36:56.800> explorer<00:36:58.560> foundation<00:36:59.320> inside<00:36:59.720> me<00:37:00.800> gave<00:37:01.040> me<00:37:01.160> the<00:37:01.240> opportunity,<00:37:01.760> but<00:37:02.000> moreover,<00:37:02.880> the 00:37:03.000 --> 00:37:12.640 people<00:37:03.320> that<00:37:03.520> were<00:37:03.760> working<00:37:04.400> around<00:37:04.840> me,<00:37:05.520> um,<00:37:06.200> and<00:37:06.400> saw<00:37:06.640> something<00:37:07.760> in<00:37:08.080> my<00:37:08.880> skills<00:37:09.560> to<00:37:10.040> to<00:37:10.160> give<00:37:10.280> me<00:37:10.360> the<00:37:10.440> opportunity. 00:37:12.640 --> 00:37:19.080 Tony,<00:37:12.880> thank<00:37:13.080> you<00:37:13.160> so<00:37:13.280> much<00:37:13.440> for<00:37:13.560> coming<00:37:13.840> on.<00:37:14.040> Seriously,<00:37:14.400> what<00:37:14.520> an<00:37:14.640> incredible<00:37:15.160> company<00:37:15.840> and<00:37:16.720> uh<00:37:17.160> software<00:37:17.600> you've<00:37:17.800> built<00:37:18.040> with<00:37:18.200> Prowler. 00:37:19.080 --> 00:37:22.680 We're<00:37:19.240> really<00:37:19.440> honored<00:37:19.760> to<00:37:19.840> have<00:37:20.040> you.<00:37:20.160> Thank<00:37:20.360> you<00:37:20.440> so<00:37:20.560> much.<00:37:21.760> Thank<00:37:21.920> you,<00:37:22.040> Paint. 00:37:22.680 --> 00:37:25.280 Thanks<00:37:22.920> for<00:37:23.040> having<00:37:23.280> me. ``` ### Torch CEO Heather Conklin: Why human leadership matters more in the AI era URL: https://www.ceo.com/episodes/torch-ceo-heather-conklin-why-human-leadership-matters-more-in-the-ai-era/ Last updated: 2026-08-20T01:11:03.000Z # Heather Conklin thinks your AI problem is a leadership problem When Cameron Yarbrough hired Heather Conklin as Torch's first chief operating officer in 2022, it was part of a succession plan. Two years later, she was CEO. [Torch announced the promotion in August 2024](https://torch.io/newsroom/torch-promotes-heather-conklin-to-ceo/?ref=ceo.com), with Yarbrough, the co-founder, moving to executive chair. "I was hopeful that Heather could be our next CEO when I hired her," he said. Torch is a leadership coaching platform. It sells companies on the idea that leaders can be developed deliberately rather than discovered by accident. Its own succession was deliberate. Conklin came from Salesforce, where she spent nine years and ran Trailhead, the company's learning platform, as senior vice president and general manager. Before that, she created Salesforce's Associate Product Manager program, a job she got by pitching Bret Taylor, then chief product officer, on how the product organization could work differently. "I had never run a program like that before. I didn't have a blueprint. But he trusted me to build it," she said on the CEO.com Podcast. "If Bret hadn't taken that chance on me, I wouldn't be sitting here today as the CEO of a coaching company." Ask her what leadership is, and she starts by throwing out the org chart. "Leadership is not a title," she said. "It's about how you show up for other people. It's about motivating people, helping them move toward a common goal, and bringing them somewhere new together." Torch coaches at every level of its client organizations for that reason, not just the executive floor. The definition has teeth. Conklin holds that great leaders care as much about how results get achieved as about the results, and she is willing to name names. Steve Jobs built world-changing products and was known for treating people badly. "You can be the best performer in the world, but if you treat people terribly, that doesn't work for me. On the other hand, you can be incredibly empathetic and supportive, but if you never produce results, that doesn't work either. The best leaders are able to hold both of those truths at the same time." Right now, she argues, AI is testing whether companies have any such leaders. [MIT's NANDA initiative reported that 95 percent of enterprise generative AI pilots deliver no measurable return](https://fortune.com/2025/08/18/mit-report-95-percent-generative-ai-pilots-at-companies-failing-cfo/?ref=ceo.com). Conklin reads the failures as a leadership problem wearing a technology costume, a case she has also made [in Fortune](https://fortune.com/2025/10/16/torch-ceo-former-salesforce-heather-conklin-leadership-failures-ai-roi/?ref=ceo.com). "AI is exposing a lot of cracks that already existed," she told the CEO.com Podcast. "Many leadership weaknesses were there long before AI arrived. AI is simply shining a brighter light on them." The weaknesses compound because leadership is mostly inherited, not taught. "Most people learn leadership from whoever happens to be around them," she said. "If someone had a poor manager, they often end up replicating those behaviors without realizing it. Bad leadership habits get passed down." Companies spent the pandemic investing in employee well-being, then swung hard toward productivity, efficiency, and return-to-office mandates when the economy tightened. What got lost in the swing, in her telling, were the abilities that determine whether people follow a leader anywhere: communication, empathy, adaptability, resilience. "People often call these 'soft skills,' and I hate that term because there's nothing soft about them. I prefer to think of them as human skills." Torch is betting it can build those skills with machines as well as people. The company [acquired Praxis Labs in July 2025](https://torch.io/newsroom/torch-acquires-ai-learning-company-praxis-labs-to-redefine-coaching-as-a-catalyst-for-organizational-change/?ref=ceo.com), an AI learning company founded by Elise Smith and Heather Shen that had worked with companies including [eBay, Zoom, Amazon, Google, and Target](https://techcrunch.com/2025/07/11/ai-leadership-development-platform-praxis-labs-sells-to-torch/?ref=ceo.com). Torch has since folded that technology into a product that runs alongside its network of more than 350 human coaches, most of them credentialed and many with years of operating experience. Conklin's case for coaching is personal before it is commercial. Early in her career, she assumed delivering results made her a good leader. "Coaching helped me realize I hadn't spent much time understanding myself. My values, my strengths, my blind spots, and how I wanted to show up in the world. Once I did that work, everything changed." She became better, she said, at seeing other people and helping them succeed. She now runs Torch remotely from the Boston area while raising three young daughters, keeping her mornings clear for thinking and reading customer stories in a Slack channel where feedback posts automatically. The company that told her she could run it someday was right. ```chapters 00:00:00 Introduction and Overview of Torch 00:01:02 Integrating AI into Leadership Coaching 00:02:31 Defining Leadership 00:04:28 Common Traits of Effective Leaders 00:06:17 The Role of AI in Modern Leadership 00:07:07 The Necessity of Leadership in the AI Era 00:10:04 Challenges in Developing Great Leaders 00:12:12 Personal Leadership and Self-Management 00:14:20 A Day in the Life of Heather 00:16:33 Building and Growing a Coaching Business 00:20:00 Becoming a Coach at Torch 00:21:51 Reading Recommendations 00:23:49 The Importance of Giving and Taking Chances 00:25:37 Conclusion and Gratitude ``` ```vtt WEBVTT 00:00:00.280 --> 00:00:02.360 Heather,<00:00:00.520> thank<00:00:00.760> you<00:00:00.840> so<00:00:01.000> much<00:00:01.280> for<00:00:01.400> coming<00:00:01.720> on<00:00:01.840> the<00:00:01.920> show. 00:00:02.360 --> 00:00:05.080 You're<00:00:02.560> the<00:00:02.720> CEO<00:00:04.200> of<00:00:04.520> Torch. 00:00:05.080 --> 00:00:07.440 Tell<00:00:05.240> us<00:00:05.360> what<00:00:05.520> Torch<00:00:05.880> is<00:00:06.080> to<00:00:06.160> start<00:00:06.440> things<00:00:06.680> off. 00:00:07.440 --> 00:00:09.520 Yeah,<00:00:07.685> well,<00:00:07.930> thank<00:00:08.175> you<00:00:08.420> so<00:00:08.665> much<00:00:08.910> for<00:00:09.155> having<00:00:09.400> me. 00:00:09.520 --> 00:00:14.840 I<00:00:09.560> appreciate<00:00:10.120> it.<00:00:10.880> Uh<00:00:10.960> so,<00:00:11.800> Torch<00:00:12.360> is<00:00:12.920> a<00:00:13.240> leadership<00:00:13.680> coaching<00:00:14.040> platform. 00:00:14.840 --> 00:00:23.200 And<00:00:15.040> so,<00:00:15.200> we<00:00:15.400> work<00:00:15.720> with<00:00:16.840> large<00:00:17.200> businesses<00:00:18.000> across<00:00:18.360> the<00:00:18.480> world<00:00:19.440> uh<00:00:19.520> to<00:00:19.640> help<00:00:19.840> their<00:00:20.160> leaders<00:00:20.760> develop<00:00:21.320> and<00:00:21.640> 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Praxis<00:01:09.720> Labs<00:01:10.600> had<00:01:10.920> two<00:01:11.400> specific<00:01:11.920> things. 00:01:12.600 --> 00:01:16.920 Um<00:01:12.800> one<00:01:13.040> was<00:01:13.360> AI<00:01:13.680> role-play<00:01:14.200> simulations<00:01:15.120> and<00:01:15.240> one<00:01:15.440> was<00:01:15.560> an<00:01:15.760> AI<00:01:16.080> coach. 00:01:16.920 --> 00:01:23.000 And<00:01:17.480> so,<00:01:18.000> you<00:01:18.120> know,<00:01:18.400> when<00:01:18.640> we<00:01:18.760> think<00:01:18.960> about<00:01:19.280> AI<00:01:19.720> for<00:01:20.000> our<00:01:20.160> customers,<00:01:21.040> we're<00:01:21.240> really<00:01:21.520> looking<00:01:21.880> at<00:01:22.240> at<00:01:22.320> those<00:01:22.520> two<00:01:22.680> things. 00:01:23.000 --> 00:01:31.440 So,<00:01:23.280> we<00:01:23.560> have<00:01:23.840> a<00:01:24.120> new<00:01:24.400> product<00:01:24.680> that<00:01:24.960> we<00:01:25.240> launched<00:01:25.520> uh<00:01:25.800> recently<00:01:26.080> 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AI<00:01:44.960> coaching.<00:01:45.960> And<00:01:46.800> um<00:01:47.040> and<00:01:47.160> so,<00:01:47.280> that's<00:01:47.520> really<00:01:47.720> the<00:01:47.840> main<00:01:48.040> way<00:01:48.160> we<00:01:48.360> brought<00:01:48.800> it<00:01:48.880> into<00:01:49.120> like<00:01:49.320> our<00:01:49.400> products<00:01:49.840> and<00:01:50.000> services. 00:01:51.320 --> 00:01:56.280 Um<00:01:51.520> obviously,<00:01:52.160> we're<00:01:52.320> going<00:01:52.560> through<00:01:52.720> the<00:01:52.840> same<00:01:53.160> like<00:01:53.440> AI<00:01:53.760> transformation<00:01:54.640> as<00:01:54.760> every<00:01:55.000> other<00:01:55.360> business<00:01:55.840> is. 00:01:56.280 --> 00:01:59.880 And<00:01:56.480> so,<00:01:57.200> we're<00:01:57.360> also<00:01:57.680> using<00:01:58.040> it<00:01:58.200> a<00:01:58.280> lot,<00:01:58.880> you<00:01:58.960> know,<00:01:59.120> internally. 00:01:59.880 --> 00:02:08.200 So,<00:02:00.240> we<00:02:00.600> 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that's<00:02:31.480> a<00:02:31.840> I<00:02:31.880> feel<00:02:32.000> like<00:02:32.120> that<00:02:32.240> is<00:02:32.360> actually<00:02:32.600> a<00:02:32.640> very<00:02:32.880> hard<00:02:33.320> question. 00:02:33.959 --> 00:02:39.800 It's<00:02:34.120> a<00:02:35.000> Well,<00:02:35.080> you<00:02:35.200> know.<00:02:35.891> [laughter]<00:02:36.880> Um<00:02:37.560> but<00:02:37.840> it<00:02:38.080> it<00:02:38.200> is<00:02:38.360> a<00:02:38.400> tough<00:02:38.640> question. 00:02:39.800 --> 00:02:43.920 Um<00:02:40.120> you<00:02:40.200> know,<00:02:40.400> I<00:02:40.480> think<00:02:41.600> I'll<00:02:41.800> say<00:02:41.959> a<00:02:42.000> couple<00:02:42.280> things<00:02:42.520> I<00:02:42.600> think<00:02:42.880> it's<00:02:43.000> not. 00:02:43.920 --> 00:02:48.920 First<00:02:44.440> is<00:02:44.640> that<00:02:44.800> I<00:02:44.840> think<00:02:45.040> a<00:02:45.080> lot<00:02:45.360> of<00:02:45.440> people<00:02:45.680> think<00:02:45.880> of<00:02:46.000> 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organization, 00:03:13.959 --> 00:03:22.040 but<00:03:14.560> what<00:03:14.680> we're<00:03:14.800> really<00:03:15.040> trying<00:03:15.280> to<00:03:15.400> do<00:03:15.600> is<00:03:15.720> help<00:03:16.000> to<00:03:16.239> scale<00:03:17.360> great<00:03:17.640> leadership<00:03:18.200> behaviors<00:03:19.160> across<00:03:19.720> an<00:03:19.880> organization<00:03:20.720> at<00:03:20.840> all<00:03:21.080> levels. 00:03:22.040 --> 00:03:26.959 And<00:03:22.519> and<00:03:22.680> so,<00:03:23.400> we<00:03:23.560> always<00:03:23.800> say<00:03:23.920> like<00:03:24.160> anyone<00:03:24.560> can<00:03:24.720> be<00:03:24.840> a<00:03:24.920> leader,<00:03:25.239> anyone<00:03:25.600> is<00:03:25.760> a<00:03:25.800> leader. 00:03:26.959 --> 00:03:33.880 Um<00:03:27.080> and<00:03:27.200> it<00:03:27.320> really<00:03:27.600> is,<00:03:28.000> I<00:03:28.120> think,<00:03:28.360> about<00:03:29.320> um<00:03:29.640> again,<00:03:29.920> the<00:03:30.000> way<00:03:30.120> 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I<00:07:08.640> think<00:07:09.160> all<00:07:09.360> the<00:07:09.440> things<00:07:09.680> you<00:07:09.760> said<00:07:09.919> are<00:07:10.000> exactly<00:07:10.440> right. 00:07:10.880 --> 00:07:19.440 It<00:07:11.000> is<00:07:11.200> more<00:07:11.600> critical<00:07:12.240> now<00:07:12.600> than<00:07:12.800> ever<00:07:13.200> to<00:07:13.400> have<00:07:13.919> great<00:07:14.200> leaders,<00:07:14.680> and<00:07:15.560> I'm<00:07:16.200> I'm<00:07:16.360> happy<00:07:16.600> to<00:07:16.720> see<00:07:16.880> that<00:07:17.080> there's<00:07:17.640> actually<00:07:17.960> a<00:07:18.000> lot<00:07:18.160> of<00:07:18.240> places<00:07:18.600> where<00:07:18.720> I'm<00:07:18.840> seeing<00:07:19.160> that 00:07:19.440 --> 00:07:23.600 coming<00:07:19.880> out<00:07:20.160> and<00:07:20.360> and<00:07:20.560> being<00:07:21.480> um<00:07:21.800> noticed<00:07:22.360> and<00:07:22.560> and<00:07:22.720> noted. 00:07:23.600 --> 00:07:26.200 Like,<00:07:23.800> 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big<00:25:45.960> role. 00:25:47.000 --> 00:25:49.880 That's<00:25:47.160> incredible.<00:25:47.640> Heather,<00:25:47.920> thank<00:25:48.160> you<00:25:48.280> so<00:25:48.480> much<00:25:48.760> for<00:25:48.960> coming<00:25:49.240> on<00:25:49.320> the<00:25:49.400> show. 00:25:49.880 --> 00:25:54.320 Congrats<00:25:50.360> on<00:25:50.440> everything<00:25:50.880> that<00:25:51.000> you've<00:25:51.160> done<00:25:51.560> and<00:25:51.680> built<00:25:52.200> and<00:25:52.920> yeah,<00:25:53.080> what<00:25:53.240> an<00:25:53.360> honor<00:25:53.520> to<00:25:53.600> have<00:25:53.760> you. 00:25:54.320 --> 00:25:56.720 Yeah,<00:25:54.560> thank<00:25:54.840> you<00:25:54.920> so<00:25:55.040> much.<00:25:55.320> I'm<00:25:55.440> I'm<00:25:55.520> so<00:25:55.680> glad<00:25:55.920> that<00:25:56.080> we<00:25:56.200> got<00:25:56.360> the<00:25:56.440> time. 00:25:56.720 --> 00:25:59.400 Thank<00:25:56.920> you<00:25:57.000> for<00:25:57.080> all<00:25:57.160> the<00:25:57.240> great<00:25:57.400> questions. ``` ### Ampleo Chief Growth Officer Joe Grover: Why failure is every entrepreneur’s greatest teacher URL: https://www.ceo.com/episodes/ampleo-chief-growth-officer-joe-grover-why-failure-is-every-entrepreneur-s-greatest-teacher/ Last updated: 2026-08-22T20:41:49.000Z # The case for running toward the disruption Joe Grover has been a founder, venture capitalist, four-time chief marketing officer, and turnaround CEO. Ten years ago, he sat across from investors and told them their money was gone. He is now Chief Growth Officer of [Amplēo](https://ampleo.com/about/our-people/joe-grover/?ref=ceo.com), a Utah firm that places fractional executives inside small and midsize businesses. "I'm obsessed with failure because I think most entrepreneurial lessons come from failure, not success," Grover told the CEO.com Podcast. "We celebrate successful CEOs constantly, but some of the most valuable lessons come from mistakes, collapses, and setbacks." Grover started as an entrepreneur running an ad agency. He spent seven years at [Mercato Partners](https://ampleo.com/about/our-people/joe-grover/?ref=ceo.com), the Salt Lake City venture firm, where he supported investments in Skullcandy, Stance, Fusion-io, and Goal Zero, then went operational: about a decade as a venture-backed CMO in Denver and New York, a stretch as a turnaround CEO, and the CMO seat at Homie, where he grew the venture-backed real estate company into five markets. After Homie, he took a sabbatical. He played guitar, skied, and picked up fractional CMO work that led him to Amplēo, where he is now a partner and owner. Kent Thomas founded Amplēo 30 years ago as a fractional finance shop. Startups that could not afford a full-time CFO or controller called Kent. Grover launched the firm's marketing and HR practices three years ago. Amplēo [raised private equity in June 2025](https://www.prnewswire.com/news-releases/avalaunch-media-joins-amplo-to-deliver-embedded-fractional-marketing-teams-for-small-and-scaling-companies-302552819.html?ref=ceo.com), has acquired five companies including [Avalaunch Media](https://www.prnewswire.com/news-releases/avalaunch-media-joins-amplo-to-deliver-embedded-fractional-marketing-teams-for-small-and-scaling-companies-302552819.html?ref=ceo.com), and runs seven divisions serving roughly 14,000 clients. It also [partners with Silicon Slopes on Start School](https://www.prnewswire.com/news-releases/amplo-partners-with-silicon-slopes-to-grow-start-school-a-free-entrepreneurship-program-for-aspiring-founders-302770178.html?ref=ceo.com), a free entrepreneurship program. "More than 80% of small businesses fail, and we believe that's simply unacceptable," Grover said when the Avalaunch deal closed. Professional services sits squarely in AI's path. At a recent board meeting in Dallas, after hours on acquisitions and go-to-market strategy, the managing partner asked the room what the firm was doing about AI. Grover's answer is to run at the disruption rather than away from it. "If we're on the forefront of disruption, we can provide significantly more value with fewer resources and lower costs. That's an attractive position to be in." A client hiring a fractional CFO is not paying for reconciliations, he argues. "They're hiring us for 20 or 30 years of executive experience. They're buying judgment, confidence, clarity, and wisdom. Can AI automate activities? Absolutely. Can it replace trust and executive counsel? I'm not sure." Grover estimates he spends 80% of his AI time in Claude, with ChatGPT, Grok, and Perplexity filling gaps. He recently had Claude review a week of meeting notes and identify every commitment he had made. It found 65 in five days. "That was a little terrifying," he said. He has started declining more meetings. He has also worked with the same executive assistant, Michelle, for 16 years across four companies. She triages his inbox, Slack, and calendar every morning before he calls her on his 7:45 drive to the office. "Obsessive prioritization becomes critical," he said. "There are always more things to do than time allows." Grover hosts a podcast called The Real F Word. The F stands for failure. There is no business objective. He calls it entrepreneur therapy. His guests are founders who lost millions, shut down companies, and lost relationships along the way. When he had to deliver the worst news of his career to his own investors a decade ago, he did not know anyone he could talk to about it. "What I wish I'd known earlier in my career is that failure doesn't define you," he said. "A bad quarter doesn't define you. A failed company doesn't define you. What actually defines you is the accumulation of those experiences." Asked who gave him a chance, Grover named Alan Hall and Greg Warnock, who ran an early startup incubator he joined in 2005 alongside Lendio founder Brock Blake. Most of the cohort's companies failed. Hall and Warnock later brought Grover into venture capital anyway, where he spent six months working for free, calling institutional investors on the East Coast. "They saw something in me before I saw it in myself," he said. ```chapters 00:00:00 Introduction and Joe's Background 00:00:14 Early Career and Venture Capital Experience 00:00:35 Turnaround CEO and Homey Experience 00:00:56 Sabbatical and Joining Amplio 00:01:17 Amplio's History and Services 00:01:55 Impact of AI on Business 00:02:11 AI in Board Meetings and Strategy 00:02:42 AI Adoption in Small to Mid-Sized Businesses 00:03:04 Early Adoption of ChatGPT and Custom GPTs 00:03:47 AI in Professional Services 00:04:50 M&A Strategy and AI Integration 00:05:11 Value of Executive Experience vs. AI 00:06:04 Identifying AI-Disruptable Verticals 00:07:10 Preference for Claude and Co-Work Over ChatGPT 00:07:39 Use of Various AI Tools for Content Creation 00:08:54 Automating Daily Work Life with AI 00:09:47 Typical Workday Routine 00:10:20 Use of ClickUp and AI for Team Management 00:11:54 Reducing the Need for Meetings 00:12:32 Integration of Various SaaS Products 00:13:04 Future of SaaS and AI Integration 00:14:56 SaaS Market Trends and HubSpot's Position 00:16:11 Uncertainty in SaaS Platforms' Long-Term Position 00:17:15 Technology Adoption in SMBs 00:18:08 HubSpot's Market Penetration 00:19:12 Leadership Philosophy 00:22:08 Recommended Reading 00:25:29 Common Marketing Mistakes 00:27:19 Effectiveness of Billboards and Owned Media 00:29:09 Owned, Earned, and Paid Media Strategies 00:31:02 Experience with Homey and Billboards 00:31:27 Launching a Podcast on Failure 00:34:55 Mental Health and Entrepreneurship 00:36:04 The Fail Club Concept 00:36:46 Final Question: Who Gave You a Chance? 00:39:02 Junto Program and Early Entrepreneurship 00:40:13 Equity and Investment in Junto Program 00:40:44 Closing Remarks and Gratitude ``` ```vtt WEBVTT 00:00:00.000 --> 00:00:02.560 Joe,<00:00:00.320> thank<00:00:00.560> you<00:00:00.640> so<00:00:00.760> much<00:00:01.000> for<00:00:01.160> coming<00:00:01.400> on<00:00:01.480> the<00:00:01.560> show. 00:00:02.560 --> 00:00:08.240 Uh,<00:00:02.640> such<00:00:02.840> an<00:00:02.960> honor<00:00:03.200> to<00:00:03.320> have<00:00:03.600> you.<00:00:04.600> You<00:00:04.840> are<00:00:05.080> the<00:00:05.400> chief<00:00:05.800> growth<00:00:06.400> officer<00:00:07.080> of<00:00:07.280> Amplio. 00:00:08.240 --> 00:00:10.040 You<00:00:08.400> were<00:00:08.640> at<00:00:08.800> Homie<00:00:09.320> prior<00:00:09.680> to<00:00:09.800> this. 00:00:10.040 --> 00:00:14.200 Give<00:00:10.200> us<00:00:10.360> a<00:00:10.400> sense<00:00:10.720> for<00:00:10.840> your<00:00:11.000> background<00:00:11.800> and<00:00:12.440> what<00:00:12.640> Amplio<00:00:13.120> is. 00:00:14.200 --> 00:00:22.280 You<00:00:14.320> bet.<00:00:14.920> Um,<00:00:15.320> started<00:00:15.640> my<00:00:15.800> career<00:00:16.160> as<00:00:16.280> an<00:00:16.360> entrepreneur<00:00:16.920> running<00:00:17.160> an<00:00:17.280> agency,<00:00:17.880> spent<00:00:18.200> 7<00:00:18.480> years<00:00:18.680> in<00:00:18.760> venture<00:00:19.040> capital<00:00:19.480> at<00:00:19.560> Mercato<00:00:19.960> Partners,<00:00:20.520> and<00:00:21.360> left<00:00:21.800> Mercato 00:00:22.280 --> 00:00:24.760 and<00:00:22.400> joined<00:00:22.640> a<00:00:22.680> portfolio<00:00:23.160> company<00:00:23.520> as<00:00:23.640> their<00:00:23.800> chief<00:00:24.040> marketing<00:00:24.400> officer. 00:00:24.760 --> 00:00:31.400 So,<00:00:25.149> I<00:00:25.537> did<00:00:25.926> marketing,<00:00:26.314> finance,<00:00:26.703> marketing.<00:00:27.091> Um,<00:00:27.480> and<00:00:27.869> was<00:00:28.257> 10<00:00:28.646> years<00:00:29.034> as<00:00:29.423> a<00:00:29.811> venture-backed<00:00:30.200> CMO. 00:00:31.400 --> 00:00:36.360 Uh,<00:00:32.279> business<00:00:32.599> in<00:00:32.720> Denver.<00:00:33.440> We<00:00:33.560> merged<00:00:33.840> with<00:00:33.920> a<00:00:33.960> company<00:00:34.280> in<00:00:34.360> New<00:00:34.480> York<00:00:35.040> while<00:00:35.160> I<00:00:35.240> was<00:00:35.440> 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appreciate<00:40:57.240> it. ``` ### HopSkipDrive Co-Founder & CEO Joanna McFarland: How transportation shapes educational opportunity URL: https://www.ceo.com/episodes/hopskipdrive-co-founder-ceo-joanna-mcfarland-how-transportation-shapes-educational-opportunity/ Last updated: 2026-08-22T20:55:16.000Z # The bus doesn't come for everyone Joanna McFarland needed 20 minutes of help. She was working full-time and raising two kids. One of them wanted to go to karate at three o'clock on a Thursday afternoon. She had no way to get him there. She didn't need a nanny and couldn't afford one anyway. "Honestly, we felt like terrible working moms," McFarland told the CEO.com Podcast. She had found two other women with the same problem. Between them they had eight kids. In 2014 they founded [HopSkipDrive](https://www.hopskipdrive.com/about/bio/joanna-mcfarland/?ref=ceo.com), a rideshare platform built for children, with a network of vetted drivers the company calls CareDrivers. The market they backed into is bigger than karate. More than $30 billion is spent every year on student transportation in the United States, and most of it goes to a system that hasn't changed in decades: a 72-passenger yellow bus running fixed routes. "Education has changed, transportation needs have changed, and families have changed," McFarland said. HopSkipDrive now works with about 700 school districts in 17 states, filling the gaps with cars and vans where a bus doesn't work. McFarland resists the Uber-for-kids shorthand. The company is licensed the same way Uber and Lyft are, and that's where the resemblance stops, because the person in the car is not the person who booked the ride. A kid may not have a phone. A kid may not be able to speak up. So the founders built the whole system around a question McFarland still uses: What would a parent need to see before putting their own child in the car? CareDrivers average about 10 years of caregiving experience and clear background checks, fingerprinting, vehicle inspections, video interviews, and a 15-point screening. A support team watches every ride live. Parents and schools can see who is driving, where the child is, and when the car will arrive. The customers who proved the model were foster kids. Federal law lets a foster child stay enrolled at her school even when she's moved to a new placement, and a placement can happen overnight, 45 miles away. No bus system reroutes itself for one student. HopSkipDrive can. A Los Angeles County employee who used the service for her own daughter introduced the company to the child welfare system, and today many of its riders are foster youth, students experiencing homelessness, and students with special needs. For their families, a ride is rarely just a ride. In a [2025 survey](https://apnorc.org/projects/2025-state-of-school-transportation/?ref=ceo.com) by The Associated Press-NORC Center for Public Affairs Research and HopSkipDrive, 11 percent of parents said they had lost a job because of getting their children to and from school. About a third had missed work. The company's [2026 State of School Transportation Report](https://www.hopskipdrive.com/2026-state-of-school-transportation-report/?ref=ceo.com) found [71 percent of districts surveyed](https://www.businesswire.com/news/home/20260806153272/en/New-HopSkipDrive-Data-Districts-Are-Feeling-the-Real-Consequences-of-Bus-Driver-Shortages?ref=ceo.com) experienced at least one operational consequence of driver shortages in the past year, from longer ride times to missed pickups. "Transportation impacts much more than getting from Point A to Point B," McFarland said. "It impacts education. It impacts workforce participation. It impacts economic mobility." The company nearly didn't live long enough to make the argument. When COVID closed schools, the business stopped with them, and McFarland laid off more than half her staff. She rehired more than a third of them as schools reopened into worse driver shortages and higher absenteeism than before. In 2022, HopSkipDrive [raised a $37 million Series D](https://www.hopskipdrive.com/blog/how-hopskipdrive-will-use-37m-in-funding-to-modernize-school-transportation/?ref=ceo.com) from investors including Energy Impact Partners, Keyframe Capital, and FirstMark Capital. The newest product is software. RouteWise AI lets a district upload its transportation data and test hundreds of thousands of routing scenarios in minutes. One school board proposed a schedule change; RouteWise showed it would cost an extra $2 million a year, then produced alternatives that hit the same goal for nothing. "For us, AI isn't about replacing people," McFarland said. "It's about helping people focus on the work that matters most." McFarland came to all this sideways. Investment banking first, then private equity, then a Stanford MBA and 15 years in product management before the karate problem. In 2025, [Inc. put her on its Female Founders 500 list](https://www.inc.com/profile/joanna-mcfarland?ref=ceo.com). Asked who gave her a chance, she talked about the people who promoted her early. "What stands out most are the people who trusted me before I was fully ready," she said. "They put me in situations that were uncomfortable and challenging. They allowed me to learn, make mistakes, and grow. Those opportunities shaped my career more than anything else." ```chapters 00:00:00 Introduction to HopSkipDrive 00:00:29 Identifying the Problem 00:01:01 Founding Story and Initial Solution 00:01:43 Evolution to School Transportation 00:02:47 Differentiation from Uber and Lyft 00:03:29 Safety Measures and Technology 00:05:13 Impact on Parents and Special Needs 00:05:46 Realizing the Business Potential 00:06:57 Serving Vulnerable Populations 00:09:15 Current Reach and Scale 00:09:32 Typical Day for the CEO 00:10:53 Utilizing AI in Operations 00:14:34 Funding and Financial Challenges 00:15:31 Navigating COVID-19 00:18:39 Leadership and Company Values 00:21:05 Final Thoughts and Mentorship ``` ```vtt WEBVTT 00:00:00.000 --> 00:00:02.120 Joanna,<00:00:00.560> thank<00:00:00.800> you<00:00:00.880> so<00:00:01.000> much<00:00:01.240> for<00:00:01.360> coming<00:00:01.640> on<00:00:01.760> the<00:00:01.840> show. 00:00:02.120 --> 00:00:07.120 You're<00:00:02.240> the<00:00:02.360> 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you<00:04:13.040> know,<00:04:13.120> if<00:04:13.200> a<00:04:13.240> driver<00:04:13.840> is<00:04:13.959> going<00:04:14.200> to<00:04:14.360> be<00:04:14.520> late<00:04:15.040> to<00:04:15.200> school<00:04:15.520> pick<00:04:15.840> up,<00:04:16.480> that's<00:04:16.760> a<00:04:16.840> safety<00:04:17.640> problem,<00:04:18.160> right? 00:04:18.359 --> 00:04:21.920 Because<00:04:18.519> that<00:04:18.640> might<00:04:18.799> be<00:04:18.920> a<00:04:19.000> child<00:04:20.200> who<00:04:20.320> is<00:04:20.519> waiting<00:04:21.040> by<00:04:21.200> themselves. 00:04:21.920 --> 00:04:24.919 That's<00:04:22.120> very<00:04:22.400> different<00:04:23.400> than<00:04:23.560> how<00:04:23.800> Uber<00:04:24.040> and<00:04:24.120> Lyft<00:04:24.360> operate. 00:04:24.919 --> 00:04:33.400 And<00:04:25.080> so,<00:04:25.240> we<00:04:25.440> are<00:04:25.560> monitoring<00:04:26.080> that.<00:04:26.400> We<00:04:26.520> are<00:04:26.640> communicating<00:04:27.680> and<00:04:27.840> providing<00:04:28.400> full<00:04:28.720> transparency<00:04:30.200> full<00:04:30.520> transparency<00:04:32.000> and<00:04:32.200> visibility<00:04:33.240> to 00:04:33.400 --> 00:04:36.760 the<00:04:33.520> school,<00:04:34.480> to<00:04:34.640> the<00:04:34.760> parents<00:04:35.480> and<00:04:35.640> caregivers. 00:04:36.760 --> 00:04:45.440 Our<00:04:36.960> team<00:04:37.440> is<00:04:37.600> monitoring<00:04:38.160> that.<00:04:38.760> And<00:04:38.919> so,<00:04:39.240> everything<00:04:40.520> is<00:04:40.680> really<00:04:40.960> wrapped<00:04:41.440> around<00:04:42.120> this<00:04:42.440> safe<00:04:42.800> ride<00:04:43.040> experience<00:04:43.680> that<00:04:43.840> makes<00:04:44.160> it<00:04:44.400> a<00:04:44.480> very<00:04:45.160> very 00:04:45.440 --> 00:04:48.360 different<00:04:45.800> model.<00:04:46.800> And<00:04:46.919> uh<00:04:46.960> schools<00:04:47.320> love<00:04:47.560> that,<00:04:48.040> right? 00:04:48.360 --> 00:04:53.240 Like<00:04:48.880> you<00:04:49.040> and<00:04:49.200> I<00:04:49.360> I<00:04:49.480> can<00:04:49.640> order<00:04:49.880> pizza<00:04:50.480> and<00:04:50.680> watch<00:04:51.000> my<00:04:51.120> pizza<00:04:51.560> get<00:04:51.720> delivered<00:04:52.160> to<00:04:52.280> me. 00:04:53.240 --> 00:04:56.680 Most<00:04:53.680> school<00:04:53.919> buses<00:04:54.360> today<00:04:54.800> don't<00:04:55.240> have<00:04:55.480> that<00:04:55.680> technology. 00:04:56.680 --> 00:05:01.160 Most<00:04:57.120> They're<00:04:57.280> They're<00:04:57.880> getting<00:04:58.240> there,<00:04:59.040> but<00:04:59.240> parents<00:04:59.640> don't<00:04:59.880> have<00:05:00.000> any<00:05:00.200> idea<00:05:00.440> where<00:05:00.560> their<00:05:00.680> kids<00:05:01.000> are. 00:05:01.160 --> 00:05:04.280 With<00:05:01.400> our<00:05:01.680> app,<00:05:02.240> there's<00:05:02.560> full<00:05:02.840> visibility<00:05:03.360> and<00:05:03.480> transparency. 00:05:04.280 --> 00:05:12.160 Parents<00:05:04.720> know<00:05:05.040> who<00:05:05.200> the<00:05:05.320> driver<00:05:05.760> is,<00:05:05.960> they<00:05:06.080> know<00:05:06.400> where<00:05:06.560> their<00:05:06.720> child<00:05:07.240> is,<00:05:07.440> they<00:05:07.520> know<00:05:07.680> exactly<00:05:08.240> what's<00:05:08.480> happening,<00:05:09.480> and<00:05:09.600> it<00:05:09.720> just<00:05:09.919> creates<00:05:10.320> peace<00:05:10.640> of<00:05:10.840> mind<00:05:11.760> across 00:05:12.160 --> 00:05:18.720 the<00:05:12.280> board.<00:05:13.880> Yeah,<00:05:14.120> which<00:05:14.440> is<00:05:15.040> unbelievable<00:05:16.400> if<00:05:16.680> you<00:05:16.919> have<00:05:17.280> a<00:05:17.320> child<00:05:17.800> who<00:05:17.960> needs<00:05:18.280> this,<00:05:18.520> right? 00:05:18.720 --> 00:05:21.800 Like<00:05:18.960> I<00:05:19.000> mean,<00:05:19.720> child<00:05:20.000> child<00:05:20.200> transportation<00:05:20.760> is<00:05:20.880> such<00:05:21.160> a<00:05:21.200> huge<00:05:21.480> deal. 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--> 00:05:38.120 So,<00:05:35.800> um<00:05:36.480> thank<00:05:36.800> you<00:05:37.240> for<00:05:37.400> what<00:05:37.560> you're<00:05:37.680> building. 00:05:38.120 --> 00:05:41.160 It's<00:05:38.360> It's<00:05:38.560> actually<00:05:39.000> a<00:05:39.560> really<00:05:39.840> remarkable. 00:05:41.160 --> 00:05:44.120 And<00:05:41.720> at<00:05:42.280> what<00:05:42.480> point<00:05:42.640> did<00:05:42.800> you<00:05:42.880> realize,<00:05:43.160> "Hey,<00:05:43.280> we're<00:05:43.480> onto<00:05:43.760> something." 00:05:44.120 --> 00:05:52.520 At<00:05:44.240> what<00:05:44.360> point<00:05:44.560> did<00:05:44.680> it<00:05:44.800> start<00:05:45.040> working?<00:05:46.600> Yeah,<00:05:47.000> it<00:05:47.160> was<00:05:47.440> you<00:05:47.560> know,<00:05:48.200> what<00:05:48.400> was<00:05:48.560> interesting<00:05:49.480> is<00:05:50.120> and<00:05:50.320> and<00:05:50.480> you<00:05:50.560> mentioned<00:05:50.920> special<00:05:51.280> needs<00:05:52.120> kids 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to<00:06:09.960> think<00:06:10.400> about<00:06:11.360> how<00:06:11.520> to<00:06:11.640> be<00:06:11.760> in<00:06:11.840> compliance<00:06:12.400> with<00:06:12.640> federal<00:06:13.040> laws<00:06:13.560> around<00:06:13.920> foster<00:06:14.360> youth. 00:06:14.720 --> 00:06:21.680 So,<00:06:14.920> foster<00:06:15.440> youth<00:06:15.800> have<00:06:16.120> the<00:06:16.240> federal<00:06:16.880> right<00:06:17.600> to<00:06:17.760> stay<00:06:18.000> at<00:06:18.120> their<00:06:18.280> school<00:06:19.240> regardless<00:06:19.840> of<00:06:19.919> their<00:06:20.080> housing<00:06:20.440> situation. 00:06:21.680 --> 00:06:24.280 Think<00:06:21.840> about<00:06:22.080> this.<00:06:22.240> You<00:06:22.320> have<00:06:22.400> a<00:06:22.480> kid<00:06:22.720> who's<00:06:22.919> in<00:06:23.040> foster<00:06:23.400> care. 00:06:24.280 --> 00:06:27.760 They've<00:06:24.520> now<00:06:24.720> moved<00:06:25.200> home<00:06:25.400> placements.<00:06:26.360> They<00:06:26.480> might<00:06:26.680> have<00:06:26.800> moved<00:06:27.000> far<00:06:27.160> away. 00:06:27.760 --> 00:06:33.240 Here<00:06:27.919> in<00:06:28.000> LA,<00:06:28.320> one<00:06:28.560> out<00:06:28.680> of<00:06:28.760> every<00:06:29.000> three<00:06:29.200> kids<00:06:29.520> moves<00:06:29.760> to<00:06:29.840> Antelope<00:06:30.160> Valley,<00:06:30.480> which<00:06:30.640> is<00:06:30.800> like<00:06:31.040> 45<00:06:31.600> miles<00:06:31.880> away. 00:06:33.240 --> 00:06:36.120 Every<00:06:33.560> source<00:06:33.840> of<00:06:33.919> stability<00:06:34.400> that<00:06:34.560> this<00:06:34.720> kid<00:06:34.960> has<00:06:35.360> is<00:06:35.480> gone. 00:06:36.120 --> 00:06:42.720 They're<00:06:36.280> in<00:06:36.360> a<00:06:36.400> new<00:06:36.640> home,<00:06:37.240> they're<00:06:37.440> in<00:06:37.520> a<00:06:37.560> new<00:06:38.320> they<00:06:38.520> may<00:06:38.880> have<00:06:39.080> been<00:06:39.200> told<00:06:39.600> like<00:06:39.800> you<00:06:39.880> 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stay<00:06:53.200> at<00:06:53.280> their<00:06:53.440> school,<00:06:53.960> right? 00:06:54.160 --> 00:07:01.600 That's<00:06:54.400> really<00:06:54.840> important<00:06:55.240> for<00:06:55.320> these<00:06:55.560> kids.<00:06:55.960> And<00:06:56.080> by<00:06:56.160> the<00:06:56.280> way,<00:06:56.440> every<00:06:56.680> time<00:06:56.960> you<00:06:57.600> move<00:06:57.919> schools,<00:06:58.840> your<00:06:59.160> odds<00:06:59.440> of<00:06:59.560> graduating<00:07:00.200> just<00:07:00.480> plummet,<00:07:01.320> right? 00:07:01.600 --> 00:07:07.880 Because<00:07:01.880> of<00:07:02.000> the<00:07:02.360> because<00:07:02.760> of<00:07:02.840> this<00:07:03.000> instability<00:07:03.720> and<00:07:04.160> different<00:07:04.480> schools<00:07:04.880> teach<00:07:05.240> different<00:07:05.600> things<00:07:05.960> in<00:07:06.040> different<00:07:06.360> grades. 00:07:07.880 --> 00:07:10.320 Transportation<00:07:08.600> is<00:07:08.720> one<00:07:08.840> of<00:07:08.880> the<00:07:08.960> biggest<00:07:09.280> obstacles<00:07:09.840> to<00:07:09.960> that. 00:07:10.320 --> 00:07:15.800 How<00:07:10.440> are<00:07:10.520> you<00:07:10.600> going<00:07:10.720> to<00:07:10.800> get<00:07:10.960> this<00:07:11.160> kid<00:07:11.400> there?<00:07:12.080> The<00:07:12.160> kid<00:07:12.400> moves<00:07:12.640> at<00:07:12.760> 10:30<00:07:13.160> at<00:07:13.240> night,<00:07:13.480> you<00:07:13.560> can't<00:07:13.840> reroute<00:07:14.120> a<00:07:14.200> school<00:07:14.480> bus<00:07:14.800> for<00:07:14.960> this<00:07:15.160> kid. 00:07:15.800 --> 00:07:20.440 HopSkipDrive<00:07:16.600> can<00:07:16.720> get<00:07:16.840> them<00:07:16.960> to<00:07:17.080> school<00:07:17.280> the<00:07:17.360> next<00:07:17.600> day<00:07:17.760> with<00:07:17.960> no<00:07:18.360> interruption<00:07:19.000> in<00:07:19.120> their<00:07:19.240> schooling. 00:07:20.440 --> 00:07:25.720 And<00:07:20.560> so<00:07:20.720> as<00:07:20.960> we<00:07:21.080> 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started<00:07:50.000> working<00:07:50.240> with<00:07:50.400> school<00:07:50.680> districts. 00:07:51.840 --> 00:08:00.400 And<00:07:52.240> and<00:07:52.360> what<00:07:52.520> we<00:07:52.640> see<00:07:52.840> is<00:07:53.080> kind<00:07:53.280> of<00:07:53.360> the<00:07:53.440> most<00:07:53.680> vulnerable<00:07:54.200> populations,<00:07:55.000> the<00:07:55.080> ones<00:07:55.320> that<00:07:55.480> most<00:07:55.960> need<00:07:56.440> service<00:07:56.960> are<00:07:57.200> the<00:07:57.360> least<00:07:57.720> likely<00:07:58.680> to<00:07:58.840> be<00:07:59.000> able<00:07:59.320> to<00:07:59.480> be<00:07:59.600> served 00:08:00.400 --> 00:08:03.840 by<00:08:00.560> a<00:08:00.640> school<00:08:00.920> bus.<00:08:01.600> It's<00:08:01.840> foster<00:08:02.320> youth,<00:08:02.720> homeless<00:08:03.320> youth. 00:08:03.840 --> 00:08:09.320 These<00:08:04.040> kids<00:08:04.280> are<00:08:04.400> moving<00:08:04.880> all<00:08:05.080> the<00:08:05.200> time<00:08:06.080> 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00:12:44.800 --> 00:12:47.680 If<00:12:44.920> you<00:12:45.040> change<00:12:45.360> it<00:12:45.520> by<00:12:45.760> 2<00:12:46.080> minutes,<00:12:46.880> here's<00:12:47.160> what<00:12:47.280> happens. 00:12:47.680 --> 00:12:54.839 If<00:12:47.800> you<00:12:47.920> want,<00:12:48.200> you<00:12:48.280> know,<00:12:48.920> we've<00:12:49.080> had<00:12:49.240> situations<00:12:49.839> where<00:12:51.560> boards<00:12:52.040> have<00:12:52.240> said,<00:12:52.480> school<00:12:52.760> boards<00:12:53.040> have<00:12:53.200> said,<00:12:53.440> "This<00:12:53.640> is<00:12:53.720> going<00:12:53.839> to<00:12:53.920> be<00:12:54.040> the<00:12:54.120> bell<00:12:54.320> time." 00:12:54.839 --> 00:12:59.280 And<00:12:55.680> once<00:12:56.000> we<00:12:56.160> used<00:12:56.520> Routewise,<00:12:56.960> we<00:12:57.040> said,<00:12:57.200> "Great,<00:12:57.440> that's<00:12:57.640> going<00:12:57.760> to<00:12:57.839> cost<00:12:58.080> you<00:12:58.160> $2<00:12:58.440> million." 00:12:59.280 --> 00:13:07.600 If<00:12:59.440> that's<00:12:59.640> what<00:12:59.760> you<00:12:59.839> want<00:12:59.960> to<00:13:00.040> do,<00:13:00.680> great.<00:13:01.320> Here's<00:13:01.960> five<00:13:02.360> other<00:13:02.600> solutions<00:13:03.320> that<00:13:03.520> meet<00:13:03.800> the<00:13:03.880> intent<00:13:04.320> of<00:13:04.440> what<00:13:04.600> you<00:13:04.720> want<00:13:04.960> to<00:13:05.120> do<00:13:05.800> and<00:13:05.920> are<00:13:06.000> cost-neutral. 00:13:07.600 --> 00:13:15.440 That's<00:13:07.880> real<00:13:08.040> power<00:13:08.520> for<00:13:08.720> a<00:13:08.760> school<00:13:09.320> and<00:13:09.440> a<00:13:09.480> school<00:13:09.800> board<00:13:10.560> and<00:13:10.760> a<00:13:10.800> director<00:13:11.200> of<00:13:11.280> transportation<00:13:12.080> to<00:13:12.200> be<00:13:12.320> able<00:13:12.520> to<00:13:12.640> understand<00:13:13.320> the<00:13:13.440> impact<00:13:13.839> of<00:13:13.920> those<00:13:14.160> decisions. 00:13:15.440 --> 00:13:23.600 Um,<00:13:15.960> we<00:13:16.080> can<00:13:16.240> also<00:13:16.480> use<00:13:16.680> it<00:13:16.800> to<00:13:16.920> help<00:13:17.160> them<00:13:17.360> see<00:13:17.640> how<00:13:17.960> a<00:13:18.040> multimodal<00:13:18.720> system<00:13:19.520> will<00:13:19.760> reduce<00:13:20.160> cost,<00:13:20.880> will<00:13:21.000> reduce<00:13:21.440> time<00:13:21.760> in<00:13:21.839> transit,<00:13:22.800> will<00:13:22.960> mean<00:13:23.240> that,<00:13:23.520> you 00:13:23.600 --> 00:13:28.600 know,<00:13:23.760> your<00:13:23.920> students<00:13:24.240> with<00:13:24.320> special<00:13:24.640> needs<00:13:24.960> don't<00:13:25.240> need<00:13:25.400> to<00:13:25.480> be<00:13:25.600> on<00:13:25.680> the<00:13:25.760> bus<00:13:26.000> for<00:13:26.160> 3<00:13:26.440> hours,<00:13:26.839> and<00:13:27.000> here's<00:13:27.240> how<00:13:27.360> to<00:13:27.520> do<00:13:27.760> that. 00:13:28.600 --> 00:13:35.480 Um,<00:13:29.000> 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Uh<00:21:09.080> Joanna,<00:21:09.760> um<00:21:10.320> it's<00:21:10.480> amazing. 00:21:10.880 --> 00:21:18.120 We<00:21:11.040> end<00:21:11.160> every<00:21:11.360> interview<00:21:11.600> with<00:21:11.720> the<00:21:11.800> same<00:21:12.000> question<00:21:12.480> and<00:21:12.640> that<00:21:12.840> is<00:21:12.960> at<00:21:13.160> ceo.com,<00:21:14.720> we<00:21:14.880> believe<00:21:15.200> the<00:21:15.320> chances<00:21:15.760> one<00:21:16.040> gives<00:21:16.560> are<00:21:16.680> just<00:21:16.920> as<00:21:17.000> important<00:21:17.320> as<00:21:17.400> the<00:21:17.480> chances<00:21:17.920> one 00:21:18.120 --> 00:21:22.920 takes.<00:21:19.400> When<00:21:19.680> you<00:21:19.880> hear<00:21:20.120> that,<00:21:20.360> who<00:21:20.520> gave<00:21:20.760> you<00:21:20.880> a<00:21:20.920> chance<00:21:21.240> to<00:21:21.320> get<00:21:21.480> you<00:21:21.560> to<00:21:21.640> where<00:21:21.800> you<00:21:21.920> are<00:21:22.040> today? 00:21:22.920 --> 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opportunities<00:21:43.760> that<00:21:44.040> that<00:21:44.200> I<00:21:44.320> got<00:21:44.560> very<00:21:44.840> early<00:21:45.080> on<00:21:45.200> in<00:21:45.280> my<00:21:45.400> career<00:21:46.680> way<00:21:47.000> over<00:21:47.200> my<00:21:47.360> head,<00:21:47.640> had<00:21:47.800> no<00:21:48.080> idea<00:21:48.320> what<00:21:48.440> I<00:21:48.480> was<00:21:48.680> doing<00:21:49.160> and 00:21:49.400 --> 00:21:57.640 and<00:21:49.600> somebody<00:21:50.560> put<00:21:50.840> their<00:21:51.000> trust<00:21:51.480> in<00:21:51.640> me<00:21:52.000> to<00:21:52.720> and<00:21:52.920> put<00:21:53.120> me<00:21:53.280> into<00:21:53.720> to<00:21:53.840> situations<00:21:54.480> where<00:21:54.640> I<00:21:54.680> was<00:21:54.840> very<00:21:55.080> uncomfortable<00:21:56.760> um<00:21:57.320> and<00:21:57.480> and 00:21:57.640 --> 00:22:05.720 probably<00:21:57.946> they<00:21:58.252> were<00:21:58.558> very<00:21:58.865> uncomfortable,<00:21:59.171> <00:21:59.477> [laughter<00:21:59.783> and<00:22:00.089> snorts]<00:22:00.395> <00:22:00.702> but<00:22:01.008> uh<00:22:01.314> but<00:22:01.620> let<00:22:01.926> me<00:22:02.232> grow<00:22:02.538> and<00:22:02.845> learn<00:22:03.151> and<00:22:03.457> make<00:22:03.763> mistakes<00:22:04.069> um<00:22:04.375> and<00:22:04.682> and<00:22:04.988> that<00:22:05.294> was<00:22:05.600> you 00:22:05.720 --> 00:22:12.160 know,<00:22:05.880> I<00:22:05.960> think<00:22:06.280> some<00:22:06.480> of<00:22:06.600> the<00:22:06.720> biggest<00:22:08.000> uh<00:22:08.560> benefits<00:22:09.120> to<00:22:09.240> my<00:22:09.400> career<00:22:09.680> that<00:22:10.040> that<00:22:10.640> I<00:22:10.760> could<00:22:10.920> have<00:22:11.040> gotten. 00:22:12.160 --> 00:22:14.760 <00:22:12.343> That's<00:22:12.527> incredible.<00:22:12.710> Joanna,<00:22:12.893> thank<00:22:13.077> you<00:22:13.260> so<00:22:13.443> much<00:22:13.627> for<00:22:13.810> coming<00:22:13.993> on<00:22:14.177> the<00:22:14.360> show. 00:22:14.760 --> 00:22:19.480 Really,<00:22:14.954> what<00:22:15.149> an<00:22:15.343> honor<00:22:15.537> to<00:22:15.731> have<00:22:15.926> you.<00:22:16.120> <00:22:16.314> Thank<00:22:16.509> you<00:22:16.703> so<00:22:16.897> much<00:22:17.091> for<00:22:17.286> having<00:22:17.480> me. ``` ### Branch CEO David Karnstedt - How AI Agents Will Transform Marketing URL: https://www.ceo.com/episodes/branch-ceo-david-karnstedt-how-ai-agents-will-transform-marketing/ Last updated: 2026-08-22T21:06:50.000Z # David Karnstedt thinks your next customer will be an agent Someone sent David Karnstedt a Wall Street Journal article over the weekend. He clicked the link on his phone. Instead of the article, he got the homepage of the Journal's app. "The article was gone," he said. Karnstedt is the CEO of Branch, and broken links are his business. The company's deep links carry a user through to the thing they actually clicked, even through an app install. Its measurement products tell marketers which channels drive results and which just look like they do. Branch has been at this for 12 years. [Karnstedt took over in May 2024](https://www.prnewswire.com/news-releases/branch-strengthens-leadership-team-with-executive-appointments-302149946.html?ref=ceo.com), a marketing technology veteran with more than 25 years of experience and senior roles at Overture, Yahoo, Efficient Frontier, and Adobe. On the CEO.com Podcast, he told a story about his own company that explains the moment better than any forecast. Branch recently rewrote its entire interface and the architecture underneath it. The team scoped the project at 12 months. It shipped in six. "Our designers are telling us they can do in a day what previously took two weeks," he said. The same tools cut Branch's support ticket volume roughly in half. Karnstedt draws a narrow conclusion from all this, narrower than most CEOs would. Not fewer people. The same people, aimed better. "I don't view AI as replacing employees. I view it as helping us deploy people into roles where they can create more impact." Where he does make a prediction, it's a big one. "I think we're moving toward a world where personal AI agents will interface with brands on our behalf," he said. "If that sounds far away, I don't think it is. I think it's coming much faster than people realize." His evidence is recent history. Ten years ago, nobody predicted social platforms would become primary channels for product discovery. Then they did. He is already spending R&D money on the ugly side of that future. Branch sells fraud prevention products today, catching things like invalid app installs, and Karnstedt expects the problem to grow as agents multiply. Even Branch's own modest ad budget attracts meaningful click fraud. Cut 5% or 10% of fraudulent traffic, he said, and the performance gains are substantial. For a man whose company just compressed a year into six months, Karnstedt talks like someone with time. Branch last raised in February 2022, [$300 million at a $4 billion valuation led by NEA](https://www.branch.io/resources/news/branch-raises-300-million-at-4-billion-valuation-to-open-mobile-ecosystem-and-provide-solution-to-walled-gardens/?ref=ceo.com), the same firm that later introduced him to the CEO job. He has no interest in raising again unless he chooses to. "The era of free capital is over. The days of growth at all costs are gone." On privacy, the posture is the same. "If there's a privacy line, we intentionally stay well behind it." The company runs about 300 people across India, Dubai, and a dozen other places. "Sometimes it feels like I'm running a 7-Eleven because we're always open." Last week he flew the entire product and engineering organization into Mountain View to plan the 2026 roadmap in one room, with whiteboards, because some work still refuses to happen over Zoom. Asked what makes a great leader, he did not reach for a framework. He reached for a person. Jeff Weiner, who worked alongside him at Yahoo before running LinkedIn, held every meeting to the same three or four priorities. Never more. "Everyone knew exactly what mattered. If people were executing against those priorities, leadership's job was simply to remove obstacles." Every CEO.com interview ends with the same question, about the chances one gives and the chances one takes. Karnstedt went back to Yahoo. Several businesses were being folded into one organization, thousands of employees, billions in revenue, the press watching, and someone handed him the job. "Being trusted with something that large fundamentally changed the trajectory of my career," he said. It led to his first CEO role, then Adobe, then Branch. Somebody gave him the link. It carried him all the way through. ```chapters 00:00:00 Introduction and Overview of Branch 00:00:49 David's Background and Role at Branch 00:01:10 Impact of AI on Marketing 00:02:20 Future of AI and Personal Agents 00:03:34 Social Media in the Age of AI 00:04:40 Employee Empowerment and Efficiency with AI 00:05:34 Building Company Culture Post-COVID 00:07:06 A Day in the Life of a CEO 00:07:49 Reading and Podcast Recommendations 00:09:02 Funding and Financial Strategy 00:10:05 Macroeconomic Environment and Business Strategy 00:11:08 Privacy and Security in Marketing 00:12:37 Best Paid Marketing Channels 00:14:10 Growth of TikTok and Influencer Marketing 00:14:47 Qualities of a Great Leader 00:15:56 Reflecting on Career Opportunities and Mentorship 00:16:51 Conclusion and Thanksgiving Wishes ``` ```vtt WEBVTT 00:00:00.000 --> 00:00:01.920 David,<00:00:00.440> thank<00:00:00.640> you<00:00:00.680> so<00:00:00.800> much<00:00:00.960> for<00:00:01.080> coming<00:00:01.360> on<00:00:01.480> the<00:00:01.560> show. 00:00:01.920 --> 00:00:06.240 What<00:00:02.080> an<00:00:02.200> honor<00:00:02.360> to<00:00:02.480> have<00:00:02.920> you.<00:00:03.120> You're<00:00:03.280> the<00:00:03.440> CEO<00:00:04.600> of<00:00:04.920> Branch. 00:00:06.240 --> 00:00:08.760 Tell<00:00:06.440> us<00:00:06.560> what<00:00:06.680> Branch<00:00:07.040> is<00:00:07.240> and<00:00:07.320> how<00:00:07.440> you<00:00:07.560> became<00:00:07.840> the<00:00:07.920> CEO. 00:00:08.760 --> 00:00:14.120 Yeah,<00:00:09.200> well,<00:00:09.480> so<00:00:09.680> Branch<00:00:10.320> is<00:00:10.680> a<00:00:11.120> mobile<00:00:11.440> measurement<00:00:12.040> and<00:00:12.200> deep<00:00:12.480> linking<00:00:12.840> platform. 00:00:14.120 --> 00:00:16.400 Uh,<00:00:14.680> been<00:00:14.880> around<00:00:15.280> for<00:00:15.400> about<00:00:15.760> 12<00:00:16.120> years. 00:00:16.400 --> 00:00:19.760 And<00:00:16.520> what<00:00:16.840> that<00:00:17.000> really<00:00:17.200> means,<00:00:17.520> Clint,<00:00:18.080> is<00:00:18.560> I'll<00:00:18.680> give<00:00:18.760> you<00:00:18.840> a<00:00:18.880> perfect<00:00:19.200> example. 00:00:19.760 --> 00:00:23.200 Somebody<00:00:20.080> sent<00:00:20.240> me<00:00:20.840> a<00:00:20.920> Wall<00:00:21.120> Street<00:00:21.360> Journal<00:00:21.680> article<00:00:22.080> over<00:00:22.200> the<00:00:22.280> weekend. 00:00:23.200 --> 00:00:30.240 Uh,<00:00:23.960> I<00:00:24.440> tried<00:00:24.720> to<00:00:24.760> open<00:00:24.960> the<00:00:25.040> link,<00:00:25.320> dropped<00:00:25.560> me<00:00:25.640> to<00:00:25.720> the<00:00:25.800> front<00:00:26.040> page<00:00:26.560> of<00:00:26.760> my<00:00:26.960> mobile<00:00:27.400> app<00:00:27.680> at<00:00:27.760> the<00:00:27.840> Wall<00:00:28.000> Street<00:00:28.240> Journal,<00:00:28.680> and<00:00:28.800> the<00:00:28.880> article<00:00:29.200> was<00:00:29.320> gone. 00:00:30.240 --> 00:00:37.480 If<00:00:30.480> the<00:00:30.560> Wall<00:00:30.720> Street<00:00:30.920> Journal<00:00:31.160> had<00:00:31.360> used<00:00:31.880> uh<00:00:32.400> Branch<00:00:32.720> deep<00:00:33.000> links,<00:00:33.800> it<00:00:33.920> would<00:00:34.000> have<00:00:34.120> deferred<00:00:34.480> that<00:00:34.680> link<00:00:34.960> and<00:00:35.080> opened<00:00:35.320> the<00:00:35.440> article<00:00:35.840> once<00:00:36.120> the<00:00:36.720> app<00:00:37.000> fired. 00:00:37.480 --> 00:00:44.840 So,<00:00:37.600> that's<00:00:37.760> on<00:00:37.880> the<00:00:37.960> linking<00:00:38.280> side.<00:00:38.880> Measurement<00:00:39.320> side<00:00:39.520> is<00:00:39.680> really<00:00:40.080> allowing<00:00:40.600> marketers<00:00:41.960> uh<00:00:42.040> to<00:00:42.160> measure<00:00:42.400> what's<00:00:42.600> most<00:00:42.880> effective,<00:00:43.360> whether<00:00:43.560> that<00:00:43.720> be<00:00:43.840> organic<00:00:44.560> or 00:00:44.840 --> 00:00:48.760 paid<00:00:45.160> for<00:00:45.360> channels,<00:00:46.360> and<00:00:46.480> then<00:00:46.600> allocating<00:00:47.080> spend<00:00:47.400> accordingly. 00:00:48.760 --> 00:00:53.000 And<00:00:49.720> uh<00:00:49.760> to<00:00:49.840> your<00:00:49.960> point,<00:00:50.200> Clint,<00:00:50.440> I've<00:00:50.520> been<00:00:50.680> on<00:00:50.840> board<00:00:51.120> for<00:00:51.200> about<00:00:51.440> 18<00:00:51.840> months. 00:00:53.000 --> 00:00:58.320 Uh,<00:00:53.480> joined<00:00:54.440> uh<00:00:54.520> via<00:00:54.960> NEA,<00:00:55.520> which<00:00:55.760> is<00:00:55.880> one<00:00:56.000> of<00:00:56.080> our<00:00:56.200> lead<00:00:56.480> backers. 00:00:58.320 --> 00:01:00.760 What<00:00:58.600> were<00:00:58.680> you<00:00:58.760> doing<00:00:59.000> prior?<00:00:59.960> You<00:01:00.120> know,<00:01:00.240> it's<00:01:00.400> interesting. 00:01:00.760 --> 00:01:06.040 I<00:01:00.800> was<00:01:00.920> working<00:01:01.280> with<00:01:01.400> a<00:01:01.480> lot<00:01:01.840> of<00:01:02.160> uh<00:01:02.560> founder<00:01:03.920> uh<00:01:04.000> CEOs<00:01:04.640> that<00:01:04.760> were<00:01:04.839> looking<00:01:05.120> to<00:01:05.199> scale<00:01:05.519> businesses. 00:01:06.040 --> 00:01:12.560 So,<00:01:06.160> I<00:01:06.200> consulted<00:01:06.760> with<00:01:06.920> a<00:01:06.960> number<00:01:07.280> of<00:01:07.360> different<00:01:08.520> uh<00:01:08.600> companies<00:01:09.120> prior<00:01:09.440> to<00:01:09.560> taking<00:01:09.840> a<00:01:09.880> full-time<00:01:10.360> role<00:01:10.560> here<00:01:10.880> at<00:01:11.080> Branch. 00:01:12.560 --> 00:01:17.920 Uh,<00:01:12.960> that's<00:01:13.200> awesome.<00:01:13.720> Well,<00:01:14.520> uh<00:01:14.600> tell<00:01:14.800> me<00:01:14.920> how<00:01:15.080> marketing<00:01:15.600> is<00:01:15.720> changing<00:01:16.240> in<00:01:16.400> the<00:01:16.520> age<00:01:16.720> of<00:01:16.840> AI. 00:01:17.920 --> 00:01:20.720 Uh,<00:01:18.120> well,<00:01:18.480> I<00:01:18.560> mean,<00:01:18.760> everything's<00:01:19.440> changing. 00:01:20.720 --> 00:01:29.000 Uh<00:01:20.800> I<00:01:20.920> mean,<00:01:21.080> I<00:01:21.240> mean,<00:01:21.480> we're<00:01:21.600> talking<00:01:21.960> on<00:01:22.080> the<00:01:22.240> release<00:01:22.760> of<00:01:23.240> recent<00:01:23.640> release<00:01:24.160> of<00:01:24.400> Gemini,<00:01:25.480> which<00:01:25.720> seems<00:01:26.240> way<00:01:26.560> better<00:01:26.880> than<00:01:27.280> everything<00:01:27.800> else,<00:01:28.280> which<00:01:28.440> is<00:01:28.560> crazy. 00:01:29.000 --> 00:01:31.440 Like,<00:01:29.160> it's<00:01:29.280> way<00:01:29.440> better<00:01:29.640> than<00:01:29.800> ChatGPT,<00:01:30.400> at<00:01:30.480> least<00:01:31.320> currently. 00:01:31.440 --> 00:01:33.680 It<00:01:31.520> seems<00:01:31.760> like<00:01:32.160> That's<00:01:32.360> like<00:01:32.520> the<00:01:32.840> Like,<00:01:32.960> this<00:01:33.160> is<00:01:33.360> nuts. 00:01:33.680 --> 00:01:37.400 And<00:01:33.760> then<00:01:33.920> like<00:01:34.200> a<00:01:34.280> month<00:01:34.520> from<00:01:34.680> now,<00:01:34.880> who's<00:01:35.080> going<00:01:35.200> to<00:01:35.280> have<00:01:35.520> the<00:01:35.600> one<00:01:35.800> that's<00:01:35.960> way<00:01:36.120> better<00:01:36.360> than<00:01:36.600> the<00:01:36.720> current<00:01:36.960> Gemini? 00:01:37.400 --> 00:01:44.600 It's<00:01:37.760> crazy.<00:01:38.280> Yeah,<00:01:38.440> I<00:01:38.520> mean,<00:01:38.720> just<00:01:39.200> you<00:01:39.280> know,<00:01:39.720> you<00:01:39.840> know,<00:01:40.000> it's<00:01:40.400> it's<00:01:40.600> overblown,<00:01:41.200> and<00:01:41.280> it's<00:01:41.400> been<00:01:41.560> said<00:01:41.840> so<00:01:41.960> much,<00:01:42.280> but<00:01:42.520> AI<00:01:42.800> is<00:01:42.960> transforming<00:01:43.600> everything. 00:01:44.600 --> 00:01:50.320 I'll<00:01:44.760> give<00:01:44.920> you<00:01:45.000> an<00:01:45.080> example<00:01:45.680> for<00:01:45.880> Branch.<00:01:46.880> We<00:01:47.000> just<00:01:47.240> totally<00:01:47.680> rewrote<00:01:48.400> our<00:01:48.560> entire<00:01:49.040> interface. 00:01:50.320 --> 00:01:58.000 And<00:01:50.800> and<00:01:51.160> and<00:01:51.400> kind<00:01:51.560> of<00:01:51.640> underpitting<00:01:52.440> underpinnings<00:01:53.040> of<00:01:53.160> that<00:01:53.840> interface,<00:01:54.960> we<00:01:55.080> thought<00:01:55.240> it<00:01:55.320> was<00:01:55.400> going<00:01:55.520> to<00:01:55.600> take<00:01:55.800> 12<00:01:56.160> months,<00:01:56.440> took<00:01:56.600> 6<00:01:56.840> months. 00:01:58.000 --> 00:02:06.200 Uh<00:01:58.720> you<00:01:58.840> know,<00:01:59.520> and<00:01:59.800> and<00:01:59.960> this<00:02:00.080> is<00:02:00.280> real<00:02:00.600> like<00:02:00.800> designers<00:02:01.400> saying<00:02:01.840> I'm<00:02:02.080> doing<00:02:02.800> in<00:02:02.960> a<00:02:03.040> day<00:02:03.520> what<00:02:03.680> I<00:02:03.760> could<00:02:03.960> do<00:02:04.320> in<00:02:04.479> 2<00:02:04.640> weeks<00:02:04.960> before. 00:02:06.200 --> 00:02:09.759 So,<00:02:06.600> just<00:02:06.880> in<00:02:07.040> our<00:02:07.200> own<00:02:07.360> productivity<00:02:07.960> it<00:02:08.080> changes<00:02:08.479> quite<00:02:08.840> a<00:02:08.880> bit. 00:02:09.759 --> 00:02:16.920 And<00:02:09.960> then<00:02:10.240> in<00:02:10.399> our<00:02:10.560> own<00:02:10.720> platform<00:02:11.440> we're<00:02:11.560> able<00:02:11.760> to<00:02:11.880> automate<00:02:12.400> things<00:02:12.800> before<00:02:13.200> that<00:02:13.400> were<00:02:13.520> manual<00:02:14.200> and<00:02:14.320> laborious,<00:02:15.480> all<00:02:15.720> using<00:02:16.040> AI<00:02:16.320> technology. 00:02:16.920 --> 00:02:25.760 And<00:02:17.000> then<00:02:17.560> the<00:02:17.680> other<00:02:17.840> part<00:02:18.120> of<00:02:18.160> this<00:02:18.360> is<00:02:18.480> we've<00:02:18.680> got<00:02:18.959> a<00:02:19.000> massive<00:02:19.560> repository<00:02:20.640> of<00:02:20.920> data<00:02:21.880> and<00:02:22.000> the<00:02:22.120> idea<00:02:22.440> of<00:02:22.520> surfacing<00:02:23.040> it<00:02:23.200> insights<00:02:23.840> real<00:02:24.040> time,<00:02:24.280> which<00:02:24.400> we<00:02:24.480> can<00:02:24.640> now<00:02:24.840> do 00:02:25.760 --> 00:02:28.200 uh<00:02:26.080> via<00:02:26.440> our<00:02:26.720> our<00:02:27.000> agent<00:02:27.360> Ivy. 00:02:28.200 --> 00:02:35.040 I<00:02:28.320> mean,<00:02:28.520> all<00:02:28.720> of<00:02:28.800> that<00:02:29.120> is<00:02:29.240> just<00:02:29.440> changing<00:02:29.840> the<00:02:29.920> whole<00:02:30.160> experience<00:02:30.920> for<00:02:31.080> marketers<00:02:31.640> to<00:02:31.760> connect<00:02:32.680> uh<00:02:32.800> with<00:02:32.959> users. 00:02:35.040 --> 00:02:36.840 It's<00:02:35.280> wild.<00:02:35.560> Where<00:02:35.680> do<00:02:35.760> you<00:02:35.840> think<00:02:36.040> we're<00:02:36.160> going<00:02:36.480> with<00:02:36.720> it? 00:02:36.840 --> 00:02:42.040 I<00:02:36.880> mean,<00:02:37.080> obviously<00:02:38.080> the<00:02:38.240> answer<00:02:38.480> to<00:02:38.520> that<00:02:38.720> question<00:02:39.120> is<00:02:39.720> the<00:02:39.800> future<00:02:40.120> of<00:02:40.160> the<00:02:40.240> world,<00:02:40.680> but<00:02:41.280> what's<00:02:41.440> your<00:02:41.560> take? 00:02:42.040 --> 00:02:48.480 Well,<00:02:42.320> I<00:02:42.400> think,<00:02:42.680> you<00:02:42.760> know,<00:02:43.240> uh<00:02:43.480> I<00:02:43.680> I<00:02:43.800> do<00:02:44.040> think<00:02:44.280> there<00:02:44.440> will<00:02:44.600> be<00:02:45.120> uh<00:02:45.240> agents<00:02:45.760> that<00:02:45.959> will<00:02:46.120> interface<00:02:46.680> with<00:02:46.800> brands<00:02:47.160> on<00:02:47.240> our<00:02:47.320> behalf. 00:02:48.480 --> 00:02:56.480 And<00:02:48.600> we're<00:02:48.680> going<00:02:48.800> to<00:02:48.840> have<00:02:48.959> to<00:02:49.080> figure<00:02:49.440> out<00:02:50.120> how<00:02:50.360> 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of<00:04:17.760> mine,<00:04:18.000> I'm<00:04:18.120> like<00:04:18.280> that<00:04:18.440> must<00:04:18.640> be<00:04:18.760> like<00:04:18.880> a<00:04:18.959> high<00:04:19.079> school<00:04:19.400> yearbook<00:04:19.840> photo<00:04:20.160> cuz<00:04:20.320> that<00:04:20.519> isn't<00:04:21.519> what<00:04:21.640> this<00:04:21.799> person<00:04:22.080> looks<00:04:22.320> like<00:04:22.480> today. 00:04:24.320 --> 00:04:30.080 So,<00:04:24.960> yeah,<00:04:25.200> I<00:04:25.240> don't<00:04:25.400> I<00:04:25.640> think<00:04:25.880> it's<00:04:26.080> it's<00:04:26.280> changing<00:04:27.360> pretty<00:04:27.640> dramatically<00:04:28.320> right<00:04:28.480> in<00:04:28.560> front<00:04:28.720> of<00:04:28.800> our<00:04:28.880> very<00:04:29.240> eyes. 00:04:30.080 --> 00:04:32.760 It's<00:04:30.360> wild.<00:04:30.960> And<00:04:31.080> then<00:04:31.320> like<00:04:31.560> what<00:04:31.680> do<00:04:31.760> you<00:04:31.880> do<00:04:32.120> at<00:04:32.240> that<00:04:32.480> point? 00:04:32.760 --> 00:04:36.560 I<00:04:32.840> don't<00:04:32.960> know.<00:04:33.160> It's<00:04:33.560> it's<00:04:33.800> really<00:04:34.040> interesting.<00:04:34.880> So,<00:04:35.000> how<00:04:35.120> many<00:04:35.240> employees<00:04:35.560> do<00:04:35.600> you<00:04:35.680> guys<00:04:35.840> have? 00:04:36.560 --> 00:04:39.960 Uh<00:04:36.720> we're<00:04:36.840> about<00:04:37.040> 300<00:04:37.400> people.<00:04:38.480> So,<00:04:38.560> that<00:04:38.680> that's<00:04:38.960> a<00:04:39.000> sizeable<00:04:39.600> company. 00:04:39.960 --> 00:04:47.720 Do<00:04:40.080> you<00:04:40.240> do<00:04:40.360> you<00:04:40.520> see<00:04:40.840> it<00:04:41.000> as<00:04:41.280> like<00:04:42.400> um<00:04:43.320> making<00:04:43.760> you<00:04:43.919> better<00:04:44.560> and<00:04:44.720> more<00:04:44.919> efficient<00:04:45.400> to<00:04:45.480> the<00:04:45.600> point<00:04:45.880> where<00:04:46.160> you<00:04:46.320> won't<00:04:46.560> need<00:04:46.760> as<00:04:46.880> many<00:04:47.040> people<00:04:47.280> in<00:04:47.360> the<00:04:47.400> future? 00:04:47.720 --> 00:04:52.360 Do<00:04:47.840> you<00:04:47.960> see<00:04:48.240> it<00:04:48.360> as<00:04:48.560> just<00:04:48.800> like<00:04:49.000> hey<00:04:49.160> that<00:04:49.360> 300<00:04:49.720> people<00:04:50.000> now<00:04:50.240> can<00:04:50.400> do<00:04:51.160> 10<00:04:51.400> times<00:04:51.720> the<00:04:51.840> work? 00:04:52.360 --> 00:04:54.560 Or<00:04:52.520> how<00:04:52.640> are<00:04:52.720> you<00:04:52.840> thinking<00:04:53.200> about<00:04:53.400> the<00:04:53.480> culture<00:04:53.919> of<00:04:54.040> all<00:04:54.240> of<00:04:54.320> this? 00:04:54.560 --> 00:04:56.640 And<00:04:54.640> how<00:04:54.800> how<00:04:54.960> do<00:04:55.040> you<00:04:55.120> think<00:04:55.280> your<00:04:55.400> employees<00:04:55.840> are<00:04:55.960> feeling<00:04:56.200> about<00:04:56.400> all<00:04:56.480> of<00:04:56.560> it? 00:04:56.640 --> 00:05:04.200 Yeah,<00:04:56.960> I<00:04:57.040> think<00:04:57.520> our<00:04:57.640> employees<00:04:58.120> are<00:04:58.240> feeling<00:04:58.600> pretty<00:04:58.880> empowered<00:04:59.760> because<00:05:00.080> they<00:05:00.200> can<00:05:00.520> do<00:05:00.720> more<00:05:02.160> with<00:05:02.400> technology<00:05:03.000> than<00:05:03.120> we<00:05:03.240> could<00:05:03.440> before. 00:05:04.200 --> 00:05:13.040 And<00:05:04.320> that's<00:05:04.520> not<00:05:04.720> just<00:05:05.080> prod<00:05:05.520> and<00:05:05.720> engineering,<00:05:06.360> that's<00:05:06.600> also<00:05:07.600> ways<00:05:07.960> in<00:05:08.080> which<00:05:08.320> we<00:05:08.440> can<00:05:08.680> use<00:05:08.960> agents<00:05:09.480> to<00:05:10.120> cut<00:05:10.360> down<00:05:10.600> our<00:05:10.720> support<00:05:11.160> ticket<00:05:11.440> requests<00:05:11.919> by<00:05:12.080> 50%,<00:05:12.880> which 00:05:13.040 --> 00:05:20.880 is<00:05:13.160> a<00:05:13.200> real<00:05:13.440> stat<00:05:13.800> for<00:05:14.000> us.<00:05:14.960> In<00:05:15.120> a<00:05:15.200> way<00:05:15.400> that<00:05:15.720> our<00:05:15.840> employees<00:05:16.360> can<00:05:16.520> focus<00:05:16.919> on<00:05:17.080> higher<00:05:17.360> level<00:05:17.640> activities,<00:05:19.520> that's<00:05:19.880> pretty<00:05:20.160> empowering. 00:05:20.880 --> 00:05:25.720 So,<00:05:21.560> I<00:05:21.680> think<00:05:21.919> we'll<00:05:22.160> thoughtfully<00:05:22.880> continue<00:05:23.520> to<00:05:23.919> add<00:05:24.240> employees. 00:05:25.720 --> 00:05:29.120 So,<00:05:25.840> I<00:05:25.880> don't<00:05:26.040> think<00:05:26.200> this<00:05:26.360> is<00:05:26.560> in<00:05:26.720> any<00:05:26.880> way<00:05:27.040> a<00:05:27.120> replacement<00:05:28.240> for<00:05:28.440> employees. 00:05:29.120 --> 00:05:34.160 I<00:05:29.200> think<00:05:29.400> it's<00:05:29.520> just<00:05:29.680> a<00:05:29.760> way<00:05:30.120> to<00:05:30.280> more<00:05:30.440> thoughtfully<00:05:30.960> put<00:05:31.160> people<00:05:31.480> in<00:05:31.600> roles<00:05:31.880> where<00:05:32.000> they<00:05:32.080> can<00:05:32.200> make<00:05:32.360> a<00:05:32.400> bigger<00:05:32.640> impact. 00:05:34.160 --> 00:05:41.160 And<00:05:34.320> how<00:05:34.440> do<00:05:34.520> you<00:05:34.640> think<00:05:34.800> about<00:05:35.040> culture?<00:05:35.560> How<00:05:35.720> have<00:05:35.880> you<00:05:35.960> thought<00:05:36.160> about<00:05:36.480> like,<00:05:36.919> for<00:05:37.040> example,<00:05:37.800> the<00:05:37.960> work<00:05:38.240> from<00:05:38.440> home,<00:05:38.960> the<00:05:39.080> hybrid,<00:05:39.800> or<00:05:40.000> everybody<00:05:40.360> at<00:05:40.440> the<00:05:40.600> office? 00:05:41.160 --> 00:05:45.120 Like<00:05:41.760> how<00:05:41.880> do<00:05:41.960> you<00:05:42.080> build<00:05:42.280> a<00:05:42.360> culture,<00:05:43.200> you<00:05:43.320> know,<00:05:43.520> in<00:05:43.600> the<00:05:43.720> post-COVID<00:05:44.320> world? 00:05:45.120 --> 00:05:51.040 You<00:05:45.200> know,<00:05:45.360> that's<00:05:45.640> that's<00:05:45.960> that's<00:05:46.160> something<00:05:46.480> we're<00:05:46.640> all<00:05:46.800> trying<00:05:47.040> to<00:05:47.120> figure<00:05:47.480> out<00:05:47.800> and<00:05:47.920> I<00:05:47.960> think<00:05:48.720> what<00:05:48.880> we've<00:05:49.080> sort<00:05:49.320> of<00:05:49.400> landed<00:05:49.800> on<00:05:50.000> which<00:05:50.200> seems<00:05:50.440> to<00:05:50.520> be<00:05:50.640> working 00:05:51.040 --> 00:05:56.840 well<00:05:51.320> for<00:05:51.600> us<00:05:52.120> is<00:05:52.560> finding<00:05:53.080> those<00:05:53.400> times<00:05:53.880> where<00:05:54.040> you<00:05:54.240> just<00:05:54.560> need<00:05:54.760> to<00:05:54.840> get<00:05:55.040> together<00:05:55.520> as<00:05:55.680> a<00:05:55.720> team. 00:05:56.840 --> 00:06:04.560 Uh<00:05:57.160> I<00:05:57.280> will<00:05:57.440> tell<00:05:57.640> 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connection<00:06:26.120> points<00:06:26.480> for<00:06:26.600> your<00:06:26.720> remote<00:06:27.080> employees,<00:06:27.640> too. 00:06:28.400 --> 00:06:32.080 Whether<00:06:28.760> that<00:06:29.080> be,<00:06:29.760> you<00:06:29.840> know,<00:06:30.000> things<00:06:30.480> that<00:06:30.640> you<00:06:30.760> can<00:06:30.919> do<00:06:31.120> as<00:06:31.280> a<00:06:31.320> company. 00:06:32.080 --> 00:06:39.240 Uh<00:06:32.880> uh<00:06:33.080> when<00:06:33.240> we<00:06:33.360> hit<00:06:33.520> our<00:06:33.600> 12-year<00:06:34.080> anniversary,<00:06:34.720> we<00:06:34.840> sent<00:06:35.160> out<00:06:35.520> uh<00:06:36.040> a<00:06:36.120> bunch<00:06:36.560> of<00:06:36.919> um<00:06:37.440> coupons<00:06:38.000> for<00:06:38.120> our<00:06:38.240> current<00:06:38.560> customers. 00:06:39.240 --> 00:06:46.680 We<00:06:39.360> have<00:06:39.480> a<00:06:39.520> bunch<00:06:39.720> of<00:06:39.760> QSR<00:06:40.280> customers,<00:06:41.280> bunch<00:06:41.480> 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from<00:06:54.960> leadership. 00:06:56.000 --> 00:07:02.560 So,<00:06:56.240> we're<00:06:56.320> also<00:06:56.600> trying<00:06:56.919> to<00:06:57.080> find<00:06:57.320> those<00:06:57.720> core<00:06:58.040> anchor<00:06:58.320> tenants<00:06:58.720> where<00:06:58.840> we<00:06:58.919> can<00:06:59.000> get<00:06:59.160> people<00:06:59.440> together<00:07:00.040> and<00:07:00.640> and<00:07:00.760> hopefully<00:07:01.120> inspire<00:07:01.600> them<00:07:01.840> with<00:07:01.960> the<00:07:02.040> direction<00:07:02.400> we're 00:07:02.560 --> 00:07:06.560 going<00:07:02.760> as<00:07:02.880> a<00:07:02.919> company.<00:07:04.160> What<00:07:04.360> does<00:07:04.480> a<00:07:04.520> typical<00:07:04.960> day<00:07:05.160> look<00:07:05.360> like<00:07:05.560> for<00:07:05.680> you? 00:07:06.560 --> 00:07:12.960 Yeah.<00:07:07.280> Uh<00:07:07.480> I<00:07:07.600> you<00:07:07.680> know,<00:07:07.880> part<00:07:08.120> of<00:07:08.200> the<00:07:08.280> reason<00:07:08.560> 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We've<00:07:23.800> got<00:07:24.000> folks<00:07:24.280> in<00:07:24.400> Dubai.<00:07:25.520> So,<00:07:25.760> for<00:07:25.919> me,<00:07:26.400> it<00:07:26.640> it's<00:07:26.880> really<00:07:27.720> trying<00:07:28.040> to<00:07:28.120> figure<00:07:28.480> out<00:07:28.720> how<00:07:28.840> I'm<00:07:28.919> going<00:07:29.040> to<00:07:29.120> allocate<00:07:29.560> my<00:07:29.720> time<00:07:30.120> that<00:07:30.400> day. 00:07:31.600 --> 00:07:39.960 Always<00:07:32.000> with<00:07:32.120> a<00:07:32.200> focus<00:07:32.600> first<00:07:32.960> on<00:07:33.080> customers<00:07:34.440> uh<00:07:34.680> cuz<00:07:34.800> I<00:07:34.840> think<00:07:34.960> it's<00:07:35.200> easy<00:07:35.800> in<00:07:36.000> a<00:07:36.080> role<00:07:36.400> like<00:07:36.600> the<00:07:36.680> CEO<00:07:37.280> to<00:07:37.440> get<00:07:37.600> lost<00:07:38.000> and<00:07:38.120> get<00:07:38.400> separated<00:07:39.040> or<00:07:39.160> further<00:07:39.520> away<00:07:39.760> from 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00:13:10.080 Well,<00:13:06.600> I<00:13:06.640> think<00:13:06.839> I<00:13:06.920> think<00:13:07.080> it<00:13:07.160> depends,<00:13:07.760> really.<00:13:08.040> It<00:13:08.120> depends<00:13:08.520> on<00:13:08.600> what<00:13:08.720> your<00:13:08.880> business<00:13:09.360> is. 00:13:10.080 --> 00:13:14.520 You<00:13:10.160> know,<00:13:10.280> if<00:13:10.440> you<00:13:10.560> skew<00:13:10.920> younger,<00:13:11.360> you're<00:13:11.480> going<00:13:11.600> to<00:13:11.680> go<00:13:11.839> for<00:13:11.960> the<00:13:12.040> social<00:13:12.400> media<00:13:12.760> channels,<00:13:13.280> for<00:13:13.440> sure. 00:13:14.520 --> 00:13:17.400 [Uh]<00:13:14.600> emerging<00:13:14.960> brands,<00:13:15.600> same<00:13:15.880> sort<00:13:16.120> of<00:13:16.240> thing. 00:13:17.400 --> 00:13:20.160 [Uh]<00:13:17.520> depends<00:13:18.160> on<00:13:18.560> on<00:13:18.800> your<00:13:18.960> vertical. 00:13:20.160 --> 00:13:26.960 [Uh]<00:13:20.455> you<00:13:20.750> 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but<00:16:49.760> yeah,<00:16:50.120> getting<00:16:50.400> that<00:16:50.640> first<00:16:50.920> break<00:16:51.280> to<00:16:51.360> do<00:16:51.520> something<00:16:52.160> at<00:16:52.400> massive 00:16:52.800 --> 00:17:00.440 scale<00:16:54.000> [uh]<00:16:54.160> thousands<00:16:54.640> of<00:16:54.720> employees,<00:16:55.440> billions<00:16:55.839> of<00:16:55.920> dollars,<00:16:56.440> like<00:16:56.760> for<00:16:56.920> me<00:16:57.120> that<00:16:57.280> was<00:16:57.440> probably<00:16:58.400> an<00:16:58.520> inflection<00:16:59.040> point<00:16:59.240> in<00:16:59.320> my<00:16:59.440> career. 00:17:00.440 --> 00:17:03.440 Yeah,<00:17:00.600> that's<00:17:00.839> huge.<00:17:01.440> David,<00:17:01.800> thank<00:17:02.000> you<00:17:02.080> so<00:17:02.320> much<00:17:02.640> for<00:17:02.760> coming<00:17:03.000> on<00:17:03.080> the<00:17:03.160> show. 00:17:03.440 --> 00:17:08.720 What<00:17:03.600> an<00:17:03.720> honor<00:17:03.920> to<00:17:04.000> have<00:17:04.240> you.<00:17:04.439> Congratulations<00:17:05.199> on<00:17:05.280> everything<00:17:05.600> you're<00:17:05.720> building<00:17:06.280> and<00:17:06.880> hey,<00:17:07.079> happy<00:17:07.360> Thanksgiving<00:17:08.160> too. 00:17:08.720 --> 00:17:12.760 And<00:17:08.880> to<00:17:09.000> you<00:17:09.160> too<00:17:09.360> Clint.<00:17:09.600> Thanks<00:17:09.839> so<00:17:09.920> much.<00:17:10.199> I<00:17:10.280> appreciate<00:17:10.760> it. ``` ### Anthropic called Mythos a cyberweapon, government agreed URL: https://www.ceo.com/blog/anthropic-called-mythos-a-cyberweapon-government-agreed/ Last updated: 2026-08-14T00:17:33.000Z At 5:21 p.m. Eastern on June 12, 2026, Anthropic received a letter from the Commerce Department. The company says it was given ninety minutes to pull its newest model. By nightfall, it had taken both of its most powerful AI systems offline for every customer worldwide. Claude Fable 5 and Claude Mythos 5 had [launched three days earlier](https://www.anthropic.com/news/claude-fable-5-mythos-5?ref=ceo.com). Mythos went to a small set of vetted security partners. Fable, the same model under a layer of safeguards, went to the public. It was the [first time](https://www.nbcnews.com/tech/tech-news/anthropic-suspends-new-ai-models-fable-mythos-government-directive-rcna349901?ref=ceo.com) a leading AI company had pulled a publicly deployed model because the government told it to. The mechanism was export control. [Anthropic's statement](https://www.anthropic.com/news/fable-mythos-access?ref=ceo.com) said the government, citing national security authorities, barred any foreign national from using the models, whether outside or inside the United States. The order reached Anthropic's own foreign-born engineers. It reached foreign nationals working at American desks. The [letter came from](https://cyberscoop.com/us-government-anthropic-fable-5-mythos-5-export-controls/?ref=ceo.com) Commerce Secretary Howard Lutnick and went to CEO Dario Amodei. The legal theory appears to be the deemed export rule, which treats showing controlled technology to a foreign person as an export to their home country. It was written for semiconductor and encryption applications. Chris McGuire of the Council on Foreign Relations, who [reviewed the move](https://www.newsweek.com/trumps-ban-on-foreign-access-to-new-anthropic-models-sparks-tech-backlash-12070846?ref=ceo.com), allowed that targeted controls could be prudent but called applying deemed export to foreign nationals inside the country "just absurd," and said it would force the model out of distribution, which is what happened. Anthropic could not filter by citizenship in real time across its accounts and APIs, so it shut down the models for everyone. New requests now route to [Claude Opus 4.8](https://venturebeat.com/technology/anthropic-blocks-all-public-access-to-claude-fable-5-mythos-5-following-us-government-order-what-enterprises-should-do?ref=ceo.com). Every other Claude model stayed up. ## Two Accounts [Anthropic complied and disagreed](https://www.anthropic.com/news/fable-mythos-access?ref=ceo.com) in the same statement. The letter gave no detail; it said. It was understood that someone had found a way to jailbreak Fable 5: ask the model to read a codebase and flag software flaws. The vulnerabilities that surfaced were minor and already known, and other public models find the same ones with no jailbreak at all, including OpenAI's GPT-5.5. No tester had found a universal jailbreak, one that broadly defeats the safeguards. Perfect resistance is not possible for any model, Anthropic argued, and a narrow flaw does not justify recalling a product used by hundreds of millions. Apply that standard to everyone, the company said, and you stop frontier AI deployment across the industry. The White House told it differently, using Anthropic's own words. David Sacks, who co-chairs the President's Council of Advisors on Science and Technology, [gave the administration's version](https://x.com/DavidSacks/status/2065853007619588171?ref=ceo.com) on X. Fable is Mythos with guardrails. When the guardrails fail, Mythos and its cyber capabilities reach people who should not have them. Anthropic had spent months calling Mythos a cyberweapon and asking Washington to regulate it as one. A trusted partner testing Fable found a jailbreak. The administration asked Amodei to fix it or pull the model. In Sacks's words, "Dario refused." Anthropic prioritized its consumer product over safety, Sacks wrote, calling that at odds with everything the company says it stands for. The export control followed reluctantly. Patch the flaw, and it lifts. One day before the shutdown, Amodei had published an essay, ["Policy on the AI Exponential,"](https://www.anthropic.com/policy-on-the-ai-exponential?ref=ceo.com) arguing that the government should hold legal authority to block or reverse the release of frontier models that fail safety testing. He compared it to the FAA grounding of unsafe aircraft. When the government blocked his, Anthropic called the process improper. Two facts sit underneath both accounts. The partner who reported the jailbreak was, by [multiple accounts](https://fortune.com/2026/06/14/how-a-warning-from-amazon-led-the-white-house-to-shut-down-anthropics-mythos-model/?ref=ceo.com), Amazon: Anthropic's largest investor and its main cloud host. Amazon CEO Andy Jassy raised it with senior officials after his researchers prompted the model into producing restricted attack information. Whether Amazon tested Fable on its own or at the government's request is not known. The other is China. Semafor reported the White House acted [partly on suspicion](https://www.semafor.com/article/06/13/2026/white-house-move-to-limit-anthropic-linked-to-concerns-about-chinese-access-to-mythos?ref=ceo.com) that a China-linked group had reached Mythos. Anthropic told the outlet that the White House never raised Chinese access in its talks and that it blocks access to its products from inside China. The [NSA had been given Mythos 5](https://cyberscoop.com/us-government-anthropic-fable-5-mythos-5-export-controls/?ref=ceo.com) for offensive cyber operations, which leaves the order pointing partly at the government's own supply. The capability is not in dispute. In Mythos Preview's first month, Mozilla [found and fixed 271 vulnerabilities](https://hacks.mozilla.org/2026/05/behind-the-scenes-hardening-firefox/?ref=ceo.com) in Firefox using the model, more than ten times what Claude had found earlier. What people argue about is the guardrails. Peter Girnus, a software threat researcher, [put it plainly](https://www.newsweek.com/trumps-ban-on-foreign-access-to-new-anthropic-models-sparks-tech-backlash-12070846?ref=ceo.com) on X: "If you describe your product as a munition in every press release, eventually a government takes you at your word." ## Before this The shutdown landed in the middle of a fight already in court. In March, the Pentagon [labeled Anthropic a supply chain risk](https://techcrunch.com/2026/03/05/its-official-the-pentagon-has-labeled-anthropic-a-supply-chain-risk/?ref=ceo.com), a designation built for foreign adversaries, after the company refused to let the military use Claude for mass surveillance or fully autonomous weapons. Anthropic [sued](https://www.npr.org/2026/03/09/nx-s1-5742548/anthropic-pentagon-lawsuit-amodai-hegseth?ref=ceo.com). A California judge blocked the label. The D.C. Circuit [let it stand](https://www.hsfkramer.com/insights/2026-04/same-prompt-different-responses-anthropic-supply-chain-risk-designation-stands-in-dc-circuit-for-now-splitting-from-california-district-court?ref=ceo.com) and heard arguments in May, with the panel split. Sacks says the Fable order has nothing to do with any of it. Anthropic has not said the same. ### Savvi Financial Co-Founder & CEO Gina Mourtzinou: How AI is transforming financial wellness URL: https://www.ceo.com/episodes/savvi-financial-co-founder-ceo-gina-mourtzinou-how-ai-is-transforming-financial-wellness/ Last updated: 2026-08-22T21:31:18.000Z # What AI can't do with your money Gina Mourtzinou managed mutual funds through the financial crisis, and by the standard her industry uses to judge itself, she did well. Her funds beat their benchmarks. She received a bonus in 2008\. Her clients lost anyway, some because they lacked liquidity when markets fell, others because they panicked, sold, and missed the recovery that followed. "People don't necessarily need investment alpha as much as they need sound financial planning and advice," she told the CEO.com Podcast. The problem is that most Americans never get that advice. Only [27 percent work with a financial advisor](https://yougov.com/en-us/articles/50180-27-americans-use-financial-advisors-60-prioritizing-trust-as-the-top-factor?ref=ceo.com), according to YouGov, and usage climbs steeply with education: 19 percent of Americans with some college but no degree, 45 percent of those with postgraduate degrees. The people who need guidance most are the least likely to receive it. Mourtzinou's answer was to look at where ordinary Americans actually make their biggest financial decisions: at work, once a year, during benefits enrollment, usually alone and usually guessing. Which medical plan. HSA or FSA. How much toward retirement, how much toward emergency savings, whether supplemental coverage is worth it. That is the problem [Savvi Financial](https://www.savvifi.com/company?ref=ceo.com) exists to solve. The Waltham, Massachusetts company she co-founded and runs as CEO builds analytics tools that turn those decisions into personalized guidance, delivered through the HR systems employers already use. By 2025, the company had [guided more than 600,000 users](https://www.savvifi.com/company?ref=ceo.com). It operates as an [SEC-registered investment advisor](https://www.savvifi.com/legal/form-adv?ref=ceo.com), and its [founding team is five Ph.D.s](https://www.savvifi.com/company?ref=ceo.com), which tells you something about the approach. The pedigree runs back decades. Mourtzinou studied engineering at the National Technical University of Athens, earned her doctorate in operations research at MIT, and [co-founded Dynamic Ideas](https://www.savvifi.com/company?ref=ceo.com), a portfolio optimization firm, with Dimitris Bertsimas, the MIT professor [whose curriculum vitae lists her 1995 thesis](https://www.mit.edu/~dbertsim/cv.pdf?ref=ceo.com) under his supervision and who won the [2019 INFORMS John von Neumann Theory Prize](https://www.informs.org/Recognizing-Excellence/INFORMS-Prizes/John-von-Neumann-Theory-Prize?ref=ceo.com). American Express acquired the business in 2002 and turned the team into its boutique quant group, where they grew global allocation strategies to $12 billion in assets under management. The core team regrouped, and Savvi followed in 2013. Given that history, her view of AI carries some weight, and it cuts against the industry's current mood. She uses it daily for onboarding, coding, and explaining financial concepts to clients. She does not believe it can do the actual work. "AI can't determine the best benefits plan for your family or exactly how much you should contribute to retirement," she said. "Those are optimization problems that require additional techniques." A chatbot can retrieve information and communicate it well, but it does not know your household, your complete financial picture, or what you can afford to lose, and it makes mistakes. "When you point out the mistake, it's much nicer than my kids. It apologizes and tells me I'm right. But it's still a mistake." Her firmest line is on data. Savvi works with claims data and other sensitive information, and she argues the industry should act more like fiduciaries than platforms: "We should never trade privacy for convenience." Her advice for fellow CEOs is the same advice she gives everyone, and she admits she sometimes fails to follow it herself. Sit down. Define the goals: when to retire, whether to travel, what to leave behind. Build a plan robust enough to survive both markets and life. Heading into 2026, the quant's market outlook amounts to diversification, adequate reserves, and humility about models that have not behaved lately. Every CEO.com Podcast conversation ends with the same question, about the chances one gives rather than takes. Mourtzinou's answer went back to a second landline in her family's home in Greece, a number that had previously belonged to an OB-GYN practice and rang constantly with wrong numbers. Twice she answered, heard nothing, and hung up. The third call was MIT's Operations Research Center offering her a position. The caller was Bertsimas, who later told her he had not planned to keep trying. ```chapters 00:00:00 Introduction and Overview of Savvi Financial 00:01:52 Impact of AI on Workflow and Industry 00:04:30 Drawbacks and Cautions of AI in Financial Services 00:05:21 Gina's Background and Inspiration for Founding Savvi Financial 00:08:06 Financial Planning Advice for CEOs and Leaders 00:09:47 A Day in the Life of Gina, CEO of Savvi Financial 00:10:22 Reading Recommendations and Interests 00:11:32 Data Privacy and Security in Fintech 00:13:06 Hybrid Work Model and Company Culture 00:14:50 Macroeconomic Environment and Future Outlook 00:15:59 Reflecting on Opportunities and Mentorship 00:17:19 Closing Remarks and Gratitude ``` ```vtt WEBVTT 00:00:00.000 --> 00:00:02.720 Gina,<00:00:00.680> thank<00:00:00.920> you<00:00:01.040> so<00:00:01.280> much<00:00:01.560> for<00:00:01.720> coming<00:00:02.000> on<00:00:02.120> the<00:00:02.200> show. 00:00:02.720 --> 00:00:06.560 You<00:00:03.000> 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my<00:05:09.760> kids.<00:05:10.120> It<00:05:10.240> says,<00:05:10.440> "I'm<00:05:10.600> so<00:05:10.800> sorry. 00:05:11.560 --> 00:05:14.120 You<00:05:11.680> are<00:05:11.800> so<00:05:12.040> right,<00:05:12.360> but<00:05:13.040> but<00:05:13.120> it<00:05:13.280> was<00:05:13.480> a<00:05:13.520> mistake." 00:05:14.120 --> 00:05:21.320 So,<00:05:14.280> I<00:05:14.360> think<00:05:14.560> people<00:05:14.840> have<00:05:15.040> to<00:05:15.200> double-check<00:05:16.120> and<00:05:16.520> and<00:05:16.720> triple-check<00:05:17.919> um<00:05:18.400> important<00:05:19.800> answers,<00:05:20.320> right? 00:05:21.320 --> 00:05:24.520 <00:05:21.635> Yeah.<00:05:21.950> Yeah,<00:05:22.265> I<00:05:22.580> I<00:05:22.895> think<00:05:23.210> that's<00:05:23.525> exactly<00:05:23.840> right. 00:05:24.520 --> 00:05:27.320 What<00:05:24.760> had<00:05:25.040> you<00:05:25.520> Prior<00:05:25.760> to<00:05:25.840> this,<00:05:26.080> you<00:05:26.200> were<00:05:26.320> 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know,<00:17:15.240> I<00:17:15.360> stayed<00:17:16.760> forever<00:17:17.079> here,<00:17:17.480> so<00:17:17.959> I'm<00:17:18.079> grateful<00:17:18.480> for<00:17:18.640> that. 00:17:19.600 --> 00:17:23.319 That's<00:17:19.880> incredible.<00:17:20.760> Oh<00:17:20.800> my<00:17:20.959> god.<00:17:21.240> Gina,<00:17:21.839> thank<00:17:22.040> you<00:17:22.160> so<00:17:22.280> much<00:17:22.480> for<00:17:22.600> coming<00:17:22.839> on<00:17:22.920> the<00:17:23.000> show. 00:17:23.319 --> 00:17:27.360 What<00:17:23.520> an<00:17:23.640> incredible<00:17:25.120> uh<00:17:25.199> career<00:17:25.600> you've<00:17:25.800> had<00:17:26.280> and<00:17:26.439> continue<00:17:26.839> to<00:17:26.959> have. 00:17:27.360 --> 00:17:31.360 What<00:17:27.480> an<00:17:27.560> incredible<00:17:28.319> thing<00:17:28.560> you<00:17:28.680> built<00:17:28.880> with<00:17:29.000> Savvy<00:17:29.600> and<00:17:30.200> really<00:17:30.480> what<00:17:30.640> an<00:17:30.720> honor<00:17:30.920> to<00:17:31.040> have<00:17:31.200> you. 00:17:31.360 --> 00:17:35.520 Thank<00:17:31.600> you<00:17:31.680> so<00:17:31.800> much.<00:17:32.440> Thank<00:17:32.600> you<00:17:32.720> so<00:17:32.840> much<00:17:33.040> for<00:17:33.160> having<00:17:33.440> me,<00:17:33.520> Clayton. ``` ### Fast Slow Motion Founder & CEO John Burdett: How to build a business that runs without you URL: https://www.ceo.com/episodes/fast-slow-motion-founder-ceo-john-burdett-how-to-build-a-business-that-runs-without-you/ Last updated: 2026-08-22T21:43:27.000Z # The best year of John Burdett's life included cancer and 21 Days in the hospital John Burdett is the founder and CEO of [Fast Slow Motion](https://www.fastslowmotion.com/?ref=ceo.com), a Birmingham, Alabama consulting firm that helps growing businesses scale on Salesforce and HubSpot. He started it in 2014 after years in software engineering and operations. His pitch to clients has always been the same: heroics don't scale, systems do, and a well-built business should not depend on its founder. In January 2025, he got sick. A severe flare-up of ulcerative colitis. He lost 60 pounds in about eight weeks, spent 21 days in the hospital, and had his colon removed in February. Three months later, doctors found Stage 3 melanoma, unrelated to the colitis. "The business ran fine without me," Burdett told the CEO.com Podcast. "Honestly, it probably did better without me, which is both humbling and encouraging." He is now cancer-free and receiving treatment to keep it that way. The company's name came from his son, who threw a ball at him one day, watched him catch it, and said, "Dad, that was like fast slow motion." Burdett bought the domain. He also liked what the phrase meant. A Major League hitter sees a 95-mile-per-hour fastball as manageable because of the work he put in before the pitch. To everyone else, it's a blur. "When you've built the right systems and processes, things slow down, and you can move faster," he said. "When you haven't done that work, everything speeds up, and you slow down." Fast Slow Motion has made the [Inc. 5000 list of fastest-growing private companies four years in a row](https://www.fastslowmotion.com/fast-slow-motion-joins-hubspots-solutions-partner-program/?ref=ceo.com) and has [completed more than 3,000 projects for over 1,500 clients](https://www.fastslowmotion.com/?ref=ceo.com) across all 50 states, Canada, Europe, and the Caribbean. Burdett says the team now numbers about 135 full-time employees. All of them work remotely, and always have, a decision he made at founding. "When COVID hit, most companies had to pivot. We didn't change a thing," he said. "Decide who you are and be consistent. If you're office-only, be office-only. If you're hybrid, be hybrid. If you're remote, be remote." Burdett co-wrote [The Scalable Business Framework](https://fastslowmotion.com/scalable-business-framework/john-burdett/?ref=ceo.com) with Michael A. Johnson. It came out in 2025, shortly after he got sick. The book is built on what he calls the Three Ps. Purpose, a mission bigger than money. People, starting with employees. Profit. "That sounds obvious, but a lot of businesses miss it. If you're not making money, something is wrong with the business model." Systems and processes go on top. He calls the result "driving your business through the windshield instead of the rearview mirror." Fast Slow Motion started in the Salesforce ecosystem and added HubSpot as it matured into a real competitor. Burdett compares the two platforms to a Mercedes and a BMW. The firm [now works across Salesforce, HubSpot, and Claude](https://www.fastslowmotion.com/?ref=ceo.com), and he spends a lot of time talking clients through what AI does and doesn't change. "Fundamentally, good systems, good processes, and good execution will never go away. AI is simply a tool that elevates everything," he said. "AI is good at reading unstructured data, but it also hallucinates when that data isn't organized. If your structured data is clean and you supplement it with unstructured data, you're really positioned to win." Most businesses, he said, are scrambling because their house is not in order. About 12 years ago, exhausted by a career that was successful and not fulfilling, Burdett surrendered everything to God. He is open about his faith and credits it with getting him through the hospital. Gratitude did the rest. "I was thankful it was me and not someone in my family. I was thankful my business was healthy. I was thankful my kids were grown," he said. "I wasn't lying in a hospital bed thinking about money or awards. I was thinking about the people I loved." He calls it the best year of his life, and knows how that sounds. "It didn't matter how hard I worked, how much money I had, or who I knew. I wasn't getting out of the hospital without having my colon removed." Every interview on the CEO.com Podcast ends with the same question: who gave you a chance? Burdett named Steve Atkins, a computer science professor who had started a professional services firm, and Atkins's partners Larry Lilly and Sanjay Singh. They hired him at 21. "They gave me responsibility, mentorship, and room to make mistakes. And believe me, I made plenty," he said. "They invested in me long before I deserved it." Burdett started feeling normal again only a few weeks before the interview, for the first time all year. "When your health gets taken away, you realize how much you took it for granted. Once you get it back, you become a different person. I wake up grateful every morning." ```chapters 00:00:00 Introduction and Welcome 00:00:11 Overview of Fast Slow Motion 00:00:28 Comparing Salesforce and HubSpot 00:01:11 Importance of Data Consolidation 00:01:45 Impact of AI on Business Platforms 00:02:27 Challenges with Data Management 00:02:44 John's Personal Journey and Health Struggles 00:05:38 Coping with Adversity 00:07:53 The Scalable Business Framework 00:09:50 Qualities of a Great Leader 00:11:34 Building Company Culture 00:13:36 Remote Work and Company Flexibility 00:15:50 Origin of the Company Name 00:17:28 Macroeconomic Perspectives 00:20:43 The Importance of Giving and Receiving Chances 00:22:34 Closing Remarks and Health Update ``` ```vtt WEBVTT 00:00:00.000 --> 00:00:02.080 John,<00:00:00.400> thank<00:00:00.600> you<00:00:00.680> so<00:00:00.800> much<00:00:00.960> for<00:00:01.080> coming<00:00:01.400> on<00:00:01.520> the<00:00:01.600> show. 00:00:02.080 --> 00:00:08.160 It's<00:00:02.280> an<00:00:02.360> honor<00:00:02.560> to<00:00:02.680> have<00:00:03.000> you.<00:00:03.200> You<00:00:03.360> are<00:00:03.480> the<00:00:03.680> CEO<00:00:04.520> and<00:00:04.760> founder<00:00:05.520> of<00:00:05.800> Fast<00:00:06.400> Slow<00:00:06.920> Motion. 00:00:08.160 --> 00:00:13.240 Tell<00:00:08.440> us<00:00:08.720> what<00:00:09.000> Fast<00:00:09.280> Slow<00:00:09.560> Motion<00:00:09.840> is.<00:00:10.120> <00:00:10.400> Uh,<00:00:10.680> thanks,<00:00:10.960> Glenn,<00:00:11.240> for<00:00:11.520> having<00:00:11.800> me,<00:00:12.080> first<00:00:12.360> and<00:00:12.640> foremost. 00:00:13.240 --> 00:00:17.240 Uh,<00:00:13.320> Fast<00:00:13.560> Slow<00:00:13.680> Motion<00:00:14.160> is<00:00:14.520> a<00:00:14.600> Salesforce<00:00:15.240> and<00:00:15.360> HubSpot<00:00:15.960> consulting<00:00:16.520> firm. 00:00:17.240 --> 00:00:20.920 We<00:00:17.400> help<00:00:17.600> small<00:00:17.960> businesses<00:00:18.520> become<00:00:18.840> big<00:00:19.120> businesses<00:00:19.720> on<00:00:19.840> those<00:00:20.080> platforms. 00:00:20.920 --> 00:00:28.480 And<00:00:21.160> so,<00:00:21.400> we<00:00:21.600> love<00:00:22.520> helping<00:00:22.880> people<00:00:23.200> grow<00:00:23.520> and<00:00:23.640> scale<00:00:23.960> the<00:00:24.040> right<00:00:24.320> way,<00:00:24.600> making<00:00:25.000> wise<00:00:25.280> decisions<00:00:25.880> with<00:00:25.960> good<00:00:26.160> systems<00:00:26.560> and<00:00:26.680> processes. 00:00:28.480 --> 00:00:33.480 <00:00:28.731> How<00:00:28.982> do<00:00:29.233> you...<00:00:29.484> It's<00:00:29.736> like,<00:00:29.987> obviously,<00:00:30.238> those...<00:00:30.489> Those<00:00:30.740> two<00:00:30.991> platforms<00:00:31.242> are<00:00:31.493> competitors,<00:00:31.744> but<00:00:31.996> they<00:00:32.247> work<00:00:32.498> together<00:00:32.749> as<00:00:33.000> well. 00:00:33.480 --> 00:00:37.680 Like,<00:00:34.080> uh,<00:00:34.480> it...<00:00:34.720> it...<00:00:35.160> 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your<00:00:46.880> business. 00:00:47.720 --> 00:00:52.160 We<00:00:47.840> like<00:00:48.080> both<00:00:48.320> of<00:00:48.400> them<00:00:48.600> because<00:00:48.960> you<00:00:49.040> can<00:00:49.200> scale<00:00:49.640> and<00:00:49.760> grow<00:00:49.960> your<00:00:50.080> business<00:00:50.520> and<00:00:50.640> you'll<00:00:50.760> never<00:00:51.080> outgrow<00:00:51.480> them. 00:00:52.160 --> 00:01:00.240 So,<00:00:52.320> we're<00:00:52.480> big<00:00:52.720> fans<00:00:53.240> that<00:00:53.400> most<00:00:53.680> businesses<00:00:54.240> could<00:00:54.880> should<00:00:55.120> consolidate<00:00:55.840> their<00:00:55.960> tech<00:00:56.280> stacks<00:00:56.800> and<00:00:56.920> put<00:00:57.120> their<00:00:57.240> systems<00:00:57.760> and<00:00:57.880> processes<00:00:58.480> and<00:00:58.600> data's<00:00:58.960> in<00:00:59.040> one<00:00:59.280> place. 00:01:00.240 --> 00:01:04.720 That<00:01:00.549> allows<00:01:00.858> them<00:01:01.167> to<00:01:01.476> have<00:01:01.785> a<00:01:02.095> full<00:01:02.404> 360-degree<00:01:02.713> view<00:01:03.022> of<00:01:03.331> their<00:01:03.640> business. 00:01:04.720 --> 00:01:06.720 And,<00:01:05.480> um,<00:01:05.800> and<00:01:05.920> it<00:01:06.000> works<00:01:06.240> really<00:01:06.440> well. 00:01:06.720 --> 00:01:12.400 And<00:01:06.840> especially<00:01:07.480> in<00:01:07.640> today's<00:01:08.120> AI-driven<00:01:08.840> world,<00:01:09.280> that<00:01:09.520> data<00:01:09.840> consolidation<00:01:10.840> is<00:01:11.120> is<00:01:11.280> huge<00:01:11.640> for<00:01:11.800> businesses. 00:01:12.400 --> 00:01:14.520 So,<00:01:13.080> that's<00:01:13.560> that's<00:01:13.800> what<00:01:13.960> we<00:01:14.120> believe<00:01:14.400> in. 00:01:14.520 --> 00:01:21.960 We<00:01:14.640> started<00:01:15.160> in<00:01:15.240> the<00:01:15.360> Salesforce<00:01:15.920> ecosystem<00:01:16.720> because<00:01:17.040> at<00:01:17.160> the<00:01:17.280> time,<00:01:18.160> they<00:01:18.360> were<00:01:18.560> really<00:01:18.920> the<00:01:19.120> only<00:01:19.400> true<00:01:19.880> scalable<00:01:20.440> platform<00:01:21.040> out<00:01:21.280> there. 00:01:21.960 --> 00:01:30.240 And<00:01:22.271> then<00:01:22.582> over<00:01:22.892> the<00:01:23.203> last<00:01:23.514> few<00:01:23.825> years,<00:01:24.135> HubSpot<00:01:24.446> has<00:01:24.757> emerged<00:01:25.068> as<00:01:25.378> a,<00:01:25.689> like<00:01:26.000> you<00:01:26.311> said,<00:01:26.622> a<00:01:26.932> viable<00:01:27.243> competitor<00:01:27.554> that<00:01:27.865> <00:01:28.175> Yeah,<00:01:28.486> HubSpot,<00:01:28.797> um,<00:01:29.108> is<00:01:29.418> We<00:01:29.729> actually<00:01:30.040> use 00:01:30.240 --> 00:01:32.560 HubSpot<00:01:30.840> over<00:01:31.080> over<00:01:31.240> those<00:01:31.440> two,<00:01:31.560> but<00:01:31.680> they're<00:01:31.800> both<00:01:32.040> great. 00:01:32.560 --> 00:01:35.680 Um,<00:01:33.600> Give<00:01:33.760> me<00:01:33.880> a<00:01:33.920> sense<00:01:34.160> for<00:01:34.280> how<00:01:34.560> AI<00:01:34.880> is<00:01:35.080> changing<00:01:35.480> this. 00:01:35.680 --> 00:01:38.200 You<00:01:35.800> mentioned,<00:01:36.200> like,<00:01:36.600> this<00:01:36.840> AI-driven<00:01:37.560> landscape. 00:01:38.200 --> 00:01:42.320 I<00:01:38.280> mean,<00:01:39.480> 5<00:01:39.760> years<00:01:40.000> from<00:01:40.120> now,<00:01:40.320> do<00:01:40.440> they<00:01:40.600> Do<00:01:40.760> either<00:01:40.960> of<00:01:41.000> these<00:01:41.160> platforms<00:01:41.640> even<00:01:41.800> exist? 00:01:42.320 --> 00:01:45.520 I<00:01:42.360> don't<00:01:42.520> even<00:01:42.720> know,<00:01:43.280> right?<00:01:43.600> Like,<00:01:43.880> AI<00:01:44.120> is<00:01:44.240> changing<00:01:44.600> everything. 00:01:45.520 --> 00:01:53.800 <00:01:45.891> Yeah,<00:01:46.263> yeah.<00:01:46.634> I<00:01:47.006> think<00:01:47.377> I<00:01:47.749> think<00:01:48.120> fundamentally<00:01:48.491> good<00:01:48.863> 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execute<00:02:06.960> well,<00:02:07.440> add<00:02:07.720> value<00:02:08.080> to<00:02:08.200> the<00:02:08.280> marketplace,<00:02:09.000> solve<00:02:09.320> customer<00:02:09.759> problems<00:02:10.399> will 00:02:10.520 --> 00:02:13.080 still<00:02:10.759> be<00:02:10.920> the<00:02:11.040> winners<00:02:11.520> in<00:02:11.720> tomorrow's<00:02:12.240> world. 00:02:13.080 --> 00:02:17.480 It's<00:02:13.280> just<00:02:13.520> the<00:02:13.640> tools<00:02:13.959> are<00:02:14.040> better.<00:02:14.400> We<00:02:14.520> can<00:02:14.640> do<00:02:14.760> things<00:02:15.040> faster<00:02:16.000> and<00:02:16.160> get<00:02:16.360> more<00:02:16.640> things<00:02:17.000> done. 00:02:17.480 --> 00:02:22.480 So,<00:02:17.720> we're<00:02:17.880> very<00:02:18.080> excited<00:02:18.600> about<00:02:18.959> it.<00:02:19.600> But<00:02:19.680> you<00:02:19.760> got<00:02:19.880> to<00:02:19.959> have<00:02:20.080> your<00:02:20.160> data<00:02:20.400> house<00:02:20.640> 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see<00:02:34.120> a<00:02:34.200> lot<00:02:34.400> of<00:02:34.480> businesses,<00:02:34.959> honestly,<00:02:35.360> clear<00:02:35.560> right<00:02:35.720> now<00:02:35.880> scrambling<00:02:36.680> on<00:02:36.920> that<00:02:37.160> because<00:02:37.480> their<00:02:37.640> house<00:02:37.959> is<00:02:38.120> in<00:02:38.280> an<00:02:38.400> order<00:02:39.160> and<00:02:40.200> they<00:02:40.320> need<00:02:40.520> to<00:02:40.600> get<00:02:41.040> it<00:02:41.200> in<00:02:41.360> order 00:02:41.760 --> 00:02:44.760 in<00:02:41.959> order<00:02:42.160> to<00:02:42.280> be<00:02:42.480> able<00:02:42.720> to<00:02:42.800> use<00:02:43.040> AI<00:02:43.320> the<00:02:43.440> right<00:02:43.720> way. 00:02:44.760 --> 00:02:48.080 <00:02:45.013> Yeah.<00:02:45.267> Yeah,<00:02:45.520> for<00:02:45.773> sure.<00:02:46.027> Tell<00:02:46.280> us<00:02:46.533> about<00:02:46.787> your<00:02:47.040> own<00:02:47.293> personal<00:02:47.547> journey,<00:02:47.800> man. 00:02:48.080 --> 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started<00:03:02.249> to<00:03:02.513> help<00:03:02.776> build<00:03:03.040> and 00:03:03.200 --> 00:03:09.519 scale<00:03:03.480> businesses,<00:03:05.120> really<00:03:05.360> kind<00:03:05.560> of<00:03:05.640> did<00:03:05.840> everything<00:03:06.239> my<00:03:06.480> way,<00:03:07.239> had<00:03:07.400> a<00:03:07.440> lot<00:03:07.600> of<00:03:07.680> success,<00:03:08.280> but<00:03:08.400> I<00:03:08.440> was<00:03:08.560> exhausted. 00:03:09.519 --> 00:03:12.519 You<00:03:09.640> know,<00:03:09.760> it<00:03:09.840> just<00:03:10.080> wasn't<00:03:10.480> fulfilling<00:03:11.120> and<00:03:11.280> stuff<00:03:11.519> like<00:03:11.680> that. 00:03:12.519 --> 00:03:20.880 Honestly,<00:03:14.040> I'm<00:03:14.280> I'm<00:03:14.440> a<00:03:14.720> man<00:03:15.000> of<00:03:15.080> faith,<00:03:15.400> so<00:03:15.519> I<00:03:15.600> surrendered<00:03:16.040> everything<00:03:16.400> to<00:03:16.480> God<00:03:16.840> about<00:03:17.080> 12<00:03:17.360> years<00:03:17.600> ago,<00:03:18.320> decided<00:03:18.760> I'm<00:03:18.840> going<00:03:18.959> to<00:03:19.040> do<00:03:19.160> it<00:03:19.280> his<00:03:19.519> way,<00:03:20.239> and<00:03:20.440> then<00:03:20.760> I 00:03:20.880 --> 00:03:29.200 started<00:03:21.400> really<00:03:21.720> fundamentally<00:03:22.480> helping<00:03:23.239> my<00:03:23.519> own<00:03:23.760> businesses<00:03:24.360> do<00:03:24.560> things<00:03:25.000> with<00:03:25.160> good<00:03:25.440> systems<00:03:26.000> and<00:03:26.120> processes<00:03:26.880> and<00:03:26.959> not<00:03:27.160> heroics<00:03:28.519> so<00:03:28.760> that<00:03:29.080> it 00:03:29.200 --> 00:03:37.680 would<00:03:29.360> scale<00:03:29.880> and<00:03:30.000> grow<00:03:30.239> without<00:03:30.680> me.<00:03:31.360> And<00:03:31.880> over<00:03:32.040> the<00:03:32.120> last<00:03:32.480> 10<00:03:32.800> months,<00:03:33.200> honestly,<00:03:33.800> I've<00:03:35.239> unintentionally<00:03:36.120> proven<00:03:36.640> that<00:03:36.920> to<00:03:37.000> be<00:03:37.160> true. 00:03:37.680 --> 00:03:41.000 So,<00:03:37.840> we<00:03:37.959> wrote<00:03:38.200> a<00:03:38.239> book<00:03:38.519> on<00:03:38.720> it<00:03:38.840> called<00:03:39.000> The<00:03:39.080> Scalable<00:03:39.560> Business<00:03:39.920> Framework. 00:03:41.000 --> 00:03:50.000 In<00:03:41.120> the<00:03:41.200> final<00:03:41.560> stages<00:03:42.120> of<00:03:42.160> that<00:03:42.400> manuscript,<00:03:43.920> I<00:03:44.080> had<00:03:45.239> a<00:03:45.320> flare-up<00:03:45.800> of<00:03:45.959> ulcerative<00:03:46.400> colitis<00:03:46.920> in<00:03:47.040> January<00:03:47.760> of<00:03:48.200> 2025. 00:03:50.000 --> 00:03:57.000 We're<00:03:50.120> recording<00:03:50.600> this<00:03:50.840> in<00:03:51.040> November<00:03:51.519> of<00:03:51.640> 2025<00:03:52.920> and<00:03:53.040> had<00:03:53.280> my<00:03:53.760> I<00:03:53.840> lost<00:03:54.080> 60<00:03:54.400> lb<00:03:55.360> in<00:03:55.480> about<00:03:55.720> 8<00:03:55.840> weeks. 00:03:57.000 --> 00:04:05.800 Was<00:03:57.160> hospitalized<00:03:57.800> for<00:03:57.920> 21<00:03:58.360> days.<00:03:59.240> Had<00:03:59.440> my<00:03:59.600> entire<00:04:00.000> colon<00:04:00.400> removed<00:04:01.480> in<00:04:02.160> February<00:04:03.000> of<00:04:03.200> 2025<00:04:04.840> and<00:04:05.080> then 00:04:05.800 --> 00:04:14.760 3<00:04:06.000> months<00:04:06.280> later<00:04:06.680> found<00:04:07.000> out<00:04:07.280> I<00:04:07.360> had<00:04:07.640> stage<00:04:08.040> 3<00:04:08.480> melanoma<00:04:09.040> skin<00:04:09.320> cancer,<00:04:09.760> totally<00:04:10.120> separate<00:04:10.600> disease,<00:04:11.640> and<00:04:12.120> went<00:04:12.360> through<00:04:12.480> that<00:04:12.720> journey<00:04:13.160> and<00:04:13.320> I'm<00:04:13.520> I'm<00:04:13.640> currently<00:04:14.040> cancer-free 00:04:14.760 --> 00:04:22.960 and<00:04:15.000> receiving<00:04:15.680> treatment<00:04:16.160> to<00:04:16.239> make<00:04:16.440> 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without<00:04:32.120> me. 00:04:32.560 --> 00:04:38.280 Honestly,<00:04:33.080> it<00:04:33.320> did,<00:04:33.600> honestly,<00:04:33.919> better<00:04:34.200> without<00:04:34.560> me,<00:04:34.720> which<00:04:34.919> is,<00:04:35.240> you<00:04:35.360> know,<00:04:35.480> both<00:04:35.720> humbling<00:04:36.280> and<00:04:36.560> and<00:04:36.720> good<00:04:36.960> at<00:04:37.040> the<00:04:37.160> same<00:04:37.400> time. 00:04:38.280 --> 00:04:42.000 But<00:04:38.440> I'd<00:04:38.560> also<00:04:38.880> had<00:04:39.080> time<00:04:39.360> to<00:04:39.480> build<00:04:39.720> a<00:04:39.800> business<00:04:40.200> that<00:04:40.360> I<00:04:40.440> loved<00:04:40.919> and<00:04:41.080> enjoyed. 00:04:42.000 --> 00:04:48.600 I<00:04:42.080> didn't<00:04:42.320> miss<00:04:42.560> out<00:04:42.760> on<00:04:42.919> meaningful<00:04:43.400> relationships,<00:04:44.240> which<00:04:44.440> are<00:04:44.600> all<00:04:45.040> all<00:04:45.200> that<00:04:45.280> 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shape<00:04:59.440> spiritually. 00:05:00.480 --> 00:05:06.160 I<00:05:00.600> was<00:05:00.760> in<00:05:00.960> really<00:05:01.160> good<00:05:01.320> shape<00:05:01.880> relationally<00:05:03.000> and<00:05:03.160> I<00:05:03.200> was<00:05:03.480> really<00:05:03.680> good<00:05:03.880> shape,<00:05:04.600> like,<00:05:05.480> physically. 00:05:06.160 --> 00:05:14.760 So<00:05:06.480> I<00:05:06.560> went<00:05:06.800> into<00:05:07.160> it<00:05:07.360> where<00:05:08.440> I<00:05:08.520> was,<00:05:09.320> you<00:05:09.400> know,<00:05:09.480> nobody<00:05:09.840> has<00:05:10.000> 60<00:05:10.320> lb<00:05:10.600> to<00:05:10.680> you<00:05:10.840> lose,<00:05:11.200> maybe,<00:05:11.560> but<00:05:11.840> I<00:05:12.560> I<00:05:12.680> could<00:05:13.000> I<00:05:13.080> could<00:05:13.320> weather<00:05:13.600> that<00:05:13.840> storm<00:05:14.280> enough 00:05:14.760 --> 00:05:17.919 to<00:05:15.000> to<00:05:15.240> recover<00:05:15.919> and<00:05:16.160> get<00:05:16.360> through<00:05:16.680> it<00:05:16.840> and<00:05:17.320> everything. 00:05:17.919 --> 00:05:26.400 So<00:05:18.339> the<00:05:18.759> Scalable<00:05:19.179> Business<00:05:19.599> Framework<00:05:20.019> came<00:05:20.439> out<00:05:20.859> after<00:05:21.279> right<00:05:21.699> after<00:05:22.120> I<00:05:22.540> got<00:05:22.960> sick<00:05:23.380> and<00:05:23.800> so<00:05:24.220> we<00:05:24.640> talked<00:05:25.060> about<00:05:25.480> our<00:05:25.900> principles<00:05:26.320> and 00:05:26.400 --> 00:05:31.800 how<00:05:26.560> we<00:05:26.680> do<00:05:26.880> things<00:05:27.160> and<00:05:27.240> stuff<00:05:27.480> like<00:05:27.640> that<00:05:27.960> and<00:05:28.080> I<00:05:28.120> got<00:05:28.360> to<00:05:28.800> kind<00:05:28.960> of<00:05:29.040> say,<00:05:29.240> yeah,<00:05:29.400> this<00:05:29.640> this<00:05:29.840> actually<00:05:30.160> works. 00:05:31.800 --> 00:05:35.120 <00:05:31.976> What<00:05:32.153> got<00:05:32.329> 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out<00:05:43.280> loud. 00:05:43.960 --> 00:05:46.440 Yeah,<00:05:44.120> my<00:05:44.280> faith<00:05:44.560> first<00:05:44.800> and<00:05:44.919> foremost,<00:05:45.360> God<00:05:45.640> really<00:05:45.880> showed<00:05:46.200> up. 00:05:46.440 --> 00:05:55.040 His<00:05:46.788> presence<00:05:47.137> was<00:05:47.485> with<00:05:47.833> me<00:05:48.182> the<00:05:48.530> entire<00:05:48.878> time<00:05:49.227> and,<00:05:49.575> uh,<00:05:49.923> I<00:05:50.272> really<00:05:50.620> got<00:05:50.968> to<00:05:51.317> experience<00:05:51.665> that,<00:05:52.013> which<00:05:52.362> is,<00:05:52.710> you<00:05:53.058> know,<00:05:53.407> just<00:05:53.755> an<00:05:54.103> experience<00:05:54.452> like<00:05:54.800> I've 00:05:55.040 --> 00:05:58.880 none<00:05:55.240> ever<00:05:55.720> had<00:05:56.080> before,<00:05:56.520> but<00:05:57.160> I<00:05:57.400> I<00:05:57.480> woke<00:05:57.720> up<00:05:57.840> with<00:05:57.960> a<00:05:58.040> heart<00:05:58.200> of<00:05:58.280> gratitude. 00:05:58.880 --> 00:06:03.360 I<00:05:58.920> was<00:05:59.080> thankful<00:05:59.520> for<00:05:59.640> the<00:05:59.720> things<00:06:00.000> that<00:06:00.160> I<00:06:00.240> had.<00:06:00.600> I<00:06:00.640> was<00:06:00.760> so<00:06:00.880> thankful<00:06:01.200> it<00:06:01.280> was<00:06:01.400> me<00:06:01.680> and<00:06:01.800> not<00:06:02.000> somebody<00:06:02.320> in<00:06:02.400> my<00:06:02.520> family. 00:06:03.360 --> 00:06:06.000 I<00:06:03.400> was<00:06:03.520> so<00:06:03.640> thankful<00:06:04.000> for<00:06:04.120> my<00:06:04.320> company<00:06:04.840> and<00:06:05.000> season<00:06:05.320> of<00:06:05.480> life. 00:06:06.000 --> 00:06:12.160 I'd<00:06:06.160> really<00:06:06.400> been<00:06:06.600> prepared<00:06:07.200> for<00:06:07.320> this<00:06:07.560> season<00:06:08.520> and,<00:06:09.280> um,<00:06:09.600> you<00:06:09.680> know,<00:06:09.840> can't<00:06:10.040> imagine<00:06:10.480> had<00:06:10.760> this<00:06:10.920> happening<00:06:11.320> 10<00:06:11.560> years<00:06:11.800> ago. 00:06:12.160 --> 00:06:19.919 My<00:06:12.320> kids<00:06:12.680> were<00:06:13.280> in<00:06:13.400> college,<00:06:14.360> my<00:06:14.480> wife,<00:06:15.400> you<00:06:15.800> know,<00:06:15.880> we're<00:06:16.000> financially<00:06:16.560> stable,<00:06:17.160> the<00:06:17.240> business<00:06:17.600> was<00:06:17.720> doing<00:06:18.040> well,<00:06:18.840> all<00:06:19.040> these<00:06:19.200> kinds<00:06:19.520> of<00:06:19.600> things. 00:06:19.919 --> 00:06:28.200 So,<00:06:20.040> I<00:06:20.080> feel<00:06:20.440> I<00:06:20.560> woke<00:06:20.840> up<00:06:21.000> very<00:06:21.280> grateful<00:06:22.720> that<00:06:23.080> I<00:06:23.160> wasn't<00:06:23.440> in<00:06:23.480> the<00:06:23.600> middle<00:06:23.919> of,<00:06:24.000> like,<00:06:24.200> building<00:06:24.560> this<00:06:24.760> business<00:06:25.240> and<00:06:25.360> stuff<00:06:25.600> like<00:06:25.720> that,<00:06:26.200> 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lot<00:22:01.400> of<00:22:01.480> mistakes<00:22:02.120> and 00:22:02.320 --> 00:22:10.520 boy<00:22:02.560> did<00:22:02.760> I<00:22:02.840> make<00:22:03.040> a<00:22:03.120> lot<00:22:03.720> and<00:22:04.560> uh<00:22:04.920> it<00:22:05.040> was<00:22:05.160> just<00:22:05.320> a<00:22:05.400> blessing<00:22:05.880> to<00:22:06.000> kind<00:22:06.240> of<00:22:06.560> serve<00:22:06.960> under<00:22:07.200> them<00:22:07.480> and<00:22:07.600> work<00:22:07.880> under<00:22:08.120> them<00:22:08.720> and<00:22:09.680> um<00:22:10.320> kind 00:22:10.520 --> 00:22:18.840 of<00:22:10.600> grow<00:22:10.840> myself<00:22:11.560> up<00:22:11.880> to<00:22:12.160> to<00:22:12.520> to<00:22:12.680> the<00:22:12.800> leader<00:22:13.160> that<00:22:13.360> I<00:22:13.440> am<00:22:13.680> today<00:22:14.240> and<00:22:14.440> have<00:22:15.120> have<00:22:15.320> the<00:22:15.480> opportunities<00:22:16.000> that<00:22:16.120> I<00:22:16.200> do<00:22:16.400> today<00:22:16.960> 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health's<00:22:49.160> taken<00:22:49.440> away,<00:22:50.200> you<00:22:50.840> I<00:22:50.920> think<00:22:51.160> health<00:22:51.400> is<00:22:51.520> one<00:22:51.600> of<00:22:51.680> those<00:22:51.800> things<00:22:52.000> you<00:22:52.120> take<00:22:52.480> for<00:22:52.640> granted<00:22:53.000> most<00:22:53.680> and<00:22:54.800> once 00:22:55.040 --> 00:23:01.720 it's<00:22:55.200> away,<00:22:55.640> it's<00:22:55.880> like<00:22:56.160> wow,<00:22:57.240> wow,<00:22:58.000> if<00:22:58.160> I<00:22:58.200> could<00:22:58.400> feel<00:22:58.560> good<00:22:58.720> again<00:22:59.120> and<00:22:59.360> when<00:22:59.520> you<00:22:59.600> do,<00:23:00.520> you're<00:23:00.880> you're<00:23:01.000> a<00:23:01.040> different<00:23:01.320> person. 00:23:01.720 --> 00:23:05.080 So<00:23:01.840> I'm<00:23:02.000> very<00:23:02.240> blessed<00:23:02.680> and<00:23:02.760> wake<00:23:02.920> up<00:23:03.040> very<00:23:03.200> grateful<00:23:03.640> every<00:23:03.800> morning. 00:23:05.080 --> 00:23:08.160 Well,<00:23:05.320> good<00:23:05.520> for<00:23:05.640> you.<00:23:05.840> God<00:23:06.080> bless,<00:23:06.320> my<00:23:06.440> friend.<00:23:06.880> Really<00:23:07.120> appreciate<00:23:07.560> it. 00:23:08.160 --> 00:23:10.640 Thanks<00:23:08.360> for<00:23:08.440> having<00:23:08.640> me. ``` ### Endor Labs Founder & CEO Varun Badhwar: Why AI makes cybersecurity more important than ever URL: https://www.ceo.com/episodes/endor-labs-founder-ceo-varun-badhwar-why-ai-makes-cybersecurity-more-important-than-ever/ Last updated: 2026-10-01T23:20:37.000Z # The end of hidden vulnerabilities For decades, companies made a quiet bet: ship the software now, fix the security later, and hope nobody finds the flaws. Varun Badhwar says the bet is over. "The reality today is that advanced AI systems will find virtually every security issue hidden inside software," the Endor Labs founder and CEO said on the CEO.com Podcast. Anthropic reportedly has a model, Mythos, that it won't release because it finds vulnerabilities too well. Badhwar is unmoved by the restraint. "Whether Anthropic releases Mythos or not doesn't really matter. The capability already exists." OpenAI has it. Google has it. So do open-source labs in China. Defenders have to be right every time. Attackers only have to be right once. Badhwar has spent 20 years building security companies at moments when a technology shift made them necessary. When enterprises moved to SaaS around 2010, he founded CipherCloud. When they moved to the cloud, he founded RedLock, which [Palo Alto Networks bought for approximately $173 million](https://investors.paloaltonetworks.com/news-releases/news-release-details/palo-alto-networks-announces-intent-acquire-redlock?ref=ceo.com) in 2018, three years after its founding. He stayed on to build Prisma Cloud into one of the company's flagship businesses. The shift he saw in 2021 was in how software gets made. "Software development is actually a misnomer," he said. "We should really call it software assembly." Developers no longer write most of their code. They pull it from open-source repositories and, increasingly, generate it with AI models trained on code from across the internet. Some of it is excellent. Some of it is dangerous. Almost none of it comes from a source anyone has vetted. He compares it to a car. A manufacturer knows who supplied every part in a vehicle, where it came from, and how it was built. Software has no such discipline. A [Harvard Business School study](https://www.hbs.edu/ris/Publication%20Files/24-038%5F51f8444f-502c-4139-8bf2-56eb4b65c58a.pdf?ref=ceo.com) put the demand-side value of open-source software at $8.8 trillion, and some of the projects underneath that number have a single maintainer. "Sometimes that's literally one person working out of a garage somewhere," Badhwar said. Compromise that person's account, and the damage cascades through thousands of organizations at once. Attackers have figured this out. Why breach one company when you can poison a component used by all of them? The defensive math is worse than most boards understand. A typical large financial institution carries five to 10 million known security findings, Badhwar told the podcast. He estimates hundreds of billions of lines of code need to be rewritten, possibly trillions. No company employs enough developers for that. His answer is to turn AI on the problem it created: use it to isolate the small fraction of findings that pose real risk, then deploy agents that can read old codebases and automate the fixes. Endor Labs, which he founded with [Dimitri Stiliadis](https://www.endorlabs.com/learn/story-of-endorlabs?ref=ceo.com), raised a [$93 million Series B](https://www.endorlabs.com/learn/why-we-raised-a-93m-series-b-in-this-market?ref=ceo.com) led by DFJ Growth, bringing total funding to [$163 million](https://techcrunch.com/2025/04/23/endor-labs-which-builds-tools-to-scan-ai-generated-code-for-vulnerabilities-lands-93m/?ref=ceo.com). The company says ARR grew 30x over 18 months with 166% net revenue retention, and its platform now protects more than 5 million applications at customers including Rubrik and Mysten Labs. In February, it [acquired Autonomous Plane](https://www.prnewswire.com/news-releases/endor-labs-acquires-autonomous-plane-expanding-ai-native-application-security-with-full-stack-reachability-from-code-to-container-302684888.html?ref=ceo.com), a container security company founded by DockerSlim creator Kyle Quest. Some executives look at all this risk and conclude the answer is to slow down, keep everything on-premises, wait for the technology to settle. Badhwar watched companies try that with cloud computing. They lost. "Trying to slow down adoption isn't a viable strategy," he said. "The better approach is to embrace AI and build the right security controls around it." The same pragmatism shapes his view of the AI race with China, which he considers a misnomer. It is an infrastructure race. Compute requires data centers, data centers require power, and the capacity gets built wherever building happens fastest. He takes the objections to data centers seriously, from electricity demand to water consumption to strained grids, and expects the current phase of unlimited AI spending to end soon. One company he heard about burned through its annual AI budget in a few months. Optimization is coming. Running Endor Labs through all of this, Badhwar now spends roughly half his time on product, more than at any point in his career, because product-market fit shifts too fast to delegate. "One of the biggest mistakes organizations make is assuming that because something didn't work six months ago, it still won't work today," he said. "The willingness to unlearn and relearn has become a critical leadership skill." Every CEO.com interview ends with the same question: who gave you a chance? Badhwar named Vijay Jaju, a KPMG manager who put a 2006 computer science graduate on enterprise security projects at a time when almost nobody hired new graduates into the field. "That chance changed everything," he said. "We still stay in touch today." ```chapters 00:00:00 Introduction and Varun's Background 00:00:39 The Concept of Software Assembly 00:01:10 Security Challenges in Software Development 00:02:30 AI and Cybersecurity Vulnerabilities 00:03:08 Importance of Cybersecurity in the Age of AI 00:04:51 Understanding Software Supply Chain Security 00:08:36 Protecting Against Software Supply Chain Attacks 00:09:09 Open Source Security and OpenClaw 00:11:15 Embedding Security in Software Development 00:12:04 On-Prem vs. Cloud Security 00:13:49 The Scale of Code Rewriting Needed 00:17:34 Public Perception of AI and Data Centers 00:21:40 Token Costs and AI Utilization 00:22:50 The AI Race with China 00:25:15 A Day in the Life of a CEO 00:27:47 Core Principles of Leadership 00:30:19 The Importance of Giving and Taking Chances 00:31:43 Closing Remarks and Gratitude ``` ```vtt WEBVTT 00:00:00.240 --> 00:00:02.240 Varun,<00:00:00.880> thank<00:00:00.960> you<00:00:01.120> so<00:00:01.280> 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forward<00:02:29.280> to<00:02:29.440> this<00:02:29.599> conversation. 00:02:30.720 --> 00:02:33.360 Well,<00:02:30.959> yeah,<00:02:31.200> we're<00:02:31.440> talking<00:02:31.680> at<00:02:31.840> a<00:02:32.080> really<00:02:32.319> interesting<00:02:32.720> time,<00:02:33.040> right? 00:02:33.360 --> 00:02:41.040 Like,<00:02:33.760> uh,<00:02:33.920> Anthropic<00:02:34.640> says<00:02:34.800> they<00:02:35.040> have<00:02:35.120> this<00:02:35.440> model<00:02:35.760> called<00:02:36.080> Mythos,<00:02:37.120> um,<00:02:37.920> that<00:02:38.319> they<00:02:38.560> don't<00:02:38.720> even<00:02:38.879> dare<00:02:39.200> release<00:02:39.599> publicly 00:02:41.040 --> 00:02:44.400 because<00:02:41.280> of<00:02:41.440> the<00:02:41.680> vulnerabilities<00:02:42.400> it's<00:02:42.640> finding<00:02:43.200> in<00:02:43.519> software. 00:02:44.400 --> 00:02:50.640 I<00:02:44.720> assume,<00:02:45.599> um,<00:02:46.319> one<00:02:46.480> or<00:02:46.640> two<00:02:46.800> 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there's<00:04:19.040> plenty<00:04:19.280> of<00:04:19.440> low-hanging<00:04:20.000> fruit,<00:04:20.320> candidly. 00:04:21.040 --> 00:04:29.360 So<00:04:21.199> I<00:04:21.359> think<00:04:21.440> Mythos<00:04:22.000> really<00:04:22.160> sets<00:04:22.479> the<00:04:22.639> tone<00:04:22.960> for,<00:04:24.160> hey,<00:04:24.479> like<00:04:24.720> we<00:04:24.960> can<00:04:25.199> no<00:04:25.440> longer<00:04:26.400> ship<00:04:26.880> software<00:04:27.680> with<00:04:27.919> security<00:04:28.320> vulnerabilities<00:04:29.120> because 00:04:29.360 --> 00:04:32.720 it<00:04:29.680> will<00:04:29.919> get<00:04:30.080> found.<00:04:30.639> I<00:04:30.800> think<00:04:30.880> it's<00:04:31.120> a<00:04:31.360> complete<00:04:31.840> mindset<00:04:32.320> shift. 00:04:32.720 --> 00:04:36.960 It's<00:04:32.960> a<00:04:33.120> complete<00:04:33.440> rewrite<00:04:34.240> of<00:04:34.479> how<00:04:34.720> we've<00:04:34.880> thought<00:04:35.120> about<00:04:35.280> software<00:04:35.840> security. 00:04:36.960 --> 00:04:42.479 It<00:04:37.199> is<00:04:37.360> dangerous,<00:04:37.759> but<00:04:37.919> just<00:04:38.160> because<00:04:38.560> Anthropic<00:04:39.199> hasn't<00:04:39.440> released<00:04:39.759> it<00:04:39.919> doesn't<00:04:40.160> make<00:04:40.240> us<00:04:40.400> any<00:04:40.639> safer<00:04:41.040> today. 00:04:42.479 --> 00:04:45.199 Could<00:04:42.639> you<00:04:42.800> talk<00:04:42.960> about<00:04:43.120> like<00:04:43.280> the<00:04:43.600> software<00:04:44.080> supply<00:04:44.560> chain? 00:04:45.199 --> 00:04:48.800 I've<00:04:45.360> heard<00:04:45.520> you<00:04:45.759> talk<00:04:45.840> about<00:04:46.000> this<00:04:46.240> before<00:04:46.479> and<00:04:46.800> like<00:04:47.040> securing<00:04:47.520> the<00:04:47.840> software<00:04:48.240> supply<00:04:48.560> chain. 00:04:48.800 --> 00:04:55.919 Give<00:04:48.880> us<00:04:49.040> a<00:04:49.120> sense<00:04:49.280> by<00:04:49.600> what<00:04:49.759> 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together. 00:05:34.080 --> 00:05:39.280 But<00:05:34.479> 90%<00:05:35.199> of<00:05:35.360> the<00:05:35.680> things<00:05:35.919> in<00:05:36.160> this<00:05:36.479> application<00:05:37.520> are<00:05:37.759> not<00:05:38.080> created<00:05:38.479> by<00:05:38.720> you. 00:05:39.280 --> 00:05:46.240 They're<00:05:39.600> created<00:05:39.919> by<00:05:40.160> somebody<00:05:40.479> else.<00:05:41.919> Except<00:05:42.400> unlike<00:05:42.880> car<00:05:43.199> manufacturing,<00:05:44.240> we<00:05:44.479> have<00:05:44.639> no<00:05:44.880> idea<00:05:45.120> who<00:05:45.360> built<00:05:45.600> this. 00:05:46.240 --> 00:05:48.479 We<00:05:46.479> don't<00:05:46.560> know<00:05:46.639> what<00:05:46.880> their<00:05:47.120> motivations<00:05:47.759> are. 00:05:48.479 --> 00:05:53.039 Can<00:05:48.720> we<00:05:48.960> trust<00:05:49.280> them?<00:05:50.160> Are<00:05:50.400> they<00:05:50.560> going<00:05:50.639> to<00:05:50.800> stand<00:05:51.039> behind<00:05:51.280> 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day<00:08:04.639> resulting 00:08:05.039 --> 00:08:09.680 from<00:08:05.199> this.<00:08:05.440> In<00:08:05.599> fact,<00:08:06.400> uh,<00:08:06.560> last<00:08:06.879> week,<00:08:07.199> GitHub<00:08:07.759> disclosed<00:08:08.560> that<00:08:08.879> they<00:08:09.120> got<00:08:09.280> breached. 00:08:09.680 --> 00:08:19.120 The<00:08:09.759> entirety<00:08:10.080> of<00:08:10.240> github.com,<00:08:10.960> a<00:08:11.199> Microsoft<00:08:11.759> company,<00:08:12.800> got<00:08:13.039> breached<00:08:13.360> because<00:08:13.599> one<00:08:13.840> developer<00:08:15.039> downloaded<00:08:15.680> one<00:08:16.080> piece<00:08:16.479> of<00:08:16.639> an<00:08:16.879> extension<00:08:17.360> to<00:08:17.599> their<00:08:17.840> IDE 00:08:19.120 --> 00:08:24.800 that<00:08:19.440> was<00:08:19.599> malicious.<00:08:20.800> So,<00:08:21.360> you<00:08:21.520> know,<00:08:21.680> these<00:08:21.919> developer<00:08:22.319> machines<00:08:22.639> are<00:08:23.120> 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00:11:18.079 And<00:11:10.480> now<00:11:10.640> we<00:11:10.800> can<00:11:10.880> kind<00:11:11.040> of<00:11:11.120> go<00:11:11.279> down,<00:11:11.760> I<00:11:11.920> I<00:11:12.240> have<00:11:12.320> a<00:11:12.480> whole<00:11:12.720> spiel<00:11:13.040> on<00:11:13.920> why<00:11:14.160> have<00:11:14.320> we<00:11:14.480> as<00:11:14.640> an<00:11:14.800> industry<00:11:15.120> failed<00:11:15.440> for<00:11:15.600> the<00:11:15.760> last<00:11:15.920> 30<00:11:16.160> years<00:11:16.320> to<00:11:16.560> ship<00:11:16.800> secure<00:11:17.279> software. 00:11:18.079 --> 00:11:20.640 A<00:11:18.240> big<00:11:18.480> part<00:11:18.640> of<00:11:18.720> that<00:11:18.959> has<00:11:19.120> certainly<00:11:19.440> been<00:11:19.600> it's<00:11:19.920> been<00:11:20.000> hard, 00:11:20.640 --> 00:11:28.240 expensive,<00:11:21.440> and<00:11:21.680> trying<00:11:21.920> to<00:11:22.079> get<00:11:22.320> thousands<00:11:22.720> and<00:11:22.959> thousands<00:11:23.279> 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there<00:31:28.240> was 00:31:28.399 --> 00:31:36.720 a<00:31:28.720> manager<00:31:29.120> named<00:31:29.360> Vijay<00:31:29.840> Jaju<00:31:31.039> who,<00:31:31.600> um,<00:31:32.000> kind<00:31:32.240> of<00:31:32.720> let<00:31:33.039> me,<00:31:33.279> a<00:31:33.440> little<00:31:33.600> kid,<00:31:33.840> along<00:31:34.159> on<00:31:34.559> projects<00:31:35.039> at<00:31:35.279> Fortune<00:31:35.840> 500s<00:31:36.480> on 00:31:36.720 --> 00:31:44.960 cybersecurity,<00:31:37.071> and,<00:31:37.423> uh,<00:31:37.774> you<00:31:38.125> know,<00:31:38.476> the<00:31:38.828> rest<00:31:39.179> is<00:31:39.530> history.<00:31:39.881> Incredible,<00:31:40.233> and<00:31:40.584> we<00:31:40.935> continue<00:31:41.286> to<00:31:41.638> stay<00:31:41.989> in<00:31:42.340> touch.<00:31:42.691> Thank<00:31:43.043> you<00:31:43.394> so<00:31:43.745> much<00:31:44.096> for<00:31:44.448> coming<00:31:44.799> on 00:31:44.960 --> 00:31:52.559 the<00:31:45.039> show,<00:31:45.279> seriously.<00:31:45.600> You're<00:31:45.760> working<00:31:45.919> on<00:31:46.080> the,<00:31:46.559> I<00:31:46.799> think<00:31:46.960> maybe<00:31:47.279> the<00:31:47.600> most<00:31:47.840> important<00:31:48.320> issue,<00:31:49.279> certainly<00:31:49.600> the<00:31:49.760> most<00:31:50.000> important<00:31:50.320> vulnerability<00:31:51.120> in,<00:31:51.360> in<00:31:51.600> the<00:31:51.760> age<00:31:52.000> of<00:31:52.159> AI. 00:31:52.559 --> 00:31:55.840 So,<00:31:52.720> thank<00:31:52.880> you<00:31:52.960> for<00:31:53.120> what<00:31:53.279> you're<00:31:53.440> doing,<00:31:53.600> and<00:31:54.399> appreciate<00:31:54.720> you<00:31:54.880> coming<00:31:55.039> on. 00:31:55.840 --> 00:31:58.799 <00:31:56.080> Thanks,<00:31:56.320> Clint.<00:31:56.559> Great<00:31:56.799> chatting. ``` ### Prospero AI CEO George Kailas: How AI is democratizing investing URL: https://www.ceo.com/episodes/prospero-ai-ceo-george-kailas-how-ai-is-democratizing-investing/ Last updated: 2026-08-23T15:50:04.000Z # George Kailas is giving away Wall Street's playbook George Kailas got his first hedge fund job at 17\. He taught himself accounting to qualify. He spent the years after on the buy side, building his own algorithms, and eventually ran an AI-as-a-service business for financial firms. The pattern he kept seeing: retail investors operating at a serious data disadvantage. Even smaller hedge funds couldn't keep up with the largest institutions. He founded [Prospero.ai](https://www.prospero.ai/about-us?ref=ceo.com) in 2019 to close that gap. "Initially, our goal was actually pretty modest," Kailas said on the CEO.com Podcast. "We wanted to help people stay out of the way of institutions and reduce costly investing mistakes. But the signals we developed ended up performing incredibly well." The numbers he cited on the podcast: picks in Prospero's [newsletter](https://prosperoai.substack.com/) have outperformed the market by an average of 63% over the last four years. About 15,000 people use the app each month. Another 10,000 read the newsletter every week. Alibaba changed his sense of what he'd built. Around 2022 or 2023, two of Prospero's most important signals spiked far above normal, so the company bought the stock. Ant Financial announced a funding round shortly after, and shares jumped. The signals cooled, and Prospero sold. Then the same pattern appeared again. Users noticed it themselves and started asking questions. Alibaba announced a major corporate reorganization and the stock surged. "Maybe we've built something bigger than simply helping people avoid mistakes," Kailas remembers thinking. The signal doing the heaviest lifting is net option sentiment, which isolates institutional behavior on the theory that institutions have better information and stronger incentives. That theory is also why he's cool on prediction markets, which people ask him about constantly. The odds usually favor the market maker, he said, and "you often can't distinguish between informed participants and uninformed participants." Prospero stayed largely free for years. Investors wanted him to charge sooner. He refused, because he believes trust will be the scarcest asset in an AI-saturated world. "If enough people trust it, the information becomes more valuable, which creates a virtuous cycle," he said. The company runs on two full-time employees. More than 50 people have contributed through equity arrangements, advisory roles, and part-time work. Total raised: a little over $1.5 million, about $538,000 of it through crowdfunding. The five-year plan is wealth management, sold to users who already have years of evidence the system works. Kailas doesn't think AI is propping up the stock market, and he does think bubbles are forming. He just doesn't find that observation useful. "A bubble can continue expanding for years," he said. "If you become overly focused on timing the collapse, you can miss substantial gains." His questions are about exit criteria and risk controls, not timing. He's less sure about the compute buildout. Communities are pushing back against data centers that consume enormous power and water while creating few long-term jobs. Smaller, specialized models are already challenging the assumption that AI requires ever more compute. And [Google has set 2029 as its target](https://blog.google/innovation-and-ai/technology/safety-security/cryptography-migration-timeline/?ref=ceo.com) for migrating to post-quantum cryptography. If quantum computing progresses the way many expect, Kailas said, it could change the economics of the infrastructure being built today. So why are companies spending hundreds of billions on data centers? "Honestly, because that's how capitalism works," he said. "If someone is willing to write the checks, someone else will build the infrastructure." On the frontier labs, he sees two different companies. OpenAI's talk of advertising and its media acquisitions suggest to him a bet on distribution over product. Anthropic is the opposite case. "I've never seen demand for a private company like I've seen with Anthropic," he said. "People are desperate to invest." The signals now have a second life. In July, Kailas launched [Aethon Fund](https://www.businesswire.com/news/home/20260714954709/en/Aethon-Fund-to-Launch-with-%2450M-in-Capital-Bringing-20-Years-of-Signal-Research-and-AI-Powered-Trading-Discipline-to-Institutional-Markets?ref=ceo.com), a hedge fund that opened with $50 million in capital and a signal library refined through four years of live calls with Prospero's community. He moved to chairman of Prospero.ai, longtime CTO Adam Plante took over as CEO, and a percentage of Aethon's proceeds goes back to the platform. CEO.com asks every guest the same final question, on the belief that the chances one gives are just as important as the chances one takes. Kailas named [Bruce Greenwald](https://business.columbia.edu/faculty/people/bruce-greenwald?ref=ceo.com), the longtime head of Columbia Business School's value investing program. Greenwald took an interest when Kailas was 16, introduced him to the people who gave him his first hedge fund opportunities, and vouched for a teenager with almost no experience. "There's no question I wouldn't be where I am today without that support," Kailas said. ```chapters 00:00:00 Introduction and Background 00:00:09 Founding of Prospero AI 00:00:42 Retail Investors' Data Disadvantage 00:01:02 Simplifying Investment Signals 00:01:46 Democratizing Investing 00:02:11 Building a Community 00:03:02 Trust in AI and Community-Based Research 00:04:08 Future Vision: Public Utility of Data 00:05:12 Predicting News Events 00:07:16 User Base and Growth 00:07:40 Beyond Stock Market: Betting Markets 00:09:08 Institutional vs. Retail Behavior in Markets 00:12:11 AI's Impact on the Stock Market 00:16:10 Overbuilding Compute and Data Centers 00:20:31 Incentives Behind Building Data Centers 00:23:13 Future of AI Companies Going Public 00:27:09 Staying Ahead with Prospero's Algorithms 00:30:57 Typical Day of a CEO 00:33:43 Team Size and Structure 00:34:42 Funding and Investment 00:35:08 Long-Term Vision for Prospero 00:38:30 Acknowledging Mentors and Opportunities ``` ```vtt WEBVTT 00:00:00.000 --> 00:00:02.000 George,<00:00:00.560> thank<00:00:00.720> you<00:00:00.800> so<00:00:00.920> much<00:00:01.040> for<00:00:01.160> coming<00:00:01.400> on<00:00:01.520> the<00:00:01.600> show. 00:00:02.000 --> 00:00:06.120 What<00:00:02.160> an<00:00:02.240> honor<00:00:02.480> to<00:00:02.560> have<00:00:02.840> you.<00:00:03.000> You<00:00:03.120> are<00:00:03.200> the<00:00:03.400> CEO<00:00:04.240> of<00:00:04.400> Prospero<00:00:05.320> AI. 00:00:06.120 --> 00:00:09.520 Tell<00:00:06.400> us<00:00:06.560> what<00:00:06.720> it<00:00:06.880> is,<00:00:07.160> how<00:00:07.280> you<00:00:07.440> became<00:00:07.760> the<00:00:07.840> CEO. 00:00:09.520 --> 00:00:13.400 Oh,<00:00:09.920> I<00:00:10.000> mean,<00:00:10.280> I<00:00:10.400> was<00:00:10.760> I<00:00:10.880> was<00:00:11.080> at<00:00:11.240> Prospero<00:00:11.880> from<00:00:12.280> from<00:00:12.480> the<00:00:12.560> start. 00:00:13.400 --> 00:00:18.960 Uh,<00:00:14.520> and<00:00:14.640> 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difficult. 00:11:36.080 --> 00:11:41.720 Like,<00:11:36.360> you're<00:11:36.480> going<00:11:36.600> to<00:11:36.680> have<00:11:36.760> to<00:11:36.840> throw<00:11:37.080> a<00:11:37.120> lot<00:11:37.480> of<00:11:37.560> money<00:11:37.840> behind<00:11:38.280> it,<00:11:38.760> and<00:11:39.280> the<00:11:39.400> juice<00:11:39.760> isn't<00:11:40.000> probably<00:11:40.360> going<00:11:40.480> to<00:11:40.520> be<00:11:40.640> worth<00:11:40.880> the<00:11:40.960> squeeze. 00:11:41.720 --> 00:11:47.120 But,<00:11:42.840> if<00:11:43.040> you're<00:11:43.280> say<00:11:44.400> what<00:11:44.720> already<00:11:45.320> short<00:11:45.840> a<00:11:45.920> mega-cap,<00:11:46.640> right? 00:11:47.120 --> 00:11:55.280 And<00:11:47.280> you<00:11:47.360> want<00:11:47.520> to<00:11:47.640> throw<00:11:48.000> a<00:11:48.080> bunch<00:11:48.360> of<00:11:48.440> money<00:11:48.760> in<00:11:48.880> the<00:11:49.000> betting<00:11:49.360> markets<00:11:50.440> to<00:11:51.160> 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00:16:29.160 --> 00:16:33.000 Tell<00:16:29.360> us<00:16:29.480> what<00:16:29.600> you<00:16:29.680> mean<00:16:29.839> by<00:16:29.960> that.<00:16:30.120> Like,<00:16:30.320> what<00:16:30.560> what<00:16:30.640> do<00:16:30.720> you<00:16:30.760> mean<00:16:30.920> by<00:16:31.040> we're<00:16:31.280> overbuilding<00:16:31.920> commute? 00:16:33.000 --> 00:16:36.600 compute,<00:16:33.400> sorry.<00:16:33.560> Well,<00:16:33.760> you<00:16:34.120> yeah,<00:16:34.440> you<00:16:34.720> hit<00:16:34.880> on<00:16:35.040> the<00:16:35.120> first<00:16:35.440> thing,<00:16:36.040> right? 00:16:36.600 --> 00:16:45.080 Like,<00:16:36.921> [laughter]<00:16:37.520> it<00:16:37.720> is<00:16:37.920> definitely<00:16:39.120> that,<00:16:40.040> you<00:16:40.120> know,<00:16:41.320> people,<00:16:42.080> you<00:16:42.240> know,<00:16:43.320> nobody<00:16:43.800> got<00:16:44.040> to<00:16:44.160> vote<00:16:45.000> for 00:16:45.080 --> 00:16:53.480 these<00:16:45.320> data<00:16:45.600> 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00:23:35.640 Cuz<00:23:28.000> you<00:23:28.120> have<00:23:28.280> seen<00:23:28.480> all<00:23:28.640> of<00:23:28.760> these<00:23:29.000> sorts<00:23:29.280> of<00:23:29.400> deals<00:23:29.800> that<00:23:30.760> kind<00:23:31.080> of<00:23:31.160> on<00:23:31.280> paper<00:23:31.520> don't<00:23:31.680> make<00:23:31.840> a<00:23:31.880> ton<00:23:32.080> of<00:23:32.160> sense,<00:23:32.400> but<00:23:32.560> when<00:23:32.720> you<00:23:32.800> go<00:23:32.960> public,<00:23:33.880> um,<00:23:34.200> you<00:23:34.280> know,<00:23:34.400> kind<00:23:34.600> of<00:23:35.440> you're 00:23:35.640 --> 00:23:40.440 you're<00:23:36.000> laid<00:23:36.280> bare.<00:23:38.360> Those<00:23:38.600> are<00:23:38.760> two<00:23:39.280> different<00:23:39.760> things. 00:23:40.440 --> 00:23:49.880 Yeah.<00:23:40.920> Right?<00:23:42.000> Um,<00:23:42.880> I<00:23:43.000> think<00:23:43.240> if<00:23:43.360> you're<00:23:43.520> talking<00:23:44.240> about,<00:23:45.360> um,<00:23:46.720> 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00:28:26.280 --> 00:28:32.200 Way<00:28:26.760> more<00:28:27.120> easy<00:28:27.400> to<00:28:27.600> interpret,<00:28:28.960> um,<00:28:29.440> for<00:28:29.560> a<00:28:29.640> person,<00:28:30.720> also<00:28:31.120> a<00:28:31.200> computer. 00:28:32.200 --> 00:28:41.000 Um,<00:28:33.120> so<00:28:33.920> that's<00:28:34.240> one<00:28:34.360> of<00:28:34.440> the<00:28:34.560> things<00:28:34.880> that<00:28:35.120> we<00:28:35.400> bet<00:28:35.920> on<00:28:36.400> and<00:28:36.640> that,<00:28:36.880> like,<00:28:37.760> you<00:28:37.880> know,<00:28:39.600> you<00:28:39.960> could<00:28:40.160> probably<00:28:40.640> make 00:28:41.000 --> 00:28:49.360 some<00:28:42.080> very<00:28:42.480> specific<00:28:43.160> prompts<00:28:44.400> that<00:28:44.600> could<00:28:44.800> duplicate<00:28:45.480> and<00:28:45.760> test<00:28:46.520> around<00:28:46.880> those<00:28:47.120> things,<00:28:47.960> but<00:28:48.720> at<00:28:48.920> the<00:28:49.000> same 00:28:49.360 --> 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00:39:09.400 And<00:39:00.920> he,<00:39:01.640> you<00:39:01.760> know,<00:39:02.560> he<00:39:02.720> not<00:39:02.960> only,<00:39:03.920> you<00:39:04.000> know,<00:39:04.160> taught<00:39:04.440> me<00:39:04.600> things,<00:39:05.120> he<00:39:05.240> helped,<00:39:05.760> you<00:39:05.880> know,<00:39:06.000> introduce<00:39:06.560> me<00:39:06.760> to<00:39:06.880> the<00:39:07.000> person<00:39:07.520> that,<00:39:07.760> you<00:39:07.840> know,<00:39:07.960> gave<00:39:08.200> me<00:39:08.320> my<00:39:08.480> first<00:39:09.160> hedge 00:39:09.400 --> 00:39:16.760 fund<00:39:09.640> job,<00:39:10.320> another<00:39:10.680> job<00:39:10.960> along<00:39:11.240> the<00:39:11.320> way,<00:39:12.520> um<00:39:13.280> you<00:39:13.320> know,<00:39:13.720> the<00:39:13.840> first<00:39:14.160> kind<00:39:14.320> of<00:39:14.400> larger<00:39:14.760> value<00:39:15.080> fund<00:39:15.360> I<00:39:15.440> worked<00:39:15.760> at. 00:39:16.760 --> 00:39:24.160 Uh<00:39:17.000> 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00:39:32.920 --> 00:39:39.760 Oh,<00:39:33.000> no,<00:39:33.240> I<00:39:33.320> was<00:39:33.600> uh<00:39:33.880> I<00:39:34.000> was<00:39:34.360> I<00:39:34.480> was<00:39:34.880> 20<00:39:35.680> at<00:39:35.840> that<00:39:36.080> time<00:39:37.200> um<00:39:37.880> that<00:39:38.120> just<00:39:38.320> like<00:39:38.480> walked<00:39:38.840> into<00:39:39.040> their<00:39:39.280> office. 00:39:39.760 --> 00:39:48.080 Like<00:39:40.080> I<00:39:40.200> like<00:39:40.560> that<00:39:40.840> that,<00:39:41.440> you<00:39:41.520> know,<00:39:41.720> cuz<00:39:42.520> you<00:39:42.680> get<00:39:42.920> these<00:39:43.120> MBA<00:39:43.520> students<00:39:44.360> all<00:39:44.560> the<00:39:44.640> time<00:39:45.040> that<00:39:45.200> like<00:39:45.360> maybe<00:39:45.640> they're<00:39:45.840> a<00:39:45.880> student,<00:39:46.320> but<00:39:46.480> I<00:39:46.560> hadn't<00:39:46.880> even<00:39:47.080> graduated<00:39:47.640> college 00:39:48.080 --> 00:39:51.760 yet.<00:39:48.640> So,<00:39:48.840> I<00:39:48.920> think<00:39:49.120> they,<00:39:49.480> you<00:39:49.600> know,<00:39:49.800> I<00:39:49.880> think<00:39:50.040> they<00:39:50.120> were<00:39:50.600> surprised<00:39:51.000> to<00:39:51.080> get<00:39:51.200> that<00:39:51.400> call. 00:39:51.760 --> 00:40:00.080 I,<00:39:52.200> you<00:39:52.320> know,<00:39:52.440> I<00:39:52.480> got<00:39:52.760> that<00:39:52.960> job.<00:39:54.040> Um<00:39:54.680> so,<00:39:54.880> yeah,<00:39:55.160> I<00:39:55.240> mean,<00:39:56.280> there's<00:39:56.560> no<00:39:56.760> way<00:39:57.040> I'd<00:39:57.160> be<00:39:57.320> where<00:39:57.520> I<00:39:57.600> was<00:39:57.840> today<00:39:58.120> if<00:39:58.240> Bruce<00:39:58.520> didn't<00:39:58.880> kind<00:39:59.040> of<00:39:59.120> take<00:39:59.280> a<00:39:59.360> shot<00:39:59.640> on<00:39:59.960> at 00:40:00.080 --> 00:40:04.560 at<00:40:00.760> uh<00:40:01.280> on<00:40:01.520> me<00:40:01.760> as<00:40:01.960> like<00:40:02.120> a<00:40:02.160> 16-year-old<00:40:03.120> kid. 00:40:04.560 --> 00:40:07.520 George,<00:40:04.840> thanks<00:40:05.040> so<00:40:05.120> much<00:40:05.280> for<00:40:05.360> coming<00:40:05.640> on.<00:40:05.800> Seriously,<00:40:06.120> it's<00:40:06.240> incredible<00:40:06.760> what<00:40:06.880> you're<00:40:07.000> building. 00:40:07.520 --> 00:40:10.520 Really,<00:40:07.840> it's<00:40:08.040> it's<00:40:08.200> remarkable.<00:40:08.840> Well<00:40:09.000> done.<00:40:10.040> Thank<00:40:10.240> you. 00:40:10.520 --> 00:40:13.400 It's<00:40:10.680> been<00:40:10.920> It's<00:40:11.040> been<00:40:11.200> great,<00:40:11.400> Clint. ``` ### Extend Co-Founder & CEO Andrew Jamison: How AI is reinventing expense management URL: https://www.ceo.com/episodes/extend-co-founder-ceo-andrew-jamison-how-ai-is-reinventing-expense-management/ Last updated: 2026-08-23T16:13:31.000Z # Andrew Jamison doesn't want your bank dead Andrew Jamison did not leave American Express with a company in mind. He left because his mother was dying. She had fought cancer for decades, and when she got worse, he took a sabbatical to be with her. "When you step away from work during a moment like that, you start realizing life isn't a dress rehearsal," he said on the CEO.com Podcast. "For the first time in years, I had space to think about what I actually enjoyed doing. I realized what I loved most was talking to customers, understanding problems, and building solutions." What he built was [Extend](https://www.paywithextend.com/?ref=ceo.com), an expense management platform that lets companies decide who can spend, where, and how much before a transaction happens, then handles receipts, and integrates with [participating banks including American Express, PNC, HSBC, and BMO](https://www.paywithextend.com/participating-banks?ref=ceo.com). That last part is the unusual part. Brex, Ramp, and Divvy set out to become card issuers and pull customers away from the banks. Extend issues nothing and underwrites nothing. It makes the card business already more powerful. "The 15 or 16 digits on your card should unlock sophisticated software capabilities automatically," Jamison said. "You shouldn't need to switch banks. You shouldn't need a new card." A business depends on its bank for lending, treasury, wires, and foreign exchange. Extend extends those relationships instead of replacing them, which is where the name came from. The market has drifted his way. Capital One bought Brex this year, a deal Jamison wrote [marks the end of business finance's manual era](https://thefr.com/news/capital-ones-brex-buy-means-end-of-business-finances-manual-era?ref=ceo.com), with spend management finally catching up to the rest of enterprise software. His company started from that premise nine years ago. Jamison calls Extend the combination of the only two jobs he has ever had: nearly a decade as an SAP consultant, then 12 years running B2B payments products at American Express. Consulting taught him what integrated systems do for a business. Amex taught him how the rails work. His father built three supermarket shelving companies and dragged the family into warehouses on weekends to count inventory. Jamison grew up certain he wanted the opposite life. "People always tell you that you become more like your parents as you get older," he said. "And they're right." On artificial intelligence, he skips the grand claims. "AI is a perfect fit for fintech because AI loves rules. And accountants love rules too." On the platform, that means a receipt texted from a phone gets read and matched to its transaction, categorized, and coded to the right ledger account without a human touching it. Next comes analytics in plain language. Ask how Q3 spending broke down, or who went over the hotel policy, and get an answer instead of building a report. Extend raised its seed round from Point72 in late 2017 and has raised just under $70 million since, from investors including FinTech Collective, [March Capital, and B Capital](https://www.businesswire.com/news/home/20211027005144/en/Modernizing-Payments-from-the-Inside-Extend-Raises-%2440M-in-Series-B-Funding?ref=ceo.com). In September 2025, it added [$20 million in new capital and a CFO](https://www.businesswire.com/news/home/20250918107234/en/Extend-Secures-$20-Million-in-New-Capital-and-Hires-Seasoned-CFO?ref=ceo.com). In November it [announced a collaboration with PNC Bank on commercial card payments](https://www.businesswire.com/news/home/20251110755999/en/Extend-and-PNC-Bank-Collaborate-to-Modernize-Commercial-Card-Payments-for-Businesses?ref=ceo.com) and [opened its software to nearly any bank credit card across all three major networks](https://www.businesswire.com/news/home/20251120578951/en/Extend-Brings-Universal-Expense-Management-to-the-SMB-Market?ref=ceo.com). Non-sales employees at Extend work from the office three days a week. Jamison comes in four days, and he lives farther away than almost anyone on the team. "If you ask something of your team, you should be willing to do it yourself," he said. "Nothing erodes trust faster than saying one thing and doing another." He reads the Financial Times in print, partly a British habit and partly because a newspaper is not curated for him the way a feed is. "People don't run through walls for companies," he said. "They run through walls for people. And that starts with trust." Someone once ran through a wall for him. Early in his consulting career, Jamison was struggling on a complicated project and received a negative review. A manager named Nick Keating read it and said, "I don't believe this." Keating pulled him onto his own team, and their project was recognized as the best in the company the following year. Keating became a mentor, an early investor in Extend, and one of Jamison's closest friends. Before any of the venture money, Extend raised $250,000 from friends and family. "When people who know you personally put their trust, and their money, behind you, you feel an obligation to make it work," Jamison told the CEO.com Podcast. "Those early supporters gave us a chance, and I'll never forget it." ```chapters 00:00:00 Introduction and Guest Background 00:00:11 Overview of Extend 00:00:52 Journey to Founding Extend 00:02:29 Origin Story and Entrepreneurial Drive 00:05:09 Market Opportunity and Middle Market Focus 00:07:22 Collaboration vs. Disruption in FinTech 00:10:11 AI in FinTech and Expense Management 00:12:15 Internal Use of AI at Extend 00:14:24 Funding and Investors 00:15:28 Company Culture and Remote Work 00:18:45 Reading Recommendations 00:21:37 Macroeconomic Environment and FinTech 00:23:36 Mentorship and Early Career Challenges 00:27:23 Capital Raising Journey 00:28:37 Closing Remarks and Future Check-in ``` ```vtt WEBVTT 00:00:00.000 --> 00:00:02.120 Andrew,<00:00:00.480> thank<00:00:00.680> you<00:00:00.760> so<00:00:00.880> much<00:00:01.040> for<00:00:01.160> coming<00:00:01.440> on<00:00:01.520> the<00:00:01.640> show. 00:00:02.120 --> 00:00:07.680 You<00:00:02.480> are<00:00:02.680> the<00:00:02.880> co-founder<00:00:03.720> and<00:00:04.000> CEO<00:00:04.760> of<00:00:04.920> Extend,<00:00:06.280> which<00:00:06.480> is<00:00:06.600> a<00:00:06.680> fintech<00:00:07.280> company. 00:00:07.680 --> 00:00:11.360 Tell<00:00:07.880> us<00:00:07.960> about<00:00:08.120> Extend<00:00:08.600> and<00:00:08.680> how<00:00:08.800> you<00:00:08.880> became<00:00:09.200> the<00:00:09.280> CEO<00:00:09.680> and<00:00:09.800> co-founder. 00:00:11.360 --> 00:00:18.920 Well,<00:00:12.200> the<00:00:12.360> how<00:00:12.560> I<00:00:12.640> got<00:00:12.840> there<00:00:13.040> is<00:00:13.160> a<00:00:13.200> different<00:00:13.560> story,<00:00:13.960> but<00:00:14.520> Extend<00:00:14.960> is<00:00:15.040> a<00:00:15.120> spend<00:00:15.920> and<00:00:16.040> expense<00:00:16.480> management<00:00:17.000> platform. 00:00:18.920 --> 00:00:26.120 And<00:00:19.080> that<00:00:19.240> what<00:00:19.360> that<00:00:19.560> means<00:00:19.800> is<00:00:19.960> we<00:00:20.080> 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industry<00:00:51.880> for<00:00:52.040> a<00:00:52.120> long<00:00:52.360> time. 00:00:52.840 --> 00:00:55.400 At<00:00:52.960> what<00:00:53.120> point<00:00:53.320> did<00:00:53.440> you<00:00:53.560> realize<00:00:53.840> like,<00:00:54.040> "Hey,<00:00:54.200> this<00:00:54.480> is<00:00:54.640> a<00:00:54.720> need. 00:00:55.400 --> 00:01:01.640 This<00:00:55.600> is<00:00:55.720> something<00:00:56.000> that<00:00:56.160> needs<00:00:56.400> to<00:00:56.480> happen."?<00:00:57.480> Well,<00:00:57.720> it's<00:00:57.840> strange<00:00:58.200> enough<00:00:58.680> Extend<00:00:59.000> is<00:00:59.080> kind<00:00:59.240> of<00:00:59.320> a<00:00:59.400> marriage<00:00:59.920> of<00:01:00.200> of<00:01:00.440> the<00:01:00.640> two<00:01:00.800> jobs<00:01:01.080> I<00:01:01.120> had<00:01:01.280> before<00:01:01.520> and<00:01:01.600> I've 00:01:01.640 --> 00:01:06.720 only<00:01:01.840> had<00:01:02.000> two<00:01:02.160> jobs<00:01:02.600> and<00:01:02.840> it's<00:01:03.040> not<00:01:03.280> because<00:01:03.520> I'm<00:01:03.600> 27<00:01:04.280> cuz<00:01:04.640> unfortunately<00:01:05.080> I'm<00:01:05.160> not. 00:01:06.720 --> 00:01:11.920 It's<00:01:07.000> I<00:01:07.040> spent<00:01:07.520> the<00:01:07.640> best<00:01:08.080> year<00:01:08.680> best<00:01:08.880> part<00:01:09.040> of<00:01:09.160> 10<00:01:09.400> years<00:01:09.960> working<00:01:10.200> alongside<00:01:10.680> SAP<00:01:11.120> as<00:01:11.280> a<00:01:11.320> consultant. 00:01:11.920 --> 00:01:20.000 So,<00:01:12.080> I<00:01:12.280> sort<00:01:12.440> of<00:01:12.520> got<00:01:12.640> the<00:01:12.760> technology<00:01:13.920> piece<00:01:14.200> of<00:01:14.320> things<00:01:15.400> in<00:01:15.520> the<00:01:15.640> earliest<00:01:16.000> part<00:01:16.200> of<00:01:16.280> my<00:01:16.440> career<00:01:17.520> and<00:01:17.680> then<00:01:18.000> sort<00:01:18.160> of<00:01:18.240> joined<00:01:19.040> American<00:01:19.480> Express<00:01:19.880> where<00:01:19.960> I 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the<00:01:35.440> idea<00:01:35.800> being<00:01:36.160> that<00:01:37.120> I'm<00:01:37.360> really<00:01:37.560> marrying<00:01:37.960> together<00:01:38.320> an<00:01:38.400> experience<00:01:38.960> I<00:01:39.080> saw<00:01:39.520> of<00:01:40.080> how<00:01:40.240> did<00:01:40.520> SAP<00:01:41.000> grow<00:01:41.240> and<00:01:41.360> develop<00:01:41.880> on<00:01:41.960> the<00:01:42.080> back<00:01:42.480> of<00:01:42.960> a<00:01:43.040> really<00:01:43.240> credit 00:01:43.480 --> 00:01:51.120 an<00:01:43.600> integrated<00:01:44.080> system<00:01:44.520> and<00:01:44.760> leveraging<00:01:45.240> EDI<00:01:45.840> as<00:01:46.040> as<00:01:46.240> a<00:01:46.360> as<00:01:46.480> a<00:01:46.520> mechanism<00:01:47.040> to<00:01:47.160> sort<00:01:47.320> of<00:01:47.520> wind<00:01:47.760> the<00:01:47.840> clock<00:01:48.160> forward<00:01:48.480> to<00:01:48.640> saying,<00:01:49.480> "Great,<00:01:49.800> now<00:01:49.960> it's<00:01:50.120> all<00:01:50.240> about<00:01:50.480> API." 00:01:51.120 --> 00:01:55.640 So,<00:01:51.280> it<00:01:51.400> makes<00:01:51.640> things<00:01:51.840> a<00:01:51.880> lot<00:01:52.040> more<00:01:52.160> dynamic<00:01:53.480> and<00:01:53.640> things<00:01:53.880> can<00:01:54.040> go<00:01:54.240> faster. 00:01:55.640 --> 00:02:04.120 But<00:01:55.800> also<00:01:56.800> sort<00:01:57.000> of<00:01:57.080> realizing<00:01:57.720> some<00:01:57.880> of<00:01:57.960> the<00:01:58.000> constraints<00:01:58.800> that<00:01:58.960> existed<00:01:59.680> with<00:01:59.960> the<00:02:00.080> concept<00:02:00.520> of<00:02:00.640> just<00:02:00.920> having<00:02:01.200> physical<00:02:01.640> cards<00:02:02.560> in<00:02:02.680> a<00:02:02.760> world<00:02:03.040> that's<00:02:03.200> becoming<00:02:03.600> increasingly 00:02:04.120 --> 00:02:08.200 digital.<00:02:05.080> Uh,<00:02:05.200> and<00:02:05.360> in<00:02:05.440> a<00:02:05.479> world<00:02:05.880> where<00:02:06.560> we<00:02:06.680> need<00:02:06.840> more<00:02:07.080> controls,<00:02:07.960> right? 00:02:08.200 --> 00:02:16.959 To<00:02:08.280> prevent<00:02:08.720> more<00:02:08.920> fraud.<00:02:10.000> Uh,<00:02:10.240> and<00:02:10.440> frankly,<00:02:11.120> the<00:02:11.200> controls<00:02:11.680> also<00:02:12.240> help<00:02:12.520> to<00:02:12.640> promote<00:02:13.000> good<00:02:13.200> behavior<00:02:13.720> across<00:02:14.160> employees<00:02:15.240> because<00:02:15.440> it's<00:02:15.520> just<00:02:15.720> much<00:02:16.000> more<00:02:16.120> transparency 00:02:16.959 --> 00:02:20.480 around<00:02:17.280> who's<00:02:17.480> doing<00:02:17.760> what,<00:02:18.000> where,<00:02:18.160> and<00:02:18.320> when.<00:02:19.640> Yeah. 00:02:20.480 --> 00:02:23.920 And<00:02:20.880> at<00:02:21.120> what<00:02:21.280> point<00:02:21.480> did<00:02:21.640> you<00:02:21.760> realize<00:02:22.040> like,<00:02:22.200> "Hey,<00:02:22.400> I'm<00:02:22.480> going<00:02:22.600> to<00:02:22.680> start<00:02:22.959> this<00:02:23.120> company?" 00:02:23.920 --> 00:02:28.160 And<00:02:24.040> did<00:02:24.240> you<00:02:24.400> take<00:02:24.640> venture<00:02:24.959> capital?<00:02:25.640> I<00:02:25.720> mean,<00:02:26.160> what<00:02:27.000> How<00:02:27.160> How<00:02:27.240> did<00:02:27.320> you<00:02:27.400> find<00:02:27.560> your<00:02:27.640> co-founder? 00:02:28.160 --> 00:02:30.760 Give<00:02:28.360> us<00:02:28.480> kind<00:02:28.640> of<00:02:28.720> the<00:02:28.840> origin<00:02:29.280> story<00:02:29.600> of<00:02:29.680> this<00:02:29.840> thing. 00:02:30.760 --> 00:02:36.280 Yeah,<00:02:31.120> so<00:02:31.520> look,<00:02:31.760> I<00:02:31.800> mean,<00:02:32.000> it's<00:02:32.240> a<00:02:32.280> bit<00:02:32.400> of<00:02:32.520> a<00:02:32.840> sort<00:02:33.000> of<00:02:33.440> uh,<00:02:33.920> a<00:02:33.959> bit<00:02:34.080> of<00:02:34.160> a<00:02:34.200> life<00:02:34.560> moment<00:02:35.000> that<00:02:35.240> that<00:02:35.400> really<00:02:35.600> dragged<00:02:35.880> me<00:02:35.959> down<00:02:36.200> here. 00:02:36.280 --> 00:02:40.959 My<00:02:36.440> father's<00:02:36.760> an<00:02:36.840> entrepreneur<00:02:37.360> very<00:02:37.640> different<00:02:38.520> uh,<00:02:38.840> uh,<00:02:39.080> uh,<00:02:39.720> uh,<00:02:40.040> set<00:02:40.240> of<00:02:40.320> industries. 00:02:40.959 --> 00:02:45.480 He<00:02:41.040> was<00:02:41.280> kind<00:02:41.440> of<00:02:41.520> in<00:02:41.600> that<00:02:41.800> sort<00:02:41.920> of<00:02:42.000> supermarket,<00:02:42.600> hypermarket,<00:02:43.360> shelving<00:02:43.760> industry<00:02:44.959> uh,<00:02:45.160> piece. 00:02:45.480 --> 00:02:50.600 But<00:02:45.600> again,<00:02:46.120> he<00:02:46.240> you<00:02:46.320> know,<00:02:46.440> he's<00:02:46.680> a<00:02:46.720> he's<00:02:46.920> a<00:02:46.959> three-time<00:02:47.480> entrepreneur<00:02:48.120> and<00:02:48.840> you<00:02:48.880> know,<00:02:48.959> I<00:02:49.040> saw<00:02:49.320> 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to<00:03:14.720> me<00:03:14.840> because<00:03:15.880> I<00:03:15.959> took<00:03:16.120> a<00:03:16.160> sabbatical<00:03:16.840> from<00:03:17.000> American<00:03:17.320> Express. 00:03:17.640 --> 00:03:21.360 That's<00:03:17.760> how<00:03:18.000> I<00:03:18.080> end<00:03:18.280> up<00:03:18.440> leaving.<00:03:19.320> My<00:03:19.440> mother<00:03:19.720> was<00:03:20.200> um,<00:03:20.560> was<00:03:20.720> not<00:03:20.920> very<00:03:21.080> well. 00:03:21.360 --> 00:03:25.600 Hadn't<00:03:21.640> been<00:03:21.840> well<00:03:22.080> for<00:03:22.200> 30<00:03:22.480> odd<00:03:22.640> years<00:03:22.880> with<00:03:23.040> cancer<00:03:23.959> through<00:03:24.160> different<00:03:24.519> bouts. 00:03:25.600 --> 00:03:29.840 Uh,<00:03:25.760> and<00:03:25.880> it's<00:03:26.000> one<00:03:26.120> of<00:03:26.200> those<00:03:26.320> moments<00:03:26.640> in<00:03:26.760> life<00:03:27.160> where<00:03:27.280> you<00:03:27.400> start<00:03:27.640> to<00:03:27.680> 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as<00:07:07.080> a<00:07:07.160> finance<00:07:07.560> team,<00:07:07.760> you're<00:07:07.919> actually 00:07:08.320 --> 00:07:11.919 in<00:07:08.440> control.<00:07:09.560> Right?<00:07:09.880> Which<00:07:10.040> is<00:07:10.160> which<00:07:10.360> is<00:07:10.440> really<00:07:10.640> what<00:07:10.760> they<00:07:10.880> want. 00:07:11.919 --> 00:07:14.640 Yeah.<00:07:12.640> Yeah,<00:07:13.000> it's<00:07:13.360> so<00:07:13.720> helpful. 00:07:14.640 --> 00:07:21.880 I<00:07:14.800> I've<00:07:15.280> I've<00:07:15.360> had<00:07:15.480> a<00:07:15.520> sense<00:07:16.200> uh<00:07:16.280> I'm<00:07:16.440> based<00:07:16.760> in<00:07:16.880> Utah,<00:07:17.919> there's<00:07:18.160> been<00:07:18.280> a<00:07:18.360> number<00:07:18.640> of<00:07:18.760> like<00:07:18.960> really<00:07:19.200> successful<00:07:20.000> fintech<00:07:20.480> startups<00:07:20.800> that<00:07:20.880> have<00:07:20.960> come<00:07:21.120> out<00:07:21.240> of<00:07:21.280> here,<00:07:21.480> Divvy 00:07:21.880 --> 00:07:24.640 being<00:07:22.200> one,<00:07:22.600> which<00:07:22.760> was<00:07:22.880> sold<00:07:23.240> to<00:07:23.400> Bill. 00:07:24.640 --> 00:07:31.880 Um<00:07:24.840> actually,<00:07:25.160> Divvy<00:07:25.400> probably<00:07:25.680> is<00:07:25.919> similar<00:07:26.440> to<00:07:26.560> what<00:07:26.720> you<00:07:26.840> do<00:07:27.360> in<00:07:27.680> some<00:07:27.919> ways<00:07:28.240> and<00:07:28.480> and<00:07:28.720> probably<00:07:29.600> uh<00:07:29.680> some<00:07:30.000> some<00:07:30.240> big<00:07:30.400> differences<00:07:30.880> there,<00:07:31.080> too. 00:07:31.880 --> 00:07:36.200 And,<00:07:32.160> you<00:07:32.240> know,<00:07:32.400> like<00:07:32.640> a<00:07:32.720> Brex,<00:07:33.320> I<00:07:33.400> think,<00:07:33.640> is<00:07:33.760> probably<00:07:34.560> in<00:07:34.800> your<00:07:35.000> category,<00:07:35.680> as<00:07:35.880> well. 00:07:36.200 --> 00:07:45.320 And<00:07:36.320> I'm<00:07:36.880> 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banking<00:07:51.760> system<00:07:52.120> and<00:07:52.200> then<00:07:52.360> they<00:07:52.560> they<00:07:52.680> realize<00:07:53.040> like<00:07:53.200> you 00:07:53.320 --> 00:08:00.400 need<00:07:53.520> a<00:07:53.600> bank<00:07:54.000> to<00:07:54.120> partner<00:07:54.520> with<00:07:54.800> or<00:07:54.960> we're<00:07:55.080> going<00:07:55.200> to<00:07:55.280> disrupt<00:07:55.800> American<00:07:56.160> Express<00:07:56.520> but<00:07:56.760> you<00:07:56.920> kind<00:07:57.120> of<00:07:57.160> like<00:07:57.840> the<00:07:58.200> the<00:07:58.360> better<00:07:58.720> approach<00:07:59.200> has<00:07:59.400> always<00:07:59.760> seemed<00:08:00.000> to<00:08:00.120> me, 00:08:00.400 --> 00:08:05.400 you<00:08:00.520> tell<00:08:00.720> me<00:08:00.840> if<00:08:01.000> I'm<00:08:01.800> uh<00:08:01.880> off<00:08:02.080> base<00:08:02.360> here,<00:08:03.080> has<00:08:03.320> been<00:08:03.480> to<00:08:03.560> collaborate. 00:08:05.400 --> 00:08:10.040 With<00:08:05.600> them.<00:08:06.160> And<00:08:06.280> I<00:08:06.600> I<00:08:06.680> think<00:08:06.880> you<00:08:07.000> will<00:08:07.240> disrupt<00:08:07.640> them<00:08:07.920> at<00:08:08.120> some<00:08:08.280> point,<00:08:08.600> but<00:08:08.760> you<00:08:08.840> know<00:08:08.920> what<00:08:09.040> I<00:08:09.080> mean? 00:08:10.040 --> 00:08:15.840 What<00:08:10.080> do<00:08:10.160> you<00:08:10.200> think<00:08:10.320> of<00:08:10.400> that?<00:08:10.920> So<00:08:11.080> Glenn,<00:08:11.320> it's<00:08:11.480> funny<00:08:11.720> you<00:08:11.800> should<00:08:11.960> mention<00:08:12.240> that,<00:08:12.440> but<00:08:12.600> actually<00:08:13.560> the<00:08:13.720> ramps,<00:08:14.120> the<00:08:14.200> brex's,<00:08:14.919> and<00:08:15.000> the<00:08:15.080> divvys<00:08:15.440> of<00:08:15.520> this<00:08:15.640> world 00:08:15.840 --> 00:08:18.240 did<00:08:16.080> set<00:08:16.360> out<00:08:16.560> to<00:08:16.680> disrupt.<00:08:17.800> Yeah. 00:08:18.240 --> 00:08:26.800 Oh<00:08:18.320> yeah.<00:08:19.160> And<00:08:19.360> we<00:08:19.640> I<00:08:19.760> think<00:08:20.040> we're<00:08:20.280> the<00:08:21.000> a<00:08:21.040> little<00:08:21.200> bit<00:08:21.320> the<00:08:21.440> antidote<00:08:22.000> to<00:08:22.120> that<00:08:23.040> because<00:08:24.240> we<00:08:24.520> actually<00:08:25.080> don't<00:08:25.400> issue,<00:08:25.800> we<00:08:25.919> don't<00:08:26.160> underwrite,<00:08:26.720> we're 00:08:26.800 --> 00:08:35.039 not<00:08:26.960> asking<00:08:27.200> you<00:08:27.280> to<00:08:27.400> change<00:08:27.720> cards<00:08:28.040> at<00:08:28.160> all.<00:08:28.960> Actually,<00:08:29.280> we<00:08:29.520> have<00:08:30.000> partnered<00:08:30.480> with<00:08:31.200> the<00:08:31.320> banks<00:08:32.440> to<00:08:32.560> essentially<00:08:33.360> distribute<00:08:33.880> software<00:08:34.400> that<00:08:34.640> helps<00:08:34.960> to 00:08:35.039 --> 00:08:39.760 make<00:08:35.320> the<00:08:35.440> cards<00:08:35.840> that<00:08:35.960> people<00:08:36.200> already<00:08:36.440> have<00:08:36.800> in<00:08:36.880> their<00:08:37.080> possession<00:08:38.159> more<00:08:38.520> powerful. 00:08:39.760 --> 00:08:48.080 And<00:08:40.080> really<00:08:40.840> the<00:08:41.000> key<00:08:41.360> to<00:08:41.520> our<00:08:41.640> company<00:08:42.039> has<00:08:42.159> always<00:08:42.400> been<00:08:43.440> actually<00:08:43.760> the<00:08:43.960> 16<00:08:44.480> digits<00:08:45.280> or<00:08:45.440> the<00:08:45.560> 15<00:08:46.080> if<00:08:46.240> you're<00:08:46.400> American<00:08:46.760> Express<00:08:47.880> should 00:08:48.080 --> 00:08:54.120 enable<00:08:48.560> you<00:08:48.720> to<00:08:48.839> access<00:08:49.200> this<00:08:49.360> software.<00:08:49.880> You<00:08:50.040> shouldn't<00:08:50.280> need<00:08:50.400> to<00:08:50.520> speak<00:08:50.760> to<00:08:50.839> a<00:08:50.880> banker,<00:08:51.360> you<00:08:51.520> shouldn't<00:08:51.839> need<00:08:52.200> 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they<00:09:20.880> do<00:09:21.000> your<00:09:21.120> ACH,<00:09:21.400> and<00:09:21.560> all<00:09:21.760> sorts<00:09:22.000> of<00:09:22.120> other<00:09:22.320> things,<00:09:22.680> right? 00:09:22.839 --> 00:09:27.360 With<00:09:22.960> a<00:09:23.000> bank<00:09:23.240> partner.<00:09:24.040> And<00:09:24.120> let<00:09:24.240> me<00:09:24.360> marry<00:09:24.720> that<00:09:25.320> with<00:09:25.480> a<00:09:25.520> relationship<00:09:26.160> you<00:09:26.280> have. 00:09:27.360 --> 00:09:35.480 Because<00:09:27.600> I<00:09:27.680> think<00:09:27.920> that's<00:09:28.360> really<00:09:29.200> where<00:09:29.360> you<00:09:29.440> start<00:09:29.800> to<00:09:29.920> think<00:09:30.240> that's<00:09:30.440> what<00:09:30.640> most<00:09:31.320> companies<00:09:31.839> are<00:09:31.920> looking<00:09:32.280> for<00:09:32.920> is<00:09:33.080> actually<00:09:33.360> for<00:09:33.480> their<00:09:33.600> existing<00:09:34.080> card<00:09:34.400> to<00:09:34.480> do<00:09:34.680> more 00:09:35.480 --> 00:09:38.560 because<00:09:35.800> the<00:09:35.880> relationship<00:09:36.600> is<00:09:36.839> really<00:09:37.120> key<00:09:37.440> to<00:09:37.600> them,<00:09:38.320> right? 00:09:38.560 --> 00:09:45.480 Across<00:09:38.880> many<00:09:39.120> more<00:09:39.360> dimensions.<00:09:40.800> Yeah<00:09:40.920> cuz<00:09:41.160> then<00:09:41.400> you're<00:09:41.840> you're<00:09:42.160> adding<00:09:42.840> different<00:09:43.320> layers<00:09:43.800> of<00:09:43.920> things<00:09:44.200> that<00:09:44.320> you<00:09:44.400> need<00:09:44.560> to<00:09:44.840> keep<00:09:45.080> track<00:09:45.360> of. 00:09:45.480 --> 00:09:50.320 It's<00:09:45.560> not<00:09:45.680> like<00:09:45.840> you<00:09:45.920> get<00:09:46.080> rid<00:09:46.280> of<00:09:46.360> a<00:09:46.440> bank,<00:09:46.960> right?<00:09:47.160> You<00:09:47.280> still<00:09:47.480> need<00:09:47.640> it<00:09:47.760> for<00:09:47.840> all<00:09:47.960> the<00:09:48.040> things<00:09:48.240> 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00:10:17.200 Um<00:10:14.600> from<00:10:14.840> an<00:10:15.040> AI<00:10:15.400> perspective,<00:10:16.080> how<00:10:16.280> are<00:10:16.400> you<00:10:16.600> using<00:10:17.000> it? 00:10:17.200 --> 00:10:20.960 How<00:10:17.320> are<00:10:17.440> you<00:10:17.600> thinking<00:10:18.000> about<00:10:18.320> it?<00:10:18.480> How<00:10:18.640> is<00:10:18.800> it<00:10:18.920> disrupting<00:10:19.440> fintech? 00:10:20.960 --> 00:10:24.280 No,<00:10:21.120> look,<00:10:21.280> it's<00:10:21.520> it's<00:10:21.840> it's<00:10:22.040> a<00:10:22.320> it's<00:10:22.480> a<00:10:22.520> question<00:10:22.880> that<00:10:23.000> everyone<00:10:23.280> asks<00:10:23.520> every<00:10:23.720> day,<00:10:23.960> right? 00:10:24.280 --> 00:10:27.280 Is<00:10:24.480> kind<00:10:24.640> of<00:10:24.720> if<00:10:24.800> you're<00:10:24.880> not<00:10:25.040> using<00:10:25.320> AI<00:10:25.640> then<00:10:25.840> then<00:10:26.040> you<00:10:26.160> kind<00:10:26.400> of<00:10:26.480> 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00:11:26.080 --> 00:11:31.320 It<00:11:26.240> knows,<00:11:27.120> right?<00:11:27.360> So<00:11:27.520> many<00:11:27.720> more<00:11:27.960> things<00:11:28.800> that<00:11:28.920> means<00:11:29.240> you<00:11:29.440> don't<00:11:29.640> have<00:11:29.800> to<00:11:30.000> to<00:11:30.080> go<00:11:30.200> and<00:11:30.320> do<00:11:30.440> yourself. 00:11:31.320 --> 00:11:34.760 And<00:11:31.440> the<00:11:31.480> reality<00:11:31.760> is<00:11:31.880> a<00:11:31.960> machine's<00:11:32.360> less<00:11:32.560> likely<00:11:32.800> to<00:11:32.880> make<00:11:33.000> a<00:11:33.080> mistake<00:11:33.440> than<00:11:33.600> you<00:11:33.840> are. 00:11:34.760 --> 00:11:38.160 The<00:11:34.880> other<00:11:35.120> piece<00:11:35.560> is<00:11:36.320> when<00:11:36.480> we<00:11:36.640> capture<00:11:37.480> receipts,<00:11:38.000> right? 00:11:38.160 --> 00:11:42.400 We<00:11:38.240> allow<00:11:38.560> people<00:11:38.880> in<00:11:39.160> to<00:11:39.840> mail<00:11:40.240> 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company<00:28:45.120> you've<00:28:45.320> built.<00:28:45.640> Thanks<00:28:45.800> for<00:28:45.920> spending<00:28:46.200> some<00:28:46.360> time<00:28:46.600> with<00:28:46.760> us. 00:28:46.920 --> 00:28:53.120 We<00:28:47.040> should<00:28:47.240> check<00:28:47.600> in<00:28:48.160> again<00:28:48.560> in<00:28:48.640> a<00:28:48.680> year<00:28:48.960> or<00:28:49.040> so<00:28:49.280> and<00:28:49.400> see<00:28:49.520> how<00:28:49.640> things<00:28:49.880> are<00:28:49.960> going,<00:28:50.280> but<00:28:50.800> really<00:28:51.040> appreciate<00:28:51.480> you<00:28:51.560> coming<00:28:51.760> on<00:28:51.840> the<00:28:51.920> show. 00:28:53.120 --> 00:28:57.200 No,<00:28:53.360> Clint,<00:28:53.640> thanks<00:28:53.840> for<00:28:53.960> having<00:28:54.120> me<00:28:54.200> on<00:28:54.280> the<00:28:54.320> show.<00:28:54.600> Really<00:28:54.800> appreciate<00:28:55.200> it. ``` ### Gravyty CEO Justin Beck: How AI is transforming student engagement URL: https://www.ceo.com/episodes/gravyty-ceo-justin-beck-how-ai-is-transforming-student-engagement/ Last updated: 2026-08-23T16:29:14.000Z # Why Justin Beck thinks every campus needs AI A university financial aid office recently discovered that 60 percent of the questions coming in weren't about financial aid. They were about housing and enrollment. The students weren't lost. The system was. Justin Beck told that story on the CEO.com podcast. He runs Gravyty, which sells AI-powered engagement tools to universities, private K-12 schools, and nonprofits, and his diagnosis of higher education is simple: the student experience is scattered across systems that don't talk to each other. "Higher education institutions today have a collection of core systems: student information systems, CRMs, support platforms, learning management systems, and more," he said on the CEO.com podcast. "The challenge is that all of these systems tend to create silos across the student experience." Beck has spent 25 years watching those systems get built. Apple and Blackboard during the early rise of online learning. Kaltura. Salesforce. Instructure, the Salt Lake City company that put the learning management system in the cloud. Then Xplor Technologies, where he was Chief Commercial Officer. [Gravyty named him CEO in August 2025](https://gravyty.com/blog/gravyty-names-justin-beck-ceo/?ref=ceo.com), after its [merger with Ivy.ai and Ocelot](https://gravyty.com/blog/gravyty-ivy-ai-and-ocelot-unite-to-transform-student-and-donor-engagement/?ref=ceo.com), two early builders of AI virtual assistants for campuses, and its [acquisition of Athlete Network](https://gravyty.com/blog/gravyty-acquires-athlete-network/?ref=ceo.com). K1 Investment Management, the private equity firm behind all three companies, assembled the pieces. The combined company serves more than 2,700 education and nonprofit organizations, and Gravyty, Ivy.ai, and Ocelot [each earned a spot on the 2025 Inc. 5000 list](https://gravyty.com/blog/gravyty-ivy-ai-and-ocelot-inc-5000/?ref=ceo.com) of America's fastest-growing private companies. Beck's job is to make three companies act like one. The case for AI in campus administration is arithmetic. "If you're getting 30,000 inquiries over a two-week enrollment period, you can't realistically scale staffing fast enough to handle that demand," Beck said. The knowledge-base approach ran into a different problem. Beck has a college-aged kid and has watched how that generation looks for answers. "They don't want to click through six pages trying to find an answer. They're already talking to the university, so they expect the university to know who they are and provide the answer immediately." He is wary of the grander claims, though. He was in the industry when MOOCs were supposed to replace the campus. "What was missing was the human connection," he said. "Students still wanted community, mentorship, and interaction." His bet is narrower than the hype: AI belongs in higher education where it clears administrative friction so the human parts of college can happen, not where it substitutes for them. Fundraising is where that bet gets tested. Public funding is shrinking. International enrollment, long a reliable revenue source, is harder to count on. Advancement offices know their top 150 or 200 donors extremely well. It's the thousands, sometimes hundreds of thousands, of other alumni, parents, and supporters they can't see. AI can read engagement data and surface the graduate who might give, Beck said. The institution still has to build the relationship. "It's not that different from sales prospecting." Then NIL arrived and created fundraisers who never asked to be fundraisers. Athlete Network, the Overland Park, Kansas company Gravyty acquired, was built to keep athletic departments connected with former athletes. Name, image, and likeness rules changed the job. "Overnight, athletic departments and coaches found themselves needing to become fundraisers," Beck said. A coach doesn't need the $1 million donor. He needs the everyday supporters willing to give $500 or $1,500 to a collective, and a tool his department can deploy without a large IT organization, because athletic departments generally don't have one. Beck calls it one of the fastest-growing parts of the business. Gravyty itself is mostly remote, with offices in Seattle and Israel. Beck brings teams together quarterly and runs the company on three principles: clarity and focus, empathy and human connection, and curiosity over judgment. He borrowed the last one from Ted Lasso. He thinks the industry is at a familiar inflection point. Learning management systems started as departmental experiments before universities adopted them wholesale. "I think we're entering that phase with AI," he said. Eighteen months ago, the experiments were academic, focused on content creation and tutoring. Now the questions are institutional. Every CEO.com interview ends the same way: who gave you a chance? Beck named Brett Frazier, who at Blackboard handed a restless 27-year-old a new sales team to lead, then a regional vice president role. The two are still friends. "He challenged me harder than anyone else ever has," Beck said. "Most importantly, he taught me to stay curious." ```chapters 00:00:00 Introduction and Background of Gravyty 00:00:22 Formation and Evolution of Gravyty 00:00:55 Justin's Career Journey 00:01:44 Justin's Experience in EdTech 00:02:05 Gravyty's Role in Higher Education 00:02:27 Integration with LMS and CRM Systems 00:03:11 Breaking Down Silos in Education 00:03:53 Future of Higher Education 00:04:25 Value of Campus Connections 00:05:07 Administrative Challenges in Education 00:05:33 Traditional Methods vs. AI Solutions 00:06:49 Impact of Government Funding Cuts 00:07:13 Enhancing Donor Engagement 00:08:17 AI in Fundraising and Advancement 00:09:46 NIL Deals and Athletic Departments 00:11:10 Role of University Presidents 00:13:46 Day in the Life of a CEO 00:16:51 Funding and Private Equity 00:19:49 Future of AI in Education 00:21:49 Book Recommendation: "The Score That Matters" 00:23:23 Building Company Culture 00:25:34 Macroeconomic Environment and Education 00:27:06 Importance of Trade and Vocational Programs 00:27:19 Reflecting on Career Opportunities 00:27:49 Conclusion and Farewell ``` ```vtt WEBVTT 00:00:00.000 --> 00:00:02.160 Justin,<00:00:00.560> thank<00:00:00.720> you<00:00:00.800> so<00:00:00.920> much<00:00:01.160> for<00:00:01.280> coming<00:00:01.560> on<00:00:01.680> the<00:00:01.760> show. 00:00:02.160 --> 00:00:04.800 You<00:00:02.400> are<00:00:02.600> the<00:00:03.080> CEO<00:00:03.920> of<00:00:04.080> Gravity. 00:00:04.800 --> 00:00:08.560 Tell<00:00:05.080> us<00:00:05.240> what<00:00:05.520> Gravity<00:00:06.080> is<00:00:06.560> and<00:00:06.680> how<00:00:06.800> you<00:00:06.920> became<00:00:07.280> the<00:00:07.400> CEO. 00:00:08.560 --> 00:00:11.320 Uh,<00:00:08.800> client,<00:00:09.160> appreciate<00:00:09.520> you<00:00:09.600> having<00:00:09.760> me.<00:00:09.840> It's<00:00:09.960> great<00:00:10.160> to<00:00:10.360> uh<00:00:10.440> connect<00:00:10.840> with<00:00:11.000> you<00:00:11.080> today. 00:00:11.320 --> 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things<00:00:50.040> like<00:00:50.200> virtual<00:00:50.600> chatbots,<00:00:51.200> virtual<00:00:51.520> assistants<00:00:52.520> to<00:00:53.000> from<00:00:53.320> recruiting<00:00:53.840> and<00:00:54.760> uh 00:00:54.840 --> 00:00:58.200 retention<00:00:55.520> all<00:00:55.680> the<00:00:55.760> way<00:00:55.920> to<00:00:56.120> alumni<00:00:56.640> and<00:00:56.760> fundraising<00:00:57.480> efforts. 00:00:58.200 --> 00:01:00.920 So,<00:00:58.800> second<00:00:59.120> part<00:00:59.320> of<00:00:59.400> that<00:00:59.480> question,<00:01:00.000> how'd<00:01:00.160> I<00:01:00.240> get<00:01:00.400> here? 00:01:00.920 --> 00:01:03.760 Um,<00:01:01.560> I've<00:01:01.680> spent<00:01:01.880> about<00:01:02.080> 25<00:01:03.240> years<00:01:03.520> now. 00:01:03.760 --> 00:01:07.240 It<00:01:03.840> makes<00:01:04.040> me<00:01:04.120> feel<00:01:04.320> super<00:01:04.640> old<00:01:05.199> in<00:01:05.440> the<00:01:05.720> uh<00:01:06.080> EdTech<00:01:06.520> space. 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--> 00:01:25.440 a<00:01:22.600> fast<00:01:23.200> fast-growth<00:01:23.840> VC-backed<00:01:24.480> organization. 00:01:25.440 --> 00:01:33.560 And<00:01:25.560> then<00:01:25.680> I've<00:01:25.800> rounded<00:01:26.240> off<00:01:26.360> a<00:01:26.400> couple<00:01:26.680> experiences<00:01:27.280> at<00:01:27.400> Salesforce<00:01:28.320> and<00:01:28.800> uh<00:01:28.880> the<00:01:28.960> current<00:01:29.600> online<00:01:30.080> leader<00:01:30.640> uh<00:01:30.760> Instructure<00:01:32.040> uh<00:01:32.480> based<00:01:32.760> out<00:01:32.880> of<00:01:32.960> Salt<00:01:33.200> Lake<00:01:33.320> City, 00:01:33.560 --> 00:01:36.040 which<00:01:33.720> I<00:01:33.800> believe<00:01:34.040> you<00:01:34.120> know<00:01:34.240> some<00:01:34.440> of<00:01:34.520> their<00:01:34.600> folks<00:01:34.920> fairly<00:01:35.160> fairly<00:01:35.400> well. 00:01:36.040 --> 00:01:44.400 And<00:01:36.560> um<00:01:37.040> and<00:01:37.160> then<00:01:37.400> recently<00:01:37.760> 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type<00:02:27.040> of<00:02:27.120> stuff? 00:02:27.959 --> 00:02:37.200 Yeah,<00:02:28.160> great<00:02:28.360> great<00:02:28.560> question.<00:02:28.880> So<00:02:29.120> so<00:02:29.280> with<00:02:29.440> Gravity's<00:02:29.920> goal<00:02:30.200> of<00:02:30.320> making<00:02:31.800> human<00:02:32.240> connections<00:02:32.880> through<00:02:33.120> AI<00:02:33.959> scale<00:02:34.520> through<00:02:34.840> scale<00:02:35.320> and<00:02:35.440> meaningful<00:02:35.880> connections 00:02:37.200 --> 00:02:41.000 through<00:02:37.640> communication,<00:02:38.280> access,<00:02:38.720> and<00:02:38.920> then<00:02:39.160> ultimately<00:02:39.600> support. 00:02:41.000 --> 00:02:44.920 You<00:02:41.120> know,<00:02:41.200> you<00:02:41.280> think<00:02:41.480> about<00:02:41.880> institutions<00:02:42.400> of<00:02:42.480> higher<00:02:42.640> education<00:02:43.080> today<00:02:43.480> have<00:02:44.000> their<00:02:44.200> host<00:02:44.480> systems. 00:02:44.920 --> 00:02:50.280 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education<00:03:50.760> is. 00:03:51.160 --> 00:03:53.840 I<00:03:51.200> mean,<00:03:51.400> what<00:03:51.519> is<00:03:51.720> the<00:03:51.840> future<00:03:52.160> of<00:03:52.280> education<00:03:52.920> even? 00:03:53.840 --> 00:03:56.160 Oh<00:03:54.080> my<00:03:54.200> gosh,<00:03:54.640> like<00:03:54.840> that's<00:03:55.080> like<00:03:55.320> a<00:03:55.400> loaded<00:03:55.800> question. 00:03:56.160 --> 00:04:04.960 We'll<00:03:56.280> be<00:03:56.400> here<00:03:56.520> for<00:03:56.640> 3<00:03:56.840> hours,<00:03:57.120> but<00:03:57.880> um<00:03:58.360> I<00:03:58.480> do<00:03:58.720> think<00:03:59.600> um<00:04:00.040> institutions<00:04:00.960> today<00:04:01.560> are<00:04:01.800> really<00:04:02.120> really<00:04:02.400> recognizing<00:04:03.120> that<00:04:03.320> like<00:04:03.600> the<00:04:03.760> value<00:04:04.760> that 00:04:04.960 --> 00:04:10.920 they're<00:04:05.200> able<00:04:05.480> to<00:04:05.640> provide<00:04:06.360> to<00:04:06.680> to<00:04:06.920> students<00:04:08.080> uh<00:04:08.160> is<00:04:08.640> the<00:04:08.800> packaging<00:04:09.520> of<00:04:09.640> a<00:04:09.720> variety<00:04:10.320> of<00:04:10.400> experience. 00:04:10.920 --> 00:04:18.640 Not<00:04:11.160> only<00:04:11.360> from<00:04:11.560> like<00:04:11.760> the<00:04:11.880> content<00:04:12.440> they<00:04:12.520> get<00:04:12.680> delivered,<00:04:13.440> the<00:04:13.920> professorial<00:04:14.680> connections<00:04:15.440> they<00:04:15.600> build,<00:04:15.880> the<00:04:15.959> relationships<00:04:16.760> they<00:04:16.920> build,<00:04:17.440> whether<00:04:17.720> in<00:04:17.840> an<00:04:18.040> online 00:04:18.640 --> 00:04:25.240 or<00:04:18.799> campus<00:04:19.320> experience.<00:04:20.720> Um<00:04:20.959> that's<00:04:21.280> that's<00:04:21.560> the<00:04:21.640> value<00:04:21.880> because<00:04:22.120> you<00:04:22.200> know<00:04:22.360> I<00:04:22.720> I<00:04:23.040> actually<00:04:23.320> had<00:04:23.480> 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going<00:04:51.640> to<00:04:51.800> drive<00:04:52.280> to<00:04:52.440> job<00:04:52.800> outcomes. 00:04:53.640 --> 00:04:57.320 Where<00:04:53.840> we<00:04:53.960> get<00:04:54.120> to<00:04:54.200> step<00:04:54.480> in<00:04:54.600> and<00:04:54.720> help<00:04:55.240> is<00:04:55.480> on<00:04:55.640> the<00:04:55.760> administrative<00:04:56.560> side<00:04:56.800> of<00:04:56.919> things. 00:04:57.320 --> 00:05:03.440 Helping<00:04:57.640> remove<00:04:57.960> complexity,<00:04:59.000> helping<00:04:59.400> remove<00:05:00.520> um<00:05:01.000> people<00:05:01.280> that<00:05:01.360> get<00:05:01.560> stuck<00:05:02.320> in<00:05:02.480> certain<00:05:02.919> workflows. 00:05:03.440 --> 00:05:10.400 Like<00:05:03.600> if<00:05:03.720> you're<00:05:03.880> trying<00:05:04.240> to<00:05:04.680> you<00:05:04.760> know<00:05:04.880> I<00:05:05.000> we<00:05:05.240> we<00:05:05.400> were<00:05:05.480> with<00:05:05.640> a<00:05:05.720> customer<00:05:06.560> uh<00:05:06.800> 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have<00:05:20.440> you<00:05:20.600> noticed<00:05:21.080> about<00:05:21.480> how<00:05:22.000> higher<00:05:22.880> higher<00:05:23.200> education<00:05:23.720> institutions<00:05:24.160> or<00:05:24.280> really<00:05:24.480> just<00:05:24.680> any<00:05:24.840> educational<00:05:25.440> institution<00:05:25.880> because<00:05:26.040> I<00:05:26.080> know<00:05:26.240> you're<00:05:26.360> not 00:05:26.560 --> 00:05:31.280 just<00:05:26.760> higher<00:05:26.960> education?<00:05:27.840> Sure.<00:05:28.320> Um<00:05:28.840> how<00:05:29.040> were<00:05:29.240> how<00:05:29.440> were<00:05:29.560> they<00:05:29.760> previously<00:05:30.280> doing<00:05:30.560> this<00:05:30.720> without<00:05:31.080> you? 00:05:31.280 --> 00:05:37.960 I<00:05:31.360> imagine<00:05:31.840> it's<00:05:32.000> pretty<00:05:32.240> archaic.<00:05:33.520> Yeah,<00:05:33.919> it's<00:05:34.320> uh<00:05:34.480> they<00:05:34.680> they<00:05:34.880> have<00:05:35.000> been<00:05:35.200> trying<00:05:35.640> 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core<00:05:50.920> recruiting<00:05:51.480> or<00:05:51.600> right<00:05:51.800> before<00:05:52.200> your<00:05:52.360> financial<00:05:52.920> aids 00:05:53.160 --> 00:05:59.320 do.<00:05:53.640> You<00:05:53.760> just<00:05:54.200> you<00:05:54.920> you<00:05:55.120> couldn't<00:05:55.400> staff<00:05:55.720> up<00:05:56.080> to<00:05:56.200> something<00:05:56.640> that<00:05:56.880> large<00:05:57.080> or<00:05:57.200> during<00:05:57.480> that<00:05:57.800> open<00:05:58.120> enrollment<00:05:58.640> period. 00:05:59.320 --> 00:06:02.400 So,<00:05:59.800> they<00:06:00.200> they<00:06:00.360> they<00:06:00.600> struggled<00:06:01.240> with<00:06:01.360> those<00:06:01.560> type<00:06:01.720> of<00:06:01.800> things. 00:06:02.400 --> 00:06:09.840 Um<00:06:02.920> they've<00:06:03.080> tried<00:06:03.800> knowledge<00:06:04.240> bases<00:06:04.800> or<00:06:05.000> just<00:06:05.280> web<00:06:05.560> properties,<00:06:06.200> but<00:06:06.400> you<00:06:06.480> know,<00:06:06.640> 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want<00:06:18.640> a<00:06:18.760> super<00:06:19.120> quick<00:06:19.400> answer<00:06:19.880> that<00:06:20.040> they<00:06:20.160> can<00:06:20.360> ask<00:06:21.000> a<00:06:21.080> virtual<00:06:21.440> assistant<00:06:21.960> or<00:06:22.080> someone<00:06:22.440> super<00:06:22.680> quick,<00:06:23.200> and<00:06:23.360> they<00:06:23.480> don't<00:06:24.240> um<00:06:25.160> honestly<00:06:25.600> have<00:06:25.840> much<00:06:26.200> uh 00:06:26.480 --> 00:06:31.680 you<00:06:26.560> know,<00:06:26.640> this<00:06:26.760> sounds<00:06:26.919> terrible.<00:06:27.160> I'm<00:06:27.240> bashing<00:06:27.640> the<00:06:27.760> generation<00:06:28.200> that's<00:06:28.360> in<00:06:28.440> college<00:06:28.680> right<00:06:28.800> now,<00:06:28.919> but<00:06:29.040> they<00:06:29.120> don't<00:06:29.280> have<00:06:29.680> they<00:06:29.800> don't<00:06:29.960> have<00:06:30.080> like<00:06:30.760> uh<00:06:30.919> the<00:06:31.080> patience 00:06:31.680 --> 00:06:35.120 to<00:06:31.919> say,<00:06:32.520> "Hey,<00:06:32.760> I<00:06:32.840> actually<00:06:33.120> need<00:06:33.320> to<00:06:33.400> go<00:06:33.760> explore<00:06:34.240> this<00:06:34.480> elsewhere." 00:06:35.120 --> 00:06:40.160 Like,<00:06:35.320> "I'm<00:06:35.440> talking<00:06:35.760> to<00:06:35.840> my<00:06:35.919> university<00:06:36.360> right<00:06:36.560> now.<00:06:36.680> They<00:06:36.800> should<00:06:37.000> know<00:06:37.200> all<00:06:37.360> things<00:06:37.680> about<00:06:38.000> me,<00:06:38.080> and<00:06:38.200> I<00:06:38.240> should<00:06:38.440> be<00:06:38.520> able<00:06:38.680> to<00:06:38.760> provide<00:06:39.520> those<00:06:39.760> answers." 00:06:40.160 --> 00:06:49.680 So,<00:06:40.640> I<00:06:40.680> think<00:06:40.880> it's<00:06:41.000> been<00:06:41.760> um<00:06:42.280> through<00:06:42.480> scrappy<00:06:43.160> activities<00:06:44.000> as<00:06:44.320> well<00:06:44.840> as,<00:06:45.080> you<00:06:45.160> know,<00:06:45.280> 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state<00:07:00.160> of<00:07:00.240> Utah<00:07:00.680> where<00:07:00.840> you<00:07:00.960> mentioned<00:07:01.240> it<00:07:01.560> that<00:07:01.680> I'm<00:07:01.800> from<00:07:02.160> where<00:07:02.280> our<00:07:02.320> instructor's<00:07:02.800> from. 00:07:03.600 --> 00:07:09.080 Um<00:07:03.840> and<00:07:03.960> so,<00:07:04.120> I<00:07:04.200> imagine<00:07:04.600> it's<00:07:04.720> happening<00:07:05.080> in<00:07:05.160> all<00:07:05.320> 50<00:07:05.680> states,<00:07:06.640> which<00:07:06.840> makes<00:07:07.160> donor<00:07:07.600> engagement<00:07:08.200> even<00:07:08.440> more<00:07:08.680> important. 00:07:09.080 --> 00:07:13.840 So,<00:07:09.200> how<00:07:09.400> are<00:07:09.520> you<00:07:10.480> uh<00:07:10.680> providing<00:07:11.200> that<00:07:11.400> donor<00:07:11.760> engagement,<00:07:12.360> and<00:07:12.480> what<00:07:12.640> does<00:07:12.760> that<00:07:13.000> look<00:07:13.160> like? 00:07:13.840 --> 00:07:20.400 Yeah,<00:07:14.040> 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like<00:07:27.120> they<00:07:27.480> have<00:07:27.960> have<00:07:28.200> historically<00:07:28.960> as<00:07:29.200> well. 00:07:29.520 --> 00:07:34.520 So,<00:07:29.720> that's<00:07:30.240> been<00:07:30.440> a<00:07:30.760> you<00:07:30.840> know,<00:07:30.960> a<00:07:31.040> high<00:07:32.160> uh<00:07:32.360> ROI<00:07:33.080> return<00:07:33.720> to<00:07:33.840> the<00:07:33.960> university. 00:07:34.520 --> 00:07:37.120 So,<00:07:34.680> they're<00:07:34.960> getting<00:07:35.160> pressured<00:07:35.600> on<00:07:35.720> a<00:07:35.760> couple<00:07:36.320> different<00:07:36.600> perspectives. 00:07:37.120 --> 00:07:45.720 So,<00:07:37.320> what<00:07:37.440> does<00:07:37.560> that<00:07:37.680> mean?<00:07:38.160> It<00:07:38.280> means<00:07:38.520> your<00:07:39.120> domestic<00:07:40.040> face-to-face<00:07:40.680> and<00:07:40.800> online<00:07:41.200> students,<00:07:42.160> your<00:07:42.400> retention<00:07:43.080> requirement<00:07:43.720> to<00:07:43.800> 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to 00:09:50.960 --> 00:09:58.920 like<00:09:51.200> help<00:09:51.480> with<00:09:51.640> like<00:09:51.840> NIL<00:09:52.400> deals?<00:09:53.360> Like<00:09:53.520> as<00:09:53.640> you<00:09:53.720> were<00:09:53.800> saying<00:09:54.120> that<00:09:54.280> immediately<00:09:54.800> like<00:09:55.840> came<00:09:56.080> to<00:09:56.160> mind<00:09:56.520> with<00:09:56.640> the<00:09:56.760> whole<00:09:56.960> sports<00:09:57.360> side<00:09:57.520> of<00:09:57.640> things<00:09:58.000> and<00:09:58.160> like<00:09:58.760> there's 00:09:58.920 --> 00:10:04.160 a<00:09:59.000> lot<00:09:59.200> of<00:09:59.240> people<00:09:59.480> trying<00:09:59.720> to<00:09:59.840> do<00:10:00.040> that<00:10:00.280> but<00:10:00.440> you<00:10:00.880> want<00:10:01.120> somebody<00:10:01.360> who<00:10:01.440> like<00:10:01.920> actually<00:10:02.240> knows<00:10:02.440> what<00:10:02.560> they're<00:10:02.720> doing<00:10:03.160> to<00:10:03.240> be<00:10:03.360> able<00:10:03.480> 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day<00:27:57.200> for<00:27:57.360> the<00:27:57.440> career<00:27:57.760> journey<00:27:58.080> he<00:27:58.200> kicked<00:27:58.480> off<00:27:58.680> for<00:27:58.840> me. 00:27:59.880 --> 00:28:01.960 That's<00:28:00.120> awesome.<00:28:00.400> Justin,<00:28:00.720> thank<00:28:00.880> you<00:28:00.960> so<00:28:01.080> much<00:28:01.280> for<00:28:01.360> coming<00:28:01.640> on. 00:28:01.960 --> 00:28:04.280 Congrats<00:28:02.400> on<00:28:02.480> everything.<00:28:03.480> It's<00:28:03.600> an<00:28:03.680> incredible<00:28:04.040> company. 00:28:04.280 --> 00:28:09.080 It's<00:28:04.400> a<00:28:04.440> very<00:28:04.640> needed<00:28:04.960> company<00:28:05.480> that,<00:28:05.760> that<00:28:05.920> you're<00:28:06.040> building,<00:28:06.480> and<00:28:06.560> let's<00:28:06.720> have<00:28:06.880> you<00:28:06.960> back<00:28:07.240> on<00:28:07.360> in<00:28:07.480> the<00:28:07.600> year<00:28:07.800> and<00:28:07.920> see<00:28:08.000> how<00:28:08.120> you're<00:28:08.240> doing. 00:28:09.080 --> 00:28:11.600 Uh,<00:28:09.280> Clint,<00:28:09.600> I<00:28:09.640> appreciate<00:28:10.080> this.<00:28:10.240> I<00:28:10.280> hope<00:28:10.440> you<00:28:10.560> and<00:28:10.680> everybody<00:28:10.960> have<00:28:11.040> a<00:28:11.080> great<00:28:11.240> day. 00:28:11.600 --> 00:28:13.800 Thank<00:28:11.800> you. ``` ### Mochi Founder & CEO Dr. Myra Ahmad: How GLP-1s are transforming healthcare URL: https://www.ceo.com/episodes/mochi-founder-ceo-dr-myra-ahmad-how-glp-1s-are-transforming-healthcare/ Last updated: 2026-08-23T17:04:22.000Z # Myra Ahmad bet her company on the word "personalized" On April 20, a federal judge in San Francisco [ruled](https://www.courthousenews.com/wp-content/uploads/2026/04/eli-lilly-vs-mochi-health-order.pdf?ref=ceo.com) that Eli Lilly's lawsuit against Mochi Health can go forward. Judge Jacqueline Scott Corley had thrown out Lilly's first complaint in October for failing to establish that Lilly was harmed at all. The amended version cleared that bar, and two claims survived: unfair competition under California law and false advertising under the federal Lanham Act. Lilly alleges Mochi Health, a corporation without a medical license, exercises control over the doctors who prescribe through it. It hires the physicians at the affiliated Mochi Medical entities, advertises for them, supplies diagnostic protocols, and trains their staff. It also, Lilly says, changed the dose and formulation of patients' compounded tirzepatide three separate times, in December 2024, March 2025, and September 2025, driven by shifting pharmacy partnerships rather than any clinical indication. California prohibits lay corporations from practicing medicine, and Corley found the allegations plausible enough to proceed. The California Medical Association filed a brief against Mochi's motion to dismiss, [according to Courthouse News](https://www.courthousenews.com/eli-lilly-can-proceed-with-lawsuit-against-telehealth-seller-of-weight-loss-drugs/?ref=ceo.com). The order is not uniformly bad for Mochi. Corley dismissed Lilly's civil conspiracy claim outright, finding no plausible agreement among Mochi Health, the Mochi Medical entities, and Aequita Pharmacy, all named defendants. Mere association, she wrote, is not a conspiracy. She also declined to infer that Mochi forced any physician to write a particular prescription, noting the allegations do not support that. Discovery is now open. Mochi said it was pleased with the ruling and "remain confident in our position." Aequita is the other thread. A year before the ruling, Washington State [ordered](https://doh.wa.gov/newsroom/pharmacy-quality-assurance-commission-issues-limited-stop-service-license-pharmacy?ref=ceo.com) the Kirkland pharmacy to stop compounding after it failed to implement a state-approved plan to correct deficient practices. The commission alleged those practices included letting untrained and unqualified staff perform sterile compounding. Mochi [responded](https://joinmochi.com/blog/aequita-quality-reports?ref=ceo.com) by publishing third-party certificates of analysis for recent batches, saying it would not resume work with Aequita until the state cleared it, and characterizing the state's concerns as matters of reporting structure and operations. The Washington notice describes something more than paperwork. This is the company Dr. Myra Ahmad came to talk about on the CEO.com Podcast. She is a physician trained at the University of Washington who founded Mochi in 2022 and reached profitability within a year. "We raised funding in March 2022," she said. "Then by late 2022, we became profitable and have continued operating off existing cash flow since then." She raised once. Hims & Hers, Ro, and Noom took hundreds of millions of venture dollars into the same market. Mochi grew on its own revenue instead, and by [July 2025](https://joinmochi.com/blog/mochi-health-patients-lose-over-3-million-pounds-combined?ref=ceo.com) reported 500% year-over-year growth, licensure in all 50 states, and patients who had collectively lost more than 3 million pounds. That November, it [announced](https://www.globenewswire.com/news-release/2025/11/12/3186360/0/en/Mochi-Health-Expands-Beyond-Obesity-Care-with-Comprehensive-Digital-Health-Platform-Adding-15-New-Categories-of-Care.html?ref=ceo.com) an expansion into 15 new specialty areas, putting a catalog of more than 120 conditions in front of over 500 affiliated providers. Ahmad describes the model as a marketplace rather than a pipeline. "I usually compare it to DoorDash versus Domino's." Patients choose the provider and the pharmacy; the company sells access, not a single product. The lawsuit went unmentioned in the conversation. But her defense of compounding, the practice at the center of it, ran through the whole hour. "Compounding is actually a longstanding and very normal part of pharmacy practice," she said. It already happens in IVF, pediatrics, and skincare, she pointed out, without anyone objecting. Applied to obesity drugs, it lets a provider adjust dose and formulation to a patient's side effects. "It's really personalized medicine." The FDA has since narrowed the ground further, advising that a compounded drug combining a GLP-1 with another active ingredient such as a vitamin may still count as essentially a copy of the approved product. Ahmad says tailoring is the company's entire point. On the medicine itself, her ground is firmer. "If someone comes to a doctor for depression or anxiety, providers discuss medications and treatment options openly," she said. "Historically, obesity wasn't treated that way." She has watched the category she works in become a culture-war object and does not hide her irritation. "Honestly, I've never seen a medication category receive this much vitriol." The population data is on her side. [Gallup](https://news.gallup.com/poll/712157/glp-usage-reaches-new-high.aspx?ref=ceo.com) finds the adult obesity rate has fallen from a 2022 peak of 39.9% to 36.4%, a decline it calls statistically meaningful and says tracks inversely with GLP-1 use. Current use has climbed from 3% of adults in 2024 to 11% this year. Ahmad credits the medications. Only 19% of current GLP-1 users are on a compounded version, against 68% on brand-name products. And the traffic runs mostly one way for one reason: 35% of compounded users switched from a brand name, while just 10% went the other direction, and those moving toward compounded were twice as likely to cite cost. Price is where the pressure lands, and it comes from an unexpected direction. Under the White House's [November agreements](https://www.whitehouse.gov/fact-sheets/2025/11/fact-sheet-president-donald-j-trump-announces-major-developments-in-bringing-most-favored-nation-pricing-to-american-patients/?ref=ceo.com) with Lilly and Novo Nordisk, Medicare pays $245 a month for Ozempic, Wegovy, Mounjaro, and Zepbound against a $50 patient copay; cash buyers pay about $350 through the TrumpRx platform, and Medicare covers Wegovy and Zepbound for obesity for the first time. Cheap branded drugs erode the discount that made compounded versions attractive. Ahmad chooses to see the policy as an ally. "Anything that removes unnecessary middle layers from healthcare tends to improve access and reduce costs for patients." Mochi has been adjusting all the same, adding generics to its catalog and, [this month](https://joinmochi.com/blog/per-dose-pricing-mochi-health?ref=ceo.com), replacing its flat medication rate with per-dose pricing that drops compounded semaglutide to $60 at the lowest dose. Tariffs, the year's other macro story, mostly missed her. Compounding pharmacies manufacture domestically. "At one point, we had a quarter-million water bottles stuck on boats for months," she said. "Our biggest tariff story was cardboard boxes and shipping delays." The company is fully in person in San Francisco, built its own medical records system, and leans hard on lawyers. "Healthcare is simply much more regulated than traditional SaaS businesses." Medical school showed her where the system fails patients. It taught her nothing about the money. "Doctors often graduate without understanding how money actually moves through healthcare systems." Asked who gave her a chance, she named her team. "Every one of them had many other opportunities available to them, and they chose to help build this vision together." ```chapters 00:00:00 Introduction and Welcome 00:00:13 What is Mochi? 00:00:31 Revolution in Metabolic Health 00:01:01 Mochi's Unique Approach 00:01:48 Future of Healthcare 00:02:11 Dr. Ahmad's Background and Inspiration 00:02:33 The Obesity Epidemic 00:03:37 Factors Contributing to Obesity 00:04:12 Socioeconomic Factors in Obesity 00:05:02 Government and Food Industry's Role 00:05:24 Decline in Obesity Rates 00:05:55 Anti-GLP-1 Sentiment 00:06:19 Medication Management and Supervision 00:07:29 Personalized Medication and Compounding 00:08:28 Understanding Compounded GLP-1s 00:09:47 Future of Personalized Medication 00:10:17 Why Drugs are Expensive 00:11:27 A Day in the Life of a CEO 00:12:05 Funding and Profitability 00:12:24 Competitive Landscape 00:13:18 Building the Team and Culture 00:13:37 Advantages of Starting in San Francisco 00:14:03 Startup Culture in San Francisco 00:14:55 Reading Recommendations for CEOs 00:15:29 Regulatory Hurdles in Health Tech 00:16:40 Transition from Medicine to Startup 00:17:42 Impact of Being an MD 00:18:29 Macroeconomic Environment 00:19:45 Political Impact on Healthcare 00:20:49 Final Question: Who Gave You a Chance? 00:21:21 Closing Remarks and Future Plans ``` ```vtt WEBVTT 00:00:00.000 --> 00:00:05.000 Dr.<00:00:00.560> Myra<00:00:01.120> Ahmad,<00:00:02.000> thank<00:00:02.240> you<00:00:02.360> so<00:00:02.680> much<00:00:03.200> for<00:00:03.400> joining<00:00:03.880> the<00:00:04.000> CEO.com<00:00:04.720> show. 00:00:05.000 --> 00:00:11.800 What<00:00:05.120> an<00:00:05.280> honor<00:00:05.560> to<00:00:05.680> have<00:00:05.960> you.<00:00:06.680> You<00:00:06.920> are<00:00:07.080> the<00:00:07.360> CEO<00:00:08.640> and<00:00:09.600> founder<00:00:10.400> of<00:00:10.760> Mochi. 00:00:11.800 --> 00:00:14.760 Tell<00:00:12.069> us<00:00:12.337> what<00:00:12.606> Mochi's<00:00:12.874> all<00:00:13.143> about.<00:00:13.411> <00:00:13.680> Yeah. 00:00:14.760 --> 00:00:20.160 Thank<00:00:15.000> you<00:00:15.080> so<00:00:15.160> much<00:00:15.320> for<00:00:15.440> having<00:00:15.760> me.<00:00:15.880> Mochi<00:00:16.440> is<00:00:17.160> a<00:00:18.200> marketplace<00:00:18.800> for<00:00:19.120> evidence-based<00:00:19.760> care. 00:00:20.160 --> 00:00:26.520 So<00:00:20.480> we<00:00:20.760> pride<00:00:20.960> ourselves<00:00:21.280> on<00:00:21.400> being<00:00:21.720> an<00:00:21.960> open<00:00:22.200> marketplace<00:00:22.680> for<00:00:22.800> providers<00:00:23.360> and<00:00:23.480> patients<00:00:23.880> to<00:00:24.040> get<00:00:24.360> access<00:00:24.680> to<00:00:24.800> whatever<00:00:25.080> care<00:00:25.280> they<00:00:25.440> need. 00:00:26.520 --> 00:00:31.720 Our<00:00:26.680> focus<00:00:27.040> for<00:00:27.160> the<00:00:27.240> past<00:00:28.200> couple<00:00:28.520> of<00:00:28.640> years<00:00:29.000> has<00:00:29.160> been<00:00:29.400> 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because<00:01:55.280> I<00:01:55.480> mean<00:01:56.120> like<00:01:56.600> 5<00:01:56.880> years<00:01:57.120> ago<00:01:57.360> even<00:01:57.720> I'd<00:01:57.880> go<00:01:58.040> to<00:01:58.120> the<00:01:58.200> doctor<00:01:58.480> and<00:01:58.560> I'm<00:01:58.600> like,<00:01:58.760> "Could<00:01:58.920> we<00:01:59.000> have<00:01:59.080> done 00:01:59.280 --> 00:02:01.680 this<00:01:59.496> over<00:01:59.712> Zoom?"<00:01:59.928> <00:02:00.144> Yeah.<00:02:00.360> <00:02:00.576> You<00:02:00.792> know<00:02:01.008> what<00:02:01.224> I<00:02:01.440> mean? 00:02:01.680 --> 00:02:04.880 Or<00:02:01.760> something<00:02:02.040> like<00:02:02.160> that.<00:02:02.840> And<00:02:02.960> now<00:02:03.120> you<00:02:03.280> can,<00:02:03.760> which<00:02:04.000> which<00:02:04.200> is<00:02:04.280> pretty<00:02:04.440> beautiful. 00:02:04.880 --> 00:02:08.479 What<00:02:05.320> what<00:02:05.560> inspired<00:02:06.200> you<00:02:06.720> to<00:02:06.880> start<00:02:07.200> Mochi? 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the<00:02:49.120> country,<00:02:49.400> right? 00:02:49.680 --> 00:02:54.520 It's<00:02:50.320> It's<00:02:50.600> in<00:02:50.959> diabetes,<00:02:51.480> you<00:02:51.600> see<00:02:51.760> it<00:02:51.880> in<00:02:52.080> so<00:02:52.280> many<00:02:52.480> of<00:02:52.560> the<00:02:52.640> comorbidities<00:02:53.280> from<00:02:53.560> obesity. 00:02:54.520 --> 00:03:01.400 Um<00:02:54.959> it's<00:02:55.400> it's<00:02:55.600> a<00:02:55.680> huge<00:02:56.080> fraction<00:02:56.480> of<00:02:56.560> the<00:02:56.640> population<00:02:57.600> if<00:02:57.760> you<00:02:57.880> include<00:02:59.080> obesity<00:02:59.640> and<00:02:59.920> all<00:03:00.040> of<00:03:00.120> the<00:03:00.200> other<00:03:00.360> comorbidities<00:03:00.840> associated. 00:03:01.400 --> 00:03:09.680 So,<00:03:02.200> um<00:03:02.800> I<00:03:02.920> think<00:03:03.320> our<00:03:04.320> our<00:03:04.600> goal<00:03:05.000> was<00:03:05.160> really<00:03:05.360> to<00:03:05.560> bring<00:03:05.920> awareness<00:03:06.440> that<00:03:06.720> obesity<00:03:07.280> is<00:03:07.600> a<00:03:07.640> medical<00:03:08.000> condition<00:03:08.440> that<00:03:08.880> that<00:03:09.120> deserves<00:03:09.600> the 00:03:09.680 --> 00:03:14.400 same<00:03:10.000> type<00:03:10.239> of<00:03:10.360> treatment<00:03:10.680> and<00:03:10.800> care<00:03:11.680> as<00:03:12.160> any<00:03:12.440> other<00:03:12.640> medical<00:03:12.920> condition<00:03:13.239> that<00:03:13.360> you<00:03:13.440> go<00:03:13.560> to<00:03:13.640> the<00:03:13.680> doctor<00:03:14.000> with,<00:03:14.239> right? 00:03:14.400 --> 00:03:22.320 You<00:03:14.480> go<00:03:14.760> in<00:03:15.519> for<00:03:16.200> depression<00:03:16.880> or<00:03:17.000> any<00:03:17.239> other<00:03:17.400> condition,<00:03:17.920> your<00:03:18.040> provider<00:03:18.440> is<00:03:18.519> going<00:03:18.640> to<00:03:18.720> talk<00:03:18.880> to<00:03:18.959> you<00:03:19.000> about<00:03:19.160> medication<00:03:19.720> options<00:03:20.880> um<00:03:21.160> and<00:03:21.360> build<00:03:21.560> a<00:03:21.600> care<00:03:21.840> plan<00:03:22.040> around 00:03:22.320 --> 00:03:26.080 that.<00:03:22.440> And<00:03:22.560> I<00:03:22.600> think<00:03:22.800> that<00:03:23.000> was<00:03:23.200> not<00:03:23.480> the<00:03:23.560> case<00:03:23.840> for<00:03:23.959> obesity<00:03:24.360> a<00:03:24.440> couple<00:03:24.680> of<00:03:24.720> years<00:03:24.880> ago. 00:03:26.080 --> 00:03:31.280 <00:03:26.275> Uh<00:03:26.470> do<00:03:26.665> you<00:03:26.861> have<00:03:27.056> like<00:03:27.251> a<00:03:27.446> take<00:03:27.641> or<00:03:27.836> an<00:03:28.032> opinion<00:03:28.227> on<00:03:28.422> like<00:03:28.617> how<00:03:28.812> it<00:03:29.007> got<00:03:29.203> so<00:03:29.398> out<00:03:29.593> of<00:03:29.788> control,<00:03:29.983> uh<00:03:30.178> particularly<00:03:30.374> in<00:03:30.569> the<00:03:30.764> United<00:03:30.959> States? 00:03:31.280 --> 00:03:34.360 Like<00:03:32.000> diabetes<00:03:32.800> and<00:03:32.880> obesity<00:03:33.360> and<00:03:33.480> all<00:03:33.720> that<00:03:33.840> type<00:03:34.040> of<00:03:34.120> stuff. 00:03:34.360 --> 00:03:37.360 Like<00:03:34.880> why<00:03:35.400> how<00:03:35.519> did<00:03:35.720> we<00:03:35.840> get<00:03:36.080> here? 00:03:37.360 --> 00:03:39.480 <00:03:37.696> Yeah.<00:03:38.032> That's<00:03:38.368> a<00:03:38.704> hard<00:03:39.040> question. 00:03:39.480 --> 00:03:41.440 I<00:03:39.519> mean,<00:03:39.680> there's<00:03:39.920> so<00:03:40.239> many<00:03:40.560> factors,<00:03:41.160> right? 00:03:41.440 --> 00:03:50.040 Obesity<00:03:42.680> um<00:03:42.959> the<00:03:43.080> Obesity<00:03:43.400> Medicine<00:03:43.680> Association<00:03:44.320> has<00:03:44.760> a<00:03:44.840> diagram<00:03:45.440> that<00:03:45.640> has<00:03:46.400> a<00:03:46.480> circle<00:03:47.280> of<00:03:48.040> the<00:03:48.480> the<00:03:48.600> 12<00:03:49.000> or<00:03:49.080> 13<00:03:49.440> contributors 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the<00:05:09.640> there's<00:05:10.200> there's<00:05:10.880> a<00:05:10.960> lot<00:05:11.320> of<00:05:11.600> complicating<00:05:12.200> factors<00:05:12.560> that<00:05:12.760> led<00:05:13.040> to<00:05:13.200> obesity,<00:05:13.600> and<00:05:13.720> I<00:05:13.760> think<00:05:13.960> we're 00:05:14.080 --> 00:05:18.200 just<00:05:14.240> excited<00:05:14.640> to<00:05:14.800> start<00:05:15.600> working<00:05:15.960> on<00:05:16.080> a<00:05:16.120> solution<00:05:16.520> to<00:05:16.600> actually<00:05:16.840> reverse<00:05:17.200> this<00:05:17.360> trend,<00:05:17.760> right? 00:05:18.200 --> 00:05:26.919 Nationwide,<00:05:18.960> the<00:05:19.080> last<00:05:19.360> couple<00:05:19.600> of<00:05:19.680> years<00:05:20.080> is<00:05:20.120> the<00:05:20.200> first<00:05:20.520> time<00:05:20.800> that<00:05:21.400> has<00:05:22.240> declined<00:05:23.280> nationwide<00:05:24.680> and<00:05:24.800> we're<00:05:24.919> seeing<00:05:25.200> so<00:05:25.480> many<00:05:26.880> of 00:05:26.919 --> 00:05:30.640 the<00:05:27.960> the<00:05:28.120> fallout<00:05:28.640> from<00:05:28.840> this<00:05:29.320> trickling<00:05:29.720> down,<00:05:30.040> right? 00:05:30.640 --> 00:05:38.200 Rates<00:05:30.919> of<00:05:31.000> diabetes<00:05:31.480> diagnosis<00:05:32.040> are<00:05:32.120> going<00:05:32.240> to<00:05:32.280> go<00:05:32.400> down,<00:05:32.720> rates<00:05:33.000> of<00:05:33.520> osteoarthritis,<00:05:34.520> urinary<00:05:34.880> incontinence,<00:05:35.400> sleep<00:05:35.680> apnea,<00:05:36.600> I<00:05:36.640> mean,<00:05:36.840> so<00:05:37.160> so<00:05:37.320> many<00:05:37.600> other<00:05:37.760> things. 00:05:38.200 --> 00:05:42.919 So<00:05:38.555> <00:05:38.910> What<00:05:39.265> do<00:05:39.620> you<00:05:39.975> attribute<00:05:40.330> that<00:05:40.685> decline<00:05:41.040> to? 00:05:42.919 --> 00:05:46.440 <00:05:43.399> Um<00:05:43.879> awareness<00:05:44.360> of<00:05:44.840> these<00:05:45.320> medications. 00:05:46.440 --> 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Like<00:06:02.440> the<00:06:02.560> kind<00:06:02.800> of<00:06:02.960> like<00:06:03.400> um<00:06:04.360> And<00:06:04.400> there's<00:06:04.640> I<00:06:04.760> I<00:06:04.880> want<00:06:05.000> to<00:06:05.080> say<00:06:05.160> there's<00:06:05.360> a<00:06:05.400> lot,<00:06:05.840> right? 00:06:06.040 --> 00:06:11.400 It's<00:06:06.160> not<00:06:06.280> like<00:06:06.400> the<00:06:06.480> COVID<00:06:06.880> vaccine<00:06:07.560> or<00:06:07.720> anything<00:06:08.000> like<00:06:08.160> that<00:06:08.320> where<00:06:08.440> people<00:06:08.720> are<00:06:08.840> And<00:06:08.960> it's<00:06:09.080> also<00:06:09.320> like<00:06:09.480> not<00:06:09.760> being<00:06:09.960> mandated<00:06:10.440> by<00:06:10.520> the<00:06:10.600> government,<00:06:10.920> things<00:06:11.080> like<00:06:11.200> that. 00:06:11.400 --> 00:06:16.520 But<00:06:11.520> like<00:06:12.320> um<00:06:12.920> you<00:06:13.040> know,<00:06:13.200> like<00:06:13.680> what<00:06:13.800> do<00:06:13.880> you<00:06:13.960> make<00:06:14.200> of<00:06:14.320> like<00:06:14.600> those<00:06:15.000> who<00:06:15.160> are<00:06:15.280> like<00:06:15.480> against<00:06:15.960> these<00:06:16.160> drugs? 00:06:16.520 --> 00:06:19.240 Cuz<00:06:16.680> those<00:06:16.880> people<00:06:17.280> are<00:06:17.640> out<00:06:17.840> there,<00:06:18.040> too. 00:06:19.240 --> 00:06:27.560 <00:06:19.565> I<00:06:19.890> feel<00:06:20.214> like<00:06:20.539> it's<00:06:20.864> interesting<00:06:21.189> because<00:06:21.514> I've<00:06:21.838> never<00:06:22.163> seen<00:06:22.488> a<00:06:22.813> medication<00:06:23.138> that<00:06:23.462> has<00:06:23.787> so<00:06:24.112> much<00:06:24.437> vitriol<00:06:24.762> against<00:06:25.086> it<00:06:25.411> when<00:06:25.736> I<00:06:26.061> mean,<00:06:26.386> people<00:06:26.710> are<00:06:27.035> getting<00:06:27.360> this 00:06:27.560 --> 00:06:31.400 from<00:06:27.760> their<00:06:27.960> doctor.<00:06:28.560> They're<00:06:29.120> 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compound<00:08:20.720> if 00:08:20.840 --> 00:08:27.480 I'm<00:08:20.919> not<00:08:21.040> mistaken,<00:08:21.520> correct<00:08:21.760> me<00:08:21.840> if<00:08:21.960> I'm<00:08:22.080> wrong,<00:08:22.840> that's<00:08:23.080> cheaper<00:08:23.520> is<00:08:23.640> like<00:08:23.840> is<00:08:24.360> is<00:08:24.440> the<00:08:24.520> difference<00:08:24.880> that<00:08:25.040> I<00:08:25.120> see<00:08:25.360> just<00:08:25.600> as<00:08:25.760> a<00:08:26.320> you<00:08:26.400> know,<00:08:26.880> total<00:08:27.120> novice. 00:08:27.480 --> 00:08:34.880 <00:08:27.907> Yeah.<00:08:28.333> Um<00:08:28.760> okay,<00:08:29.187> compounding<00:08:29.613> as<00:08:30.040> a<00:08:30.467> a<00:08:30.893> space<00:08:31.320> is<00:08:31.747> a<00:08:32.173> very<00:08:32.600> interesting<00:08:33.027> space<00:08:33.453> within<00:08:33.880> pharmacies. 00:08:34.880 --> 00:08:40.360 Um<00:08:35.520> basically,<00:08:36.000> compounded<00:08:36.479> medications<00:08:37.159> 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--> 00:09:32.080 It's<00:09:25.440> like,<00:09:25.640> "Hey,<00:09:25.800> we're<00:09:25.920> going<00:09:26.040> to<00:09:26.080> give<00:09:26.240> you<00:09:26.320> this<00:09:26.480> ingredient,<00:09:26.960> but<00:09:27.080> you<00:09:27.200> also<00:09:27.440> need<00:09:27.640> these<00:09:27.839> other<00:09:29.040> two<00:09:29.240> ingredients<00:09:29.960> or<00:09:30.040> whatever<00:09:30.600> specific<00:09:31.200> to<00:09:31.360> you." 00:09:32.080 --> 00:09:36.280 So<00:09:32.360> in<00:09:32.600> in<00:09:32.720> a<00:09:32.800> way<00:09:33.040> to<00:09:33.200> me,<00:09:33.480> how<00:09:33.720> I<00:09:33.839> hear<00:09:34.040> that<00:09:34.160> and<00:09:34.280> again,<00:09:34.520> I<00:09:34.760> I<00:09:34.800> don't<00:09:35.000> I<00:09:35.080> a<00:09:35.640> dog<00:09:35.920> in<00:09:36.000> the<00:09:36.080> fight. 00:09:36.280 --> 00:09:38.440 I<00:09:36.320> don't<00:09:36.440> know,<00:09:36.880> you<00:09:37.000> know,<00:09:37.200> 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00:10:30.600 No,<00:10:23.600> I<00:10:23.800> I<00:10:23.960> think<00:10:25.440> um<00:10:27.760> I<00:10:27.800> mean,<00:10:28.000> there's<00:10:28.240> so<00:10:28.400> many<00:10:28.640> different<00:10:28.960> people<00:10:29.240> in<00:10:29.360> the<00:10:29.440> food<00:10:29.640> chain. 00:10:30.600 --> 00:10:36.040 <00:10:30.803> Mhm.<00:10:31.006> <00:10:31.210> Right?<00:10:31.413> They're<00:10:31.616> manufactured<00:10:31.819> in<00:10:32.022> one<00:10:32.226> place<00:10:32.429> and<00:10:32.632> then<00:10:32.835> they're<00:10:33.038> sold<00:10:33.242> to<00:10:33.445> another<00:10:33.648> place<00:10:33.851> and<00:10:34.054> then<00:10:34.258> there's<00:10:34.461> a<00:10:34.664> whole<00:10:34.867> layer<00:10:35.070> of<00:10:35.274> big<00:10:35.477> pharma<00:10:35.680> marketing 00:10:36.040 --> 00:10:43.680 that's<00:10:36.240> happening<00:10:37.120> and<00:10:37.240> then<00:10:37.400> they're<00:10:37.520> sold<00:10:37.920> to<00:10:38.160> 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00:10:56.560 --> 00:11:00.160 That<00:10:56.720> a<00:10:56.760> huge<00:10:57.040> fraction<00:10:57.400> of<00:10:57.480> this<00:10:57.640> is<00:10:57.760> just<00:10:57.960> going<00:10:58.200> to<00:10:58.280> cover<00:10:58.560> for<00:10:59.080> required<00:10:59.520> health<00:10:59.680> insurance. 00:11:00.160 --> 00:11:09.839 So,<00:11:01.000> I<00:11:01.040> think<00:11:01.240> that's<00:11:01.400> one<00:11:01.520> of<00:11:01.560> the<00:11:01.640> more<00:11:01.839> interesting<00:11:02.200> arguments<00:11:02.600> I've<00:11:02.720> seen<00:11:03.040> from<00:11:03.200> people<00:11:03.480> who,<00:11:04.400> um,<00:11:05.000> are<00:11:06.320> critical<00:11:06.800> of,<00:11:07.600> who<00:11:07.760> are<00:11:07.880> really<00:11:08.120> anti-GLP-1,<00:11:09.600> right? 00:11:09.839 --> 00:11:16.640 Is<00:11:10.000> basically<00:11:10.440> it<00:11:10.600> is,<00:11:10.960> it<00:11:11.120> is<00:11:11.240> effectively<00:11:11.760> increasing<00:11:12.240> 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--> 00:16:24.640 <00:16:21.931> Um,<00:16:22.263> an,<00:16:22.594> an<00:16:22.926> electronic<00:16:23.257> medical<00:16:23.589> health<00:16:23.920> record. 00:16:24.640 --> 00:16:32.520 <00:16:24.929> Okay.<00:16:25.218> <00:16:25.508> It's<00:16:25.797> like<00:16:26.086> where,<00:16:26.375> where<00:16:26.665> all<00:16:26.954> of<00:16:27.243> the<00:16:27.532> data<00:16:27.822> goes<00:16:28.111> and<00:16:28.400> where<00:16:28.689> do<00:16:28.978> providers<00:16:29.268> put<00:16:29.557> their<00:16:29.846> notes<00:16:30.135> and<00:16:30.425> how<00:16:30.714> do<00:16:31.003> pharmacies<00:16:31.292> get<00:16:31.582> prescriptions<00:16:31.871> sent<00:16:32.160> in 00:16:32.520 --> 00:16:36.400 and<00:16:34.200> everything<00:16:34.520> that<00:16:34.640> connects<00:16:34.920> it<00:16:35.000> in<00:16:35.040> between. 00:16:36.400 --> 00:16:40.480 <00:16:36.577> When<00:16:36.754> you<00:16:36.931> went<00:16:37.109> to<00:16:37.286> medical<00:16:37.463> 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<00:17:08.430> It's<00:17:08.680> become<00:17:08.930> really<00:17:09.180> trendy.<00:17:09.430> <00:17:09.680> Really? 00:17:10.360 --> 00:17:18.600 Oh,<00:17:10.646> wow.<00:17:10.932> It's<00:17:11.218> awesome.<00:17:11.505> <00:17:11.791> Like,<00:17:12.077> really,<00:17:12.363> it's<00:17:12.649> become,<00:17:12.935> I<00:17:13.222> think<00:17:13.508> there's<00:17:13.794> a<00:17:14.080> lot<00:17:14.366> more<00:17:14.652> people<00:17:14.938> who<00:17:15.225> go<00:17:15.511> to<00:17:15.797> medical<00:17:16.083> school<00:17:16.369> who<00:17:16.655> want<00:17:16.942> to<00:17:17.228> do<00:17:17.514> healthcare<00:17:17.800> innovation 00:17:18.600 --> 00:17:20.560 and<00:17:18.959> and<00:17:19.160> tech<00:17:19.439> in<00:17:19.520> general.<00:17:20.360> So. 00:17:20.560 --> 00:17:23.680 <00:17:20.820> Well,<00:17:21.080> there's<00:17:21.340> probably<00:17:21.600> no<00:17:21.860> better,<00:17:22.120> you<00:17:22.380> know,<00:17:22.640> training<00:17:22.900> 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<00:21:03.015> Who<00:21:03.470> gave<00:21:03.925> me<00:21:04.380> a<00:21:04.835> chance?<00:21:05.290> Um,<00:21:05.745> my<00:21:06.200> team. 00:21:07.640 --> 00:21:16.000 I<00:21:07.760> think<00:21:08.000> my<00:21:08.120> team<00:21:08.840> is<00:21:09.120> exceptional<00:21:09.880> and<00:21:10.040> they<00:21:10.200> have,<00:21:11.200> they<00:21:11.320> had<00:21:12.000> tons<00:21:12.320> of<00:21:12.440> other<00:21:12.720> offers<00:21:13.200> and<00:21:13.360> tons<00:21:13.600> of<00:21:13.680> other<00:21:13.840> places<00:21:14.200> they<00:21:14.320> could<00:21:14.480> go<00:21:14.880> and<00:21:15.160> it<00:21:15.280> is<00:21:15.400> very<00:21:15.640> exciting 00:21:16.000 --> 00:21:21.800 to<00:21:16.080> get<00:21:16.240> to<00:21:16.320> work<00:21:16.480> with<00:21:16.600> them<00:21:16.760> every<00:21:16.960> day<00:21:17.400> and<00:21:18.240> realize<00:21:18.680> this<00:21:18.840> vision<00:21:19.160> of<00:21:19.280> making<00:21:19.560> health<00:21:19.720> care<00:21:19.840> more<00:21:19.960> accessible. 00:21:21.800 --> 00:21:23.880 <00:21:21.987> Dr.<00:21:22.173> Ammad,<00:21:22.360> thank<00:21:22.547> you<00:21:22.733> so<00:21:22.920> much<00:21:23.107> for<00:21:23.293> coming<00:21:23.480> on. 00:21:23.880 --> 00:21:26.840 Congratulations<00:21:24.680> on<00:21:24.760> what<00:21:24.920> you've<00:21:25.040> built.<00:21:25.280> It<00:21:25.400> really<00:21:25.640> is<00:21:25.760> so<00:21:25.880> impressive. 00:21:26.840 --> 00:21:32.840 I<00:21:26.960> highly<00:21:27.160> recommend<00:21:27.440> everybody<00:21:27.680> check<00:21:27.880> out<00:21:27.960> Mochi<00:21:28.320> Health<00:21:28.600> and<00:21:28.680> what<00:21:28.800> you're<00:21:28.920> building<00:21:29.440> and<00:21:29.640> let's<00:21:29.800> have<00:21:29.920> you<00:21:30.000> back<00:21:30.240> on<00:21:30.640> like<00:21:31.040> as<00:21:31.240> you<00:21:31.320> continue<00:21:31.680> to<00:21:31.760> grow<00:21:31.920> this<00:21:32.080> thing. 00:21:32.840 --> 00:21:36.160 <00:21:33.060> Yeah,<00:21:33.280> absolutely.<00:21:33.500> Thank<00:21:33.720> you<00:21:33.940> so<00:21:34.160> much. ``` ### Prometeo Co-Founder & Co-CEO Ximena Aleman: How AI is reshaping financial infrastructure URL: https://www.ceo.com/episodes/prometeo-co-founder-co-ceo-ximena-aleman-how-ai-is-reshaping-financial-infrastructure/ Last updated: 2026-08-23T17:03:18.000Z # Two failed startups taught Ximena Aleman what Latin America actually needed Prometeo connects more than 1,200 financial institutions across 11 countries through a single API. It is Latin America's largest open banking network. Two of the five largest banks in the world run on its infrastructure, and its [backers and clients](https://www.weforum.org/stories/authors/ximena-aleman/?ref=ceo.com) include JP Morgan, Citi, Santander, BBVA, PayPal Ventures, and Samsung Next. The company was bootstrapped for its first four years out of Montevideo, Uruguay, by three co-founders, one of whom studied journalism. That one is Ximena Aleman, Prometeo's co-founder and co-CEO. On the CEO.com Podcast, she talked about the decade of failed products that led to the company, what AI agents mean for financial infrastructure, and why she thinks culture is something a startup exports. [Prometeo](https://prometeoapi.com/en?ref=ceo.com) is her third fintech startup. The first, launched in 2015, was a digital wallet that ran account-to-account payments through WhatsApp. "At the time, it felt very avant-garde, almost sci-fi for fintech in Latin America," she said on the podcast. The second was a personal finance tool for micro-entrepreneurs, similar to Mint in the U.S. "It was a beautiful idea, but honestly, a very difficult business to monetize." Both companies ran into the same problem. The region had no API infrastructure, and every bank integration had to be built by hand, country by country. In 2018, she and her co-founders quit building products on top of rails that didn't exist and started building the rails. "We always thought about Prometeo as this giant highway for financial information and transactions across financial institutions and countries in Latin America," she said. Aleman has watched every wave of fintech in the region from the inside: lending first, then the financial inclusion era that produced Nubank, then payments companies like eBanx and Clip. "Eventually, we realized the real bottleneck wasn't just products. It was infrastructure," she said. Prometeo now sits under much of that activity, and since 2024 it has [operated in the U.S.](https://prometeoapi.com/en/blog/bank-account-verification?ref=ceo.com), where its account validation product reaches every American bank through one integration. The money came late and reluctantly. "Back in 2015 and 2016, the venture ecosystem in Uruguay wasn't very developed," Aleman said. "Most entrepreneurs were bootstrapping." When Prometeo's ambitions outgrew that, the company raised a pre-seed, a seed, and a round that closed in December 2023, [announced the following month as a $13 million raise](https://prometeoapi.com/en/blog/prometeo-series-a-funding?ref=ceo.com) led by Antler Elevate. [Bloomberg reported](https://www.bloomberg.com/news/articles/2024-01-22/uruguay-fintech-prometeo-to-staff-up-after-13-million-funding?ref=ceo.com) the round was oversubscribed after the company sought as much as $10 million. Aleman puts total funding at about $20 million, a lean number for a company wiring together the banking systems of 11 countries. She told the CEO.com Podcast that macro uncertainty mostly shows up in fundraising, not in demand. When budgets tighten, companies want cheaper, more automated financial operations, which is what Prometeo sells. Her days start before 6 a.m. She has six-year-old twins, and the morning workout is, in her words, "basically the only part of the day I fully control." Meetings run from 9 to 6:30, then family time, then, depending on the time zones in play across Latin America and the U.S., Slack and WhatsApp until 10. Prometeo has been remote-first since day one, years before COVID forced the question, and every November the entire company flies to Uruguay for an onsite week. Aleman measures culture by what leaves the building. "When someone leaves Prometeo, they carry part of our culture with them into whatever company they join next," she said. "You pay culture forward." The current bet is agentic finance. Prometeo launched an MCP that lets AI agents access financial institutions, accounts, payments, and receivables in real time, on the theory that agents will need the same standardized rails that fintechs did. Aleman is blunt about the constraint: "Trust is the core currency of financial services." So Prometeo does not hand agents the keys. Companies grant them access to specific accounts and payment environments with defined limits on what they can and cannot do. Regulators and the industry have started pulling the company into the room. Prometeo [joined the Financial Data and Technology Association](https://fdata.global/prometeo-becomes-newest-member-of-fdata/?ref=ceo.com) in January 2026, and in March, Nacha named Aleman one of its [15 Under 40 in Payments](https://www.nacha.org/news/nacha-honors-15-under-40-award-winners-2026?ref=ceo.com). She has argued in [American Banker](https://www.americanbanker.com/opinion/the-us-should-look-to-brazil-as-a-model-for-rolling-out-open-banking?ref=ceo.com) that the U.S. is well behind other countries on open banking and should look to Brazil as its model. Every CEO.com Podcast conversation ends with the same question, built on the belief that the chances one gives are just as important as the chances one takes: who gave you a chance? Aleman named her co-founders. "My background wasn't traditional for fintech at all. I studied journalism, not investment banking or engineering," she said. "They really believed in my ability to learn, adapt, persevere, and build." Then the first institutional check, from FJ Labs and Colonial Ventures. Then Interbank in Peru, the first financial institution willing to trust its infrastructure to a bootstrapped startup from Montevideo. ```chapters 00:00:00 Introduction and Background 00:00:19 Early FinTech Ventures 00:00:52 Building Prometeo 00:02:28 FinTech Ecosystem in Latin America 00:05:33 AI in FinTech 00:07:38 Security and Compliance in AI 00:10:36 Cryptocurrency Adoption in Latin America 00:14:03 A Day in the Life of Samantha 00:16:19 Funding and Investment Journey 00:18:39 Macroeconomic Environment Impact 00:20:44 Company Culture and Remote Work 00:24:40 The Importance of Giving Chances 00:26:32 Closing Remarks ``` ```vtt WEBVTT 00:00:00.000 --> 00:00:06.840 Ximena,<00:00:00.465> welcome<00:00:00.929> to<00:00:01.394> the<00:00:01.858> show.<00:00:02.323> You<00:00:02.788> are<00:00:03.252> the<00:00:03.717> co-founder<00:00:04.182> and<00:00:04.646> co-CEO<00:00:05.111> of<00:00:05.575> Prometeo,<00:00:06.040> right? 00:00:06.840 --> 00:00:12.600 Yes.<00:00:07.480> Yes.<00:00:07.840> Tell<00:00:08.000> me<00:00:09.000> what<00:00:09.240> it<00:00:09.400> is,<00:00:09.680> how<00:00:09.840> you<00:00:10.000> became<00:00:10.760> the<00:00:11.080> co-founder<00:00:11.680> and<00:00:11.800> co-CEO. 00:00:12.600 --> 00:00:15.800 I<00:00:12.640> want<00:00:12.800> to<00:00:12.880> know<00:00:13.040> everything<00:00:13.360> about<00:00:13.680> you.<00:00:13.800> I've<00:00:13.880> been<00:00:14.040> so<00:00:14.200> excited<00:00:14.560> to<00:00:14.640> talk<00:00:14.920> to<00:00:15.000> you. 00:00:15.800 --> 00:00:19.560 Give<00:00:15.960> me<00:00:16.120> a<00:00:16.200> sense<00:00:16.560> for<00:00:17.480> how<00:00:17.680> you<00:00:17.800> got<00:00:18.040> here. 00:00:19.560 --> 00:00:22.880 Okay.<00:00:20.920> So,<00:00:21.600> I'm<00:00:22.040> Uruguayan. 00:00:22.880 --> 00:00:30.120 I<00:00:22.960> live<00:00:23.160> in<00:00:23.400> Uruguay,<00:00:23.920> in<00:00:24.000> South<00:00:24.200> America.<00:00:25.560> I<00:00:25.640> have<00:00:25.840> a<00:00:26.200> I<00:00:26.280> have<00:00:26.440> been<00:00:26.720> a<00:00:26.840> fintech<00:00:27.200> entrepreneur<00:00:27.720> for<00:00:27.960> almost<00:00:28.480> 10<00:00:28.680> years<00:00:28.880> now. 00:00:30.120 --> 00:00:33.640 Actually,<00:00:30.440> Prometeo<00:00:30.920> is<00:00:31.120> my<00:00:31.280> third<00:00:31.920> fintech<00:00:32.279> startup. 00:00:33.640 --> 00:00:39.240 I<00:00:33.760> started<00:00:34.160> building<00:00:34.600> in<00:00:35.440> 2015,<00:00:37.520> like<00:00:37.680> a<00:00:37.720> digital<00:00:38.120> wallet. 00:00:39.240 --> 00:00:45.000 We<00:00:39.440> were<00:00:39.680> providing<00:00:41.280> account-to-account<00:00:42.520> transfers<00:00:43.200> or<00:00:43.360> payments<00:00:43.880> through<00:00:44.080> WhatsApp. 00:00:45.000 --> 00:00:53.840 It<00:00:45.120> was<00:00:45.280> pretty<00:00:45.520> avant-garde,<00:00:46.240> you<00:00:46.320> know,<00:00:46.520> a<00:00:46.560> little<00:00:46.800> bit<00:00:47.080> sci-fi<00:00:47.800> on<00:00:47.960> the<00:00:48.680> on<00:00:48.840> the<00:00:48.960> sci-fi<00:00:50.200> side<00:00:50.560> of<00:00:50.760> things<00:00:51.240> in<00:00:51.520> in<00:00:51.680> fintech<00:00:52.080> in<00:00:52.160> LatAm. 00:00:53.840 --> 00:01:00.720 Then,<00:00:54.240> I<00:00:54.400> went<00:00:54.640> on<00:00:54.800> to<00:00:55.120> build<00:00:55.400> with<00:00:55.640> my<00:00:55.880> co-founders<00:00:57.120> PFM,<00:00:57.840> similar<00:00:58.200> to<00:00:58.360> Mint<00:00:59.240> or<00:00:59.560> what<00:00:59.800> you<00:00:59.880> use<00:01:00.000> Oh,<00:01:00.200> yeah,<00:01:00.360> yeah. 00:01:00.720 --> 00:01:07.880 in<00:01:00.880> the<00:01:01.000> USA.<00:01:02.680> So,<00:01:02.880> it<00:01:03.040> was<00:01:03.240> like<00:01:03.440> a<00:01:03.480> single<00:01:03.760> point<00:01:03.960> of<00:01:04.080> access<00:01:04.559> to<00:01:04.760> financial<00:01:05.199> information<00:01:06.000> for<00:01:06.200> micro-entrepreneurs<00:01:07.040> in<00:01:07.120> Latin<00:01:07.360> America. 00:01:07.880 --> 00:01:12.880 It<00:01:08.000> was<00:01:08.160> a<00:01:08.280> lovely<00:01:08.640> idea.<00:01:09.520> It<00:01:09.640> was<00:01:09.760> a<00:01:09.840> very<00:01:10.080> hard<00:01:10.760> business<00:01:11.280> to<00:01:11.680> to<00:01:11.800> monetize. 00:01:12.880 --> 00:01:22.280 Um<00:01:13.960> And<00:01:14.200> so,<00:01:14.880> by<00:01:15.120> having<00:01:15.480> like<00:01:15.720> these<00:01:15.920> two<00:01:16.080> experiences,<00:01:17.840> me<00:01:18.000> and<00:01:18.120> my<00:01:18.200> co-founders,<00:01:18.800> we<00:01:18.960> understood<00:01:19.720> the<00:01:19.840> lack<00:01:20.320> of<00:01:20.560> API<00:01:21.160> infrastructure 00:01:22.280 --> 00:01:28.000 in<00:01:22.400> the<00:01:22.480> region<00:01:23.280> and<00:01:23.520> how<00:01:23.800> this<00:01:24.160> was<00:01:24.440> sort<00:01:24.640> of<00:01:24.760> a<00:01:24.840> bottleneck<00:01:25.520> for<00:01:25.680> fintech<00:01:26.080> disruption,<00:01:26.920> okay? 00:01:28.000 --> 00:01:37.360 Because<00:01:28.400> we<00:01:28.520> knew<00:01:28.800> how<00:01:28.960> to<00:01:29.080> build<00:01:29.520> like<00:01:29.760> this<00:01:30.000> powerful<00:01:30.480> tech,<00:01:31.040> we<00:01:31.160> decided<00:01:31.760> to<00:01:32.040> pivot<00:01:33.320> from<00:01:33.600> that<00:01:34.040> startup<00:01:34.640> to<00:01:35.080> what<00:01:35.360> later<00:01:35.680> became<00:01:36.280> Prometeo. 00:01:37.360 --> 00:01:45.880 And<00:01:37.800> so,<00:01:38.080> basically,<00:01:38.720> what<00:01:38.920> Prometeo<00:01:40.440> is<00:01:40.880> and<00:01:41.160> what<00:01:42.240> how<00:01:42.400> we<00:01:42.680> always<00:01:43.120> thought<00:01:43.400> about<00:01:43.760> it<00:01:44.000> is<00:01:44.040> like<00:01:44.240> a<00:01:44.320> huge<00:01:44.680> highway<00:01:45.240> of<00:01:45.440> financial 00:01:45.880 --> 00:01:55.000 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in<00:02:25.920> Latin<00:02:26.120> America. 00:02:28.080 --> 00:02:35.000 Well,<00:02:29.360> it's<00:02:31.280> Well,<00:02:31.880> it's<00:02:32.040> a<00:02:32.080> very<00:02:32.320> active<00:02:33.080> fintech<00:02:33.440> ecosystem,<00:02:34.040> you<00:02:34.160> know. 00:02:35.000 --> 00:02:43.480 I<00:02:35.160> always<00:02:37.160> I<00:02:37.240> feel<00:02:37.480> sort<00:02:37.720> of<00:02:37.840> a<00:02:37.880> veteran<00:02:39.120> in<00:02:39.280> the<00:02:39.400> fintech<00:02:39.800> space,<00:02:40.440> you<00:02:40.560> know,<00:02:41.920> because<00:02:43.160> like 00:02:43.480 --> 00:02:51.920 having<00:02:43.800> worked<00:02:44.080> for<00:02:44.360> 10<00:02:44.680> years<00:02:45.680> like<00:02:46.320> in<00:02:46.520> this<00:02:46.760> space,<00:02:47.920> I<00:02:47.959> have<00:02:48.120> been<00:02:48.280> able<00:02:48.520> to<00:02:48.680> witness<00:02:49.320> several<00:02:49.760> waves<00:02:50.360> of<00:02:50.680> what<00:02:50.959> 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different<00:04:13.040> ways,<00:04:13.400> you<00:04:13.520> know,<00:04:13.680> many<00:04:14.000> of<00:04:14.120> them<00:04:14.959> providing 00:04:15.440 --> 00:04:24.440 better<00:04:15.720> access<00:04:16.160> to<00:04:16.320> digital<00:04:16.680> payments<00:04:17.160> through<00:04:17.359> credit<00:04:18.079> card<00:04:18.280> networks<00:04:19.000> which<00:04:19.320> could<00:04:19.480> be<00:04:19.600> like<00:04:19.920> e-banks<00:04:20.600> for<00:04:20.760> instance<00:04:21.239> or<00:04:21.400> the<00:04:21.519> local<00:04:22.320> or<00:04:22.600> you<00:04:22.760> have<00:04:23.040> like<00:04:24.200> point 00:04:24.440 --> 00:04:28.553 of<00:04:24.560> sale<00:04:25.000> infrastructure<00:04:25.880> and<00:04:26.040> you<00:04:26.160> have<00:04:26.440> Clip<00:04:26.840> for<00:04:27.040> instance<00:04:27.440> in<00:04:27.560> Mexico. 00:04:28.553 --> 00:04:37.280 [snorts]<00:04:29.960> And<00:04:30.200> then<00:04:31.000> I<00:04:31.160> think<00:04:31.400> 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like<00:05:17.280> a<00:05:17.320> more<00:05:17.640> robust<00:05:18.400> financial<00:05:18.919> sector. 00:05:19.960 --> 00:05:28.720 And<00:05:20.760> and<00:05:20.919> I<00:05:21.000> think<00:05:21.360> that<00:05:22.000> that's<00:05:22.280> where<00:05:22.919> where<00:05:23.120> we<00:05:23.320> are<00:05:23.520> right<00:05:23.720> now,<00:05:24.000> you<00:05:24.120> know,<00:05:24.280> like<00:05:24.800> building<00:05:25.400> the<00:05:25.560> foundations<00:05:26.640> so<00:05:26.840> that<00:05:27.120> financial<00:05:28.080> services 00:05:28.720 --> 00:05:33.240 become<00:05:29.560> more<00:05:29.840> widely<00:05:30.320> adopted<00:05:31.200> and<00:05:31.480> more<00:05:31.640> efficient. 00:05:33.240 --> 00:05:41.720 Give<00:05:33.400> me<00:05:33.520> a<00:05:33.600> sense<00:05:34.000> for<00:05:34.600> how<00:05:35.200> AI<00:05:35.680> is<00:05:35.880> changing<00:05:36.280> all<00:05:36.480> this<00:05:36.760> and<00:05:36.880> I<00:05:36.919> know<00:05:37.200> that<00:05:37.680> Prometeo<00:05:38.320> just<00:05:38.720> recently<00:05:39.240> announced<00:05:39.760> something<00:05:40.120> along<00:05:40.480> this<00:05:40.680> lines<00:05:40.960> with<00:05:41.200> AI<00:05:41.560> and 00:05:41.720 --> 00:05:44.120 agents.<00:05:42.680> How<00:05:42.840> are<00:05:42.960> you<00:05:43.080> thinking<00:05:43.480> about<00:05:43.720> AI? 00:05:44.120 --> 00:05:49.560 How<00:05:44.320> are<00:05:44.440> you<00:05:44.600> integrating<00:05:45.200> it<00:05:45.320> into<00:05:45.480> your<00:05:45.640> product<00:05:46.360> and<00:05:46.720> just<00:05:47.080> oh<00:05:47.240> generally<00:05:47.840> how's<00:05:48.080> it<00:05:48.160> affecting<00:05:48.680> fintech? 00:05:49.560 --> 00:05:58.720 Yeah.<00:05:50.120> Okay,<00:05:50.400> so<00:05:50.680> I<00:05:50.760> think<00:05:51.000> that<00:05:51.920> we<00:05:52.040> are<00:05:52.280> at<00:05:52.440> a<00:05:52.480> point<00:05:53.000> in<00:05:53.400> 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with<00:06:37.400> new<00:06:38.080> products<00:06:38.520> and<00:06:38.680> services<00:06:39.640> using 00:06:40.160 --> 00:06:48.680 AI,<00:06:40.560> you<00:06:40.680> know.<00:06:41.240> And<00:06:41.560> so<00:06:41.680> something<00:06:42.160> that<00:06:42.880> we<00:06:43.800> we've<00:06:44.040> seen<00:06:44.560> over<00:06:45.240> over<00:06:45.840> well<00:06:46.320> these<00:06:46.520> years<00:06:47.320> in<00:06:47.560> the<00:06:47.680> financial<00:06:48.120> space<00:06:48.480> in 00:06:48.680 --> 00:06:57.080 in<00:06:48.800> LatAm<00:06:49.480> is<00:06:49.680> that<00:06:49.919> still<00:06:50.280> financial<00:06:50.720> institutions<00:06:51.640> are<00:06:51.760> struggling<00:06:52.560> with<00:06:53.480> digital<00:06:54.080> transformation,<00:06:55.000> apification,<00:06:55.880> open<00:06:56.120> banking,<00:06:56.800> things 00:06:57.080 --> 00:07:03.400 that<00:06:57.240> perhaps<00:06:57.600> in<00:06:57.720> Europe<00:06:58.200> have<00:06:58.360> been<00:06:58.600> already<00:06:59.200> solved<00:07:00.360> or<00:07:00.560> in<00:07:00.680> Brazil<00:07:01.240> for<00:07:01.480> instance<00:07:01.960> have<00:07:02.200> been<00:07:02.440> already<00:07:02.760> solved. 00:07:03.400 --> 00:07:07.880 In<00:07:03.520> the<00:07:03.680> rest<00:07:04.040> of<00:07:04.240> Latin<00:07:04.520> America<00:07:05.600> they're<00:07:05.760> still<00:07:06.200> like<00:07:06.520> a<00:07:06.640> problem,<00:07:07.240> you<00:07:07.320> know. 00:07:07.880 --> 00:07:16.919 And<00:07:08.280> so<00:07:08.919> we<00:07:09.040> think<00:07:09.240> that<00:07:09.440> at<00:07:09.600> Prometeo<00:07:10.160> because<00:07:10.640> we<00:07:10.880> already<00:07:11.280> have<00:07:11.560> this<00:07:11.720> network,<00:07:12.280> we<00:07:12.440> are<00:07:12.880> uniquely<00:07:13.480> positioned<00:07:14.600> to<00:07:15.040> provide<00:07:15.600> the<00:07:16.040> infrastructure 00:07:16.919 --> 00:07:20.560 for<00:07:17.120> agents.<00:07:17.960> 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00:10:53.880 --> 00:11:00.920 Yeah.<00:10:54.920> Well,<00:10:55.160> I<00:10:55.200> think<00:10:55.440> that<00:10:56.600> um<00:10:57.280> crypto<00:10:57.520> of<00:10:57.640> course<00:10:58.080> is<00:10:58.600> a<00:10:58.839> game<00:10:59.080> changer<00:10:59.880> game<00:11:00.080> changer. 00:11:00.920 --> 00:11:03.760 Uh<00:11:01.040> I<00:11:01.160> think<00:11:01.360> that<00:11:01.520> stable<00:11:01.880> coins<00:11:02.280> are<00:11:02.440> a<00:11:02.560> game<00:11:02.760> changer. 00:11:03.760 --> 00:11:11.160 Um<00:11:04.360> in<00:11:04.560> Latin<00:11:04.839> America<00:11:05.520> in<00:11:05.800> some<00:11:06.000> countries<00:11:06.520> they<00:11:06.640> have<00:11:07.080> they<00:11:07.200> have<00:11:07.320> been<00:11:07.560> particularly<00:11:08.960> uh<00:11:09.040> a-<00:11:09.600> well<00:11:10.120> adopted. 00:11:11.160 --> 00:11:21.000 Um<00:11:11.400> like<00:11:11.760> Argentina,<00:11:13.000> of<00:11:13.080> course<00:11:13.320> 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you. 00:26:35.360 --> 00:26:37.960 What<00:26:35.520> an<00:26:35.600> incredible<00:26:36.320> company<00:26:36.760> you've<00:26:36.920> built. 00:26:37.960 --> 00:26:44.160 Uh,<00:26:38.280> we<00:26:38.400> need<00:26:38.520> to<00:26:38.600> have<00:26:38.720> you<00:26:38.800> back<00:26:39.080> on,<00:26:39.200> 'cause<00:26:39.360> I<00:26:39.400> could<00:26:39.560> talk<00:26:39.760> to<00:26:39.880> you,<00:26:40.600> uh,<00:26:40.680> for<00:26:40.800> another<00:26:41.160> hour<00:26:41.480> about<00:26:41.720> all<00:26:41.840> this<00:26:42.040> stuff,<00:26:42.400> but<00:26:42.600> really,<00:26:42.880> thank<00:26:43.080> you<00:26:43.160> so<00:26:43.320> much. 00:26:44.160 --> 00:26:45.880 No,<00:26:44.400> thanks<00:26:44.680> to<00:26:44.800> you.<00:26:45.040> Thanks<00:26:45.240> for<00:26:45.400> having<00:26:45.720> me. 00:26:45.880 --> 00:26:50.240 I<00:26:45.960> would<00:26:46.160> truly<00:26:46.680> appreciate,<00:26:47.520> uh,<00:26:47.600> our<00:26:47.760> conversation<00:26:48.240> here. ``` ### Dynamix Founder, Chairman & CEO Andrejka Bernatova: Why energy will power the AI revolution URL: https://www.ceo.com/episodes/dynamix-founder-chairman-ceo-andrejka-bernatova-why-energy-will-power-the-ai-revolution/ Last updated: 2026-08-23T17:21:30.000Z # Andrejka Bernatova was always selling a mission The first money Andrejka Bernatova ever raised was $6,000\. She was 14, living in a small village in post-communist Czechoslovakia, and she wanted to go to America. Nobody in her life could pay for it. So she went from one small businessman to another and asked. "Some people gave me $20\. Some gave me $50\. Most people gave me nothing," she told the CEO.com Podcast. Her pitch was thin. She offered to tutor kids in math. She offered to teach them Czech. Mostly, she said the truth: her dream was to go to America, and she needed help getting there. In a country where charitable giving barely existed, where people had spent decades being taught not to dream too big, this was close to unthinkable. Years later she heard Steve Jobs say you don't sell a product, you sell a mission. Nike doesn't sell shoes. At 14, she was already selling a mission. She has raised more than [$35 billion](https://medium.com/authority-magazine/the-new-ceo-playbook-andrejka-bernatova-of-dynamix-corp-9d0ab373b4ee?ref=ceo.com) since. The first $6,000 was, she says, "probably the hardest fundraising experience of my life." The money got her to Manchester, New Hampshire, at 15\. She had imagined New York or Los Angeles. Instead, a host family picked her up and drove, and the highway got smaller and smaller until they turned onto a dirt road and stopped at a house in the woods with no neighbors for miles. "I put my suitcase down and thought: 'These people are probably going to kill me, and nobody will ever know because my parents don't even speak English.'" They did not kill her. They rebuilt her instead. She came from a culture where announcing you wanted to be president got you told to try teaching first. This family told her to change the Constitution if she had to. People who knew her before America and after America say she came back a different person. She wanted to be a diplomat. Politics filled the family table through the fall of communism, and she studied government at Harvard. But nobody was paying her bills, so she chose a toolkit that could: finance and investment banking. That toolkit built a career through the machinery of American energy. She was on the founding management team at [PennTex Midstream Partners](https://dynamixcap.com/?ref=ceo.com), which went public in 2015 and sold a year later to Energy Transfer and Eagle Claw Midstream. She co-founded Core Midstream and served as CFO of Goodnight Midstream and Enchanted Rock. She founded and led ESGEN, a SPAC that [merged with Sunergy Renewables in March 2024](https://www.sec.gov/Archives/edgar/data/1865506/000121390024024166/ea020202901ex99-3%5Fzeoenergy.htm?ref=ceo.com) to become Zeo Energy Corp. Today she is founder, chairman, and CEO of [Dynamix](https://dynamixcap.com/?ref=ceo.com), one platform with two sides: a SPAC franchise that takes companies public, focused on energy infrastructure and digital assets, and a private side that partners with profitable companies ready to scale. Dynamix III [listed on Nasdaq in October 2025](https://www.globenewswire.com/news-release/2025/10/29/3176997/0/en/Dynamix-Corporation-III-Announces-Pricing-of-175-Million-Initial-Public-Offering.html?ref=ceo.com), the team's [third SPAC in four years](https://www.spacinsider.com/news/headline-post/dynamix-ceo-andrejka-bernatova-discusses-the-ether-machine?ref=ceo.com). Her thesis has not changed. She calls it "one energy." Dynamix never split fossil fuels from renewables on ideological lines, because the world will need every viable source it can get. Renewables attract bursts of capital followed by droughts, she says, and real energy transformation requires consistent, high-quality capital over long periods. What has changed is who agrees with her. AI runs on data centers, and data centers run on power, and the technology industry has discovered it cannot build its future without the people who build energy infrastructure. "You're seeing what I call 'San Francisco meets Houston,'" she said. "The tech world suddenly realizes it desperately needs the energy world." She is more excited about energy now than she was during the shale boom, and she does not romanticize the work. "You're talking about projects where if something goes wrong, people literally die. That's a completely different level of responsibility." The same logic pulled Dynamix into digital assets, which she treats as the next generation of infrastructure. Ethereum interests her most because it has utility and programmable function, not just scarcity. "Crypto reminds me of the internet or the iPhone. It's going to fundamentally reshape how people live, even if most people don't fully understand that yet." Dynamix bet big on that view. In July 2025, the firm signed a business combination agreement with The Ether Machine, backed by [more than $1.5 billion in committed financing](https://www.sec.gov/Archives/edgar/data/2028699/000121390025069425/ea0250947-425%5Fdynamix.htm?ref=ceo.com), the largest all-common-stock financing announced since 2021, with a planned launch treasury of more than 400,000 ETH. The deal was still pending when this conversation was recorded. In April 2026 the parties [mutually terminated the agreement](https://www.sec.gov/Archives/edgar/data/2028699/000121390026042469/ea0285701-8k%5Fdynamix.htm?ref=ceo.com). Dynamix received a $50 million payment and has until November 22, 2026 to complete a business combination. Bernatova has now seen two full SPAC cycles, and her reading of the last one is unsparing. Companies that had no business being public were rushed to market. Some sponsors treated the work like a side hobby. "SPACs are like leverage," she said. "Leverage is incredibly powerful when applied correctly. It's disastrous when applied poorly." Her firm's response is almost always to say no. "We tell about 97% of companies we speak with: 'Do not go public.' Because our responsibility is protecting businesses, not destroying them through bad capital structures or premature listings." She turns the same discipline on herself. She uses AI constantly and argues with it constantly, because it hands back the obvious answers, and the work of connecting dots creatively still belongs to people. So she protects time for running, for driving without podcasts, for sitting and thinking. Every CEO.com Podcast conversation ends with the same question. The chances one gives are just as important as the chances one takes. Who gave you a chance? For Bernatova, it was Richard McDonald, headmaster of a boarding school in Switzerland, one of the most expensive in the world. She spent a year writing him letters explaining why he should admit her. Four days before school started, she called him. "You have two choices: I'm either sleeping inside the dorms or outside the dorms, but I'm coming." He went against his own board of governors and let her in. "You have to ask directly for what you want," she said. "Nobody is sitting around thinking about your dreams for you. You have to advocate for yourself. That works. It really works." ```chapters 00:00:00 Introduction and Background 00:00:11 Journey from Czechoslovakia to America 00:01:24 Fundraising for the American Dream 00:02:50 Pitching the Dream to Potential Donors 00:04:43 Inspiration to Move to America 00:06:40 First Impressions of America 00:09:03 Early Career Aspirations 00:10:36 Founding Dynamics and Initial Vision 00:13:30 Impact of AI and Energy on Business 00:17:22 Future of Energy and Digital Assets 00:19:59 A Day in the Life of a CEO 00:22:17 Macroeconomic Perspectives 00:25:19 State of Public Markets and SPACs 00:29:51 Acknowledging Key Supporters 00:32:30 Closing Remarks and Reflections ``` ```vtt WEBVTT 00:00:00.000 --> 00:00:02.360 Andre,<00:00:00.720> thank<00:00:00.920> you<00:00:01.000> so<00:00:01.120> much<00:00:01.320> for<00:00:01.480> coming<00:00:01.800> on<00:00:01.880> the<00:00:02.000> show. 00:00:02.360 --> 00:00:06.960 What<00:00:02.520> an<00:00:02.640> honor<00:00:02.840> to<00:00:02.960> have<00:00:03.280> you.<00:00:03.560> You<00:00:03.760> are<00:00:03.840> the<00:00:04.000> founder,<00:00:04.440> chairman,<00:00:04.880> and<00:00:05.040> CEO<00:00:05.520> of<00:00:05.640> Dynamics. 00:00:06.960 --> 00:00:10.240 And<00:00:07.120> you<00:00:07.200> are<00:00:07.280> the<00:00:07.400> managing<00:00:07.960> partner<00:00:08.440> of<00:00:08.680> Region<00:00:09.080> Capital. 00:00:10.240 --> 00:00:16.360 Uh,<00:00:11.360> tell<00:00:11.560> us<00:00:11.880> how<00:00:12.040> you<00:00:12.160> became<00:00:13.320> the<00:00:13.440> CEO<00:00:13.760> of<00:00:13.840> Dynamics<00:00:14.440> and<00:00:14.800> what<00:00:15.480> what<00:00:15.720> Region<00:00:16.000> Capital? 00:00:16.360 --> 00:00:19.720 Am<00:00:16.480> I<00:00:16.560> saying<00:00:16.760> that<00:00:16.920> or<00:00:16.960> is<00:00:17.080> it<00:00:17.200> Reagan<00:00:17.520> or<00:00:17.640> is<00:00:17.720> it<00:00:17.840> Region?<00:00:18.160> has<00:00:18.240> been<00:00:18.360> now<00:00:18.480> renamed<00:00:18.840> to<00:00:18.920> Dynamics. 00:00:19.720 --> 00:00:22.200 So,<00:00:19.920> we<00:00:20.040> have<00:00:20.240> Oh,<00:00:20.360> okay.<00:00:20.640> So,<00:00:20.760> it's<00:00:20.880> all<00:00:21.040> Dynamics.<00:00:21.480> Never<00:00:21.680> mind. 00:00:22.200 --> 00:00:28.280 Okay.<00:00:22.520> So,<00:00:22.760> Dynamics.<00:00:24.240> Uh,<00:00:24.760> tell<00:00:25.000> us<00:00:25.360> tell<00:00:25.520> us<00:00:25.600> how<00:00:25.720> you<00:00:25.800> got<00:00:26.040> here<00:00:26.200> and<00:00:26.320> what<00:00:26.480> you<00:00:26.560> do. 00:00:28.280 --> 00:00:36.120 Well,<00:00:28.440> it's<00:00:28.520> been<00:00:28.640> a<00:00:28.680> long<00:00:29.040> journey.<00:00:29.680> It's<00:00:29.960> a<00:00:30.360> journey<00:00:30.760> that<00:00:30.960> started<00:00:31.400> in<00:00:31.680> communist<00:00:32.160> Czechoslovakia,<00:00:33.320> you<00:00:33.440> know,<00:00:33.880> quite<00:00:34.160> a<00:00:34.200> few<00:00:34.400> 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00:31:26.920 This<00:31:19.000> you<00:31:19.080> know,<00:31:19.120> it<00:31:19.200> was<00:31:19.320> this<00:31:19.520> incredible<00:31:19.920> opportunity,<00:31:20.520> but<00:31:21.120> you<00:31:21.200> know,<00:31:21.320> he<00:31:21.480> went<00:31:21.720> against<00:31:22.440> uh<00:31:22.920> you<00:31:23.080> know,<00:31:23.480> the<00:31:23.800> sort<00:31:23.960> of<00:31:24.720> governance<00:31:25.440> body<00:31:26.080> of<00:31:26.400> the<00:31:26.520> school<00:31:26.840> at 00:31:26.920 --> 00:31:34.240 that<00:31:27.120> time.<00:31:27.400> And<00:31:27.480> now<00:31:27.760> actually<00:31:28.120> I'm<00:31:28.280> on<00:31:28.800> you<00:31:28.880> know,<00:31:28.960> very<00:31:29.160> involved<00:31:29.480> with<00:31:29.560> the<00:31:29.640> school<00:31:30.000> and<00:31:30.200> and<00:31:30.520> with<00:31:30.800> governance<00:31:31.200> of<00:31:31.320> that<00:31:31.520> school<00:31:31.720> myself,<00:31:32.240> and<00:31:32.960> you<00:31:33.000> 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00:32:12.120 --> 00:32:15.920 Nobody.<00:32:12.520> Not<00:32:12.680> your<00:32:12.840> mom,<00:32:13.160> not<00:32:13.360> your<00:32:13.520> dad,<00:32:13.840> not<00:32:14.040> your<00:32:14.200> grandma,<00:32:14.680> not<00:32:14.920> your<00:32:15.040> siblings. 00:32:15.920 --> 00:32:19.760 No<00:32:16.280> one.<00:32:16.920> You<00:32:17.160> have<00:32:17.360> to<00:32:17.440> take<00:32:17.640> that<00:32:17.800> opportunity<00:32:18.280> in<00:32:18.360> your<00:32:18.640> own<00:32:18.840> hands. 00:32:19.760 --> 00:32:23.440 Go<00:32:20.120> ask<00:32:20.640> Richard<00:32:20.960> McDonald.<00:32:21.480> Go<00:32:21.680> ask<00:32:21.920> that<00:32:22.040> headmaster. 00:32:23.440 --> 00:32:27.640 Tell<00:32:23.600> him<00:32:23.760> what<00:32:23.920> you<00:32:24.040> exactly<00:32:24.560> want<00:32:24.680> to<00:32:24.760> do,<00:32:25.760> and<00:32:26.520> just<00:32:26.720> do<00:32:26.840> it. 00:32:27.640 --> 00:32:31.800 And<00:32:27.760> it<00:32:27.840> just<00:32:28.000> works.<00:32:28.480> It<00:32:28.600> really<00:32:28.800> works.<00:32:30.600> Andreja,<00:32:31.040> you're<00:32:31.200> incredible. 00:32:31.800 --> 00:32:34.960 We<00:32:31.880> need<00:32:32.000> to<00:32:32.080> have<00:32:32.200> you<00:32:32.280> back<00:32:32.520> on.<00:32:32.880> My<00:32:33.040> word,<00:32:33.320> I<00:32:33.360> could<00:32:33.480> talk<00:32:33.640> to<00:32:33.720> you<00:32:33.760> for<00:32:33.960> hours. 00:32:34.960 --> 00:32:37.160 Uh<00:32:35.440> congratulations<00:32:36.200> everything<00:32:36.520> you've<00:32:36.680> done. 00:32:37.160 --> 00:32:39.880 What<00:32:37.280> an<00:32:37.440> incredible<00:32:37.840> career<00:32:38.280> and<00:32:38.400> life<00:32:38.680> you've<00:32:38.880> lived. 00:32:39.880 --> 00:32:42.600 Uh<00:32:40.160> Thank<00:32:40.440> you.<00:32:40.720> Seriously,<00:32:41.080> what<00:32:41.240> an<00:32:41.360> honor.<00:32:42.120> Thank<00:32:42.280> you<00:32:42.360> Glenn. 00:32:42.600 --> 00:32:51.120 Thank<00:32:42.840> you<00:32:42.920> for<00:32:43.080> having<00:32:43.400> me<00:32:43.640> and<00:32:44.480> you<00:32:44.560> know,<00:32:44.680> I<00:32:44.760> hope<00:32:45.040> that<00:32:46.240> this<00:32:46.400> discussion<00:32:46.880> could<00:32:47.000> be<00:32:47.120> inspiration<00:32:47.680> for<00:32:47.880> somebody<00:32:48.440> and<00:32:49.920> really<00:32:50.120> great<00:32:50.920> really 00:32:51.120 --> 00:32:54.000 great<00:32:51.320> to<00:32:51.360> be<00:32:51.480> here.<00:32:51.800> Thank<00:32:52.000> you. ``` ### Merge Co-Founder & CEO Shensi Ding-Lopez: Why AI agents need secure integrations URL: https://www.ceo.com/episodes/merge-co-founder-ceo-shensi-ding-lopez-why-ai-agents-need-secure-integrations/ Last updated: 2026-08-23T17:32:42.000Z # Shensi Ding-Lopez still codes at night Shensi Ding-Lopez sits in meetings until six or seven most nights. Then she opens the codebase. By her own accounting, she is the non-technical co-founder of Merge. She never worked as a software engineer outside of internships. After Columbia, she went into banking, then growth equity, then startup operations. When she and Gil Feig started Merge in 2020, Feig put in years helping her become a real engineer. It paid off in an unglamorous way: when the company built its second product, she, Feig, and one other engineer wrote the entire thing themselves. "There's just no substitute for actually doing the work yourself," she said on the CEO.com Podcast. Merge sells a unified API that lets B2B software companies connect their products to hundreds of third-party systems: HR platforms, applicant tracking, accounting, file storage, ticketing. About 120 employees across San Francisco, New York City, and Berlin. More than 400 enterprise customers and around 20,000 self-serve organizations. The company has raised roughly [$74.5 million](https://www.merge.dev/blog/announcing-merges-55-million-series-b?ref=ceo.com), most of it in a $55 million Series B led by Accel. Ding-Lopez and Feig met as 18-year-old freshmen at Columbia, in a computer science department small enough that everyone knew everyone. When she later moved to San Francisco, he helped her find her first apartment, then her first car. They compared notes on their jobs and kept hearing the same complaint in stereo. At Expanse, where she was chief of staff, integrations came up in executive syncs and sales meetings until the company [hired a full team of engineers](https://www.merge.dev/blog/why-we-started-merge?ref=ceo.com) just to build them. At Jumpstart, where Feig ran engineering, customers kept asking for applicant tracking integrations he didn't have. They quit and built the fix. "The company was built on a foundation of trust because we'd known each other for so long," she told the CEO.com Podcast. "And honestly, it's just really fun building a company with one of your best friends." The early product was rough. Customers used it anyway. They filed feedback, worked through bugs, stayed engaged. Ding-Lopez considers that the real test. "If someone immediately gives up on your product, they probably didn't need it that badly." The second product is [Agent Handler](https://www.merge.dev/blog/agent-handler?ref=ceo.com), which she describes as the company's second act. It exists because AI agents broke the old assumptions about integrations. Software workflows used to be deterministic. A user pressed a button, and data synced on a schedule. An agent decides for itself. It might pull support tickets, create a Salesforce opportunity, or take some action nobody scripted, and with the Model Context Protocol spreading, the range of possible actions keeps growing. "The risk profile for AI agents increases exponentially once they start interacting with third-party systems," she said. Credentials, permissions, personally identifiable information. [Agent Handler](https://www.merge.dev/merge-agent-handler?ref=ceo.com) sits in the middle and manages the credentials, monitoring, and governance that most early agent startups skipped. On culture, her view is blunt: you cannot change it after the hire. "Culture starts during the hiring process." Merge has passed on clearly talented candidates it judged too selfish or too political for the team, and it tells recruits up front that the company is in-person and high-commitment. When people leave, the culture is usually what they say they will miss. Asked what she reads, she confessed to murder mysteries and history audiobooks, then spent a minute evangelizing Libby, the app that connects to public libraries. "It's the best app ever," she said. "There can be waitlists for popular books, but who cares? It's free." This is a CEO whose company is backed by Accel, NEA, and Addition. Every CEO.com Podcast conversation ends the same way, on the belief that the chances one gives are just as important as the chances one takes. For Ding-Lopez, the chance was an associate role at Silver Lake's growth equity fund, one of two in her class. It brought her to San Francisco, put her around founders, and put her in the orbit of Adam Grosser, who [launched and led the fund](https://www.silverlake.com/silver-lake-to-launch-new-investment-strategy-focused-on-innovation-in-the-energy-and-resource-sectors/?ref=ceo.com) after years at Apple, and from whom she says she learned a tremendous amount. "That experience completely changed the trajectory of my life," she said. "Without it, I probably would've stayed in New York working in private equity somewhere and potentially hating my life." ```chapters 00:00:00 Introduction and Background 00:00:22 Founding Merge 00:00:54 Launching the Second Product 00:02:05 AI Agents and Security 00:03:36 Fundraising Journey 00:04:36 Early Customer Validation 00:05:10 Co-Founder's Background 00:06:00 A Day in the Life of a CEO 00:07:16 Technical Contributions 00:08:22 Future of AI 00:09:01 Economic Environment and Optimism 00:10:01 Company Culture and Hiring 00:11:56 Reading Habits and Recommendations 00:13:32 The Importance of Giving Chances 00:14:51 Closing Remarks ``` ```vtt WEBVTT 00:00:00.000 --> 00:00:01.920 Shazi,<00:00:00.480> thank<00:00:00.680> you<00:00:00.720> so<00:00:00.800> much<00:00:01.000> for<00:00:01.080> coming<00:00:01.360> on<00:00:01.440> the<00:00:01.520> show. 00:00:01.920 --> 00:00:10.560 What<00:00:02.080> an<00:00:02.200> honor<00:00:02.360> to<00:00:02.480> have<00:00:02.760> you.<00:00:02.880> You're<00:00:02.960> the<00:00:03.080> co-founder<00:00:03.640> and<00:00:03.760> CEO<00:00:04.400> of<00:00:04.600> Merge,<00:00:05.800> which<00:00:05.960> is<00:00:06.080> a<00:00:06.160> technology<00:00:06.800> company<00:00:07.120> that<00:00:07.280> provides<00:00:07.680> a<00:00:07.760> unified<00:00:08.440> API<00:00:08.960> to<00:00:09.080> help<00:00:09.440> B2B<00:00:10.000> software 00:00:10.560 --> 00:00:18.160 products<00:00:11.680> across<00:00:12.080> multiple<00:00:12.440> systems<00:00:12.880> including<00:00:13.400> HRIS,<00:00:14.360> ATS,<00:00:15.040> accounting,<00:00:15.600> file<00:00:15.880> storage,<00:00:16.400> ticketing,<00:00:16.960> and<00:00:17.120> more. 00:00:18.160 --> 00:00:22.720 Welcome<00:00:18.520> to<00:00:18.600> the<00:00:18.720> show.<00:00:19.200> Give<00:00:19.400> us<00:00:19.520> a<00:00:19.560> sense<00:00:19.800> for<00:00:19.920> how<00:00:20.040> you<00:00:20.120> became<00:00:20.400> the<00:00:20.480> co-founder<00:00:21.000> and<00:00:21.120> CEO<00:00:21.480> of<00:00:21.600> Merge. 00:00:22.720 --> 00:00:25.600 Thank<00:00:23.040> you<00:00:23.120> so<00:00:23.200> much<00:00:23.320> for<00:00:23.440> having<00:00:23.760> me.<00:00:23.920> I'm<00:00:24.040> really<00:00:24.200> excited<00:00:24.560> to<00:00:24.640> be<00:00:24.800> here. 00:00:25.600 --> 00:00:30.440 So,<00:00:26.080> I<00:00:26.200> became<00:00:26.720> the<00:00:26.840> CEO<00:00:27.240> and<00:00:27.320> co-founder<00:00:27.800> of<00:00:27.920> Merge<00:00:28.240> from<00:00:28.360> starting<00:00:28.640> the<00:00:28.720> company<00:00:29.040> around<00:00:29.240> 5<00:00:29.440> years<00:00:29.600> ago. 00:00:30.440 --> 00:00:33.200 I<00:00:30.520> started<00:00:30.800> the<00:00:30.880> company<00:00:31.160> with<00:00:31.280> one<00:00:31.400> of<00:00:31.440> my<00:00:31.520> best<00:00:31.760> friends<00:00:32.160> from<00:00:32.320> college. 00:00:33.200 --> 00:00:39.000 We<00:00:33.360> were<00:00:33.440> both<00:00:33.760> living<00:00:34.000> in<00:00:34.080> San<00:00:34.200> Francisco<00:00:34.720> working<00:00:35.040> at<00:00:35.120> startups<00:00:35.520> who<00:00:35.560> were<00:00:35.680> running<00:00:36.000> into<00:00:36.400> the<00:00:36.520> same<00:00:36.760> problem<00:00:37.160> of<00:00:37.320> needing<00:00:37.560> a<00:00:37.600> lot<00:00:37.760> of<00:00:37.840> integrations. 00:00:39.000 --> 00:00:43.320 And<00:00:39.600> we<00:00:39.680> were<00:00:39.800> just<00:00:39.960> very<00:00:40.560> lucky<00:00:40.880> to<00:00:40.960> be<00:00:41.080> super<00:00:41.480> super<00:00:41.760> interested<00:00:42.080> in<00:00:42.160> the<00:00:42.240> space. 00:00:43.320 --> 00:00:47.920 And<00:00:43.520> so<00:00:43.640> now<00:00:43.880> fast<00:00:44.160> forward<00:00:44.360> we<00:00:44.440> have<00:00:44.520> around<00:00:44.760> 120<00:00:45.160> employees<00:00:45.680> San<00:00:45.800> Francisco,<00:00:46.360> New<00:00:46.440> York<00:00:46.600> City,<00:00:46.800> and<00:00:46.920> Berlin. 00:00:47.920 --> 00:00:52.160 Over<00:00:48.120> 400<00:00:48.560> enterprise<00:00:48.920> customers<00:00:49.360> and<00:00:49.440> around<00:00:49.640> 20,000<00:00:50.320> software<00:00:50.680> organizations<00:00:51.320> using<00:00:51.560> our<00:00:51.680> product. 00:00:52.160 --> 00:00:55.200 And<00:00:52.320> we<00:00:52.480> just<00:00:52.720> launched<00:00:53.000> our<00:00:53.200> second<00:00:53.560> product<00:00:54.040> last<00:00:54.320> week. 00:00:55.200 --> 00:00:58.560 Tell<00:00:55.480> us<00:00:55.560> about<00:00:55.760> the<00:00:55.840> second<00:00:56.120> product.<00:00:57.280> That's<00:00:57.560> a<00:00:57.600> big<00:00:57.800> deal. 00:00:58.560 --> 00:01:04.480 Yeah,<00:00:58.960> I'm<00:00:59.120> really<00:00:59.360> excited.<00:01:00.200> I've<00:01:00.360> read<00:01:00.520> a<00:01:00.600> lot<00:01:00.800> about<00:01:01.200> companies<00:01:01.600> doing<00:01:01.840> 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provide<00:01:59.840> a<00:01:59.920> second<00:02:00.240> part<00:02:00.440> we<00:02:00.560> put<00:02:00.720> the<00:02:01.040> Oh<00:02:01.120> god,<00:02:01.360> sorry. 00:02:01.560 --> 00:02:05.160 We<00:02:01.640> provide<00:02:02.040> another<00:02:02.400> layer<00:02:02.960> while<00:02:03.120> we<00:02:03.160> make<00:02:03.400> it<00:02:03.479> easy<00:02:03.720> for<00:02:03.840> companies<00:02:04.200> to<00:02:04.280> manage<00:02:04.560> that. 00:02:05.160 --> 00:02:08.000 So<00:02:05.440> when<00:02:05.600> you<00:02:05.720> say<00:02:05.840> agents<00:02:06.160> are<00:02:06.240> you<00:02:06.280> talking<00:02:06.440> about<00:02:06.560> like<00:02:06.720> AI<00:02:07.040> agents? 00:02:08.000 --> 00:02:13.959 Yes,<00:02:08.320> AI<00:02:08.520> agents.<00:02:09.440> Yeah,<00:02:09.520> give<00:02:09.800> give<00:02:10.000> it<00:02:10.119> give<00:02:10.240> me<00:02:10.360> a<00:02:10.440> sense<00:02:10.759> for<00:02:10.880> how<00:02:11.120> you're<00:02:11.320> 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about<00:02:42.959> or<00:02:43.080> focused<00:02:43.560> on. 00:02:44.160 --> 00:02:52.040 So<00:02:44.480> how<00:02:44.680> are<00:02:44.800> you<00:02:45.000> thinking<00:02:45.360> about<00:02:45.640> it?<00:02:46.600> So<00:02:46.800> I<00:02:46.840> think<00:02:47.080> the<00:02:47.200> risk<00:02:47.480> for<00:02:47.720> agents<00:02:48.080> increases<00:02:48.640> pretty<00:02:48.840> exponentially<00:02:49.520> when<00:02:49.640> it<00:02:49.760> comes<00:02:50.080> to<00:02:50.280> their<00:02:50.480> interactions<00:02:51.120> with<00:02:51.560> third-party 00:02:52.040 --> 00:02:54.480 tools.<00:02:52.480> So<00:02:52.880> the<00:02:53.000> integrations<00:02:53.560> around<00:02:53.760> the<00:02:53.880> agents. 00:02:54.480 --> 00:03:01.480 I<00:02:54.600> think<00:02:54.840> if<00:02:55.000> the<00:02:55.200> agents<00:02:55.480> are<00:02:55.600> very<00:02:55.840> siloed,<00:02:56.400> they're<00:02:56.560> not<00:02:56.720> really<00:02:57.360> 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product<00:03:12.640> helps<00:03:12.880> you<00:03:13.040> connect<00:03:13.360> your<00:03:13.440> agents<00:03:13.720> to<00:03:13.800> those<00:03:14.000> third-party<00:03:14.440> tools 00:03:14.800 --> 00:03:17.480 and<00:03:14.920> that's<00:03:15.160> where<00:03:15.360> you<00:03:15.480> really<00:03:15.680> need<00:03:15.840> to<00:03:15.920> start<00:03:16.120> having<00:03:16.360> a<00:03:16.440> lot<00:03:16.560> of<00:03:16.680> monitoring. 00:03:17.480 --> 00:03:21.440 You<00:03:17.560> also<00:03:17.760> need<00:03:17.880> to<00:03:17.959> start<00:03:18.160> looking<00:03:18.480> for<00:03:18.680> any<00:03:18.880> potential<00:03:19.600> PII<00:03:20.080> that's<00:03:20.200> getting<00:03:20.440> passed<00:03:20.720> along. 00:03:21.440 --> 00:03:27.720 Um<00:03:21.600> you<00:03:21.680> also<00:03:21.880> need<00:03:22.040> to<00:03:22.120> be<00:03:22.480> configuring<00:03:23.040> rules<00:03:23.400> around<00:03:23.760> credential<00:03:24.200> management<00:03:24.760> and<00:03:24.920> how<00:03:25.080> those<00:03:25.239> credentials<00:03:25.640> are<00:03:25.760> shared<00:03:26.040> across<00:03:26.360> an<00:03:26.440> organization<00:03:26.959> as<00:03:27.120> well. 00:03:27.720 --> 00:03:33.600 So<00:03:27.800> that's<00:03:27.959> what<00:03:28.080> we're<00:03:28.239> really<00:03:28.480> thinking<00:03:28.800> about.<00:03:29.080> We<00:03:29.160> are<00:03:29.360> seeing<00:03:29.720> this<00:03:29.880> becoming<00:03:30.239> increasingly<00:03:30.840> more<00:03:31.040> an<00:03:31.160> issue<00:03:31.840> um<00:03:31.920> especially<00:03:32.320> since<00:03:32.560> agents<00:03:32.959> are<00:03:33.120> going<00:03:33.280> to<00:03:33.360> become 00:03:33.600 --> 00:03:36.800 more<00:03:33.720> popular<00:03:34.120> and<00:03:34.200> they<00:03:34.280> will<00:03:34.440> be<00:03:34.560> the<00:03:34.680> de<00:03:34.800> facto<00:03:35.080> way<00:03:35.200> of<00:03:35.320> working. 00:03:36.800 --> 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which<00:05:15.640> at<00:05:15.760> the<00:05:15.880> time<00:05:16.080> was<00:05:16.200> pretty<00:05:16.400> small. 00:05:16.760 --> 00:05:22.760 So,<00:05:16.880> everyone<00:05:17.200> knew<00:05:17.440> each<00:05:17.600> other.<00:05:18.440> Uh<00:05:18.560> so,<00:05:18.720> we<00:05:18.840> were<00:05:18.919> in<00:05:18.960> a<00:05:19.000> lot<00:05:19.120> of<00:05:19.200> the<00:05:19.280> same<00:05:19.480> classes,<00:05:19.919> group<00:05:20.120> projects,<00:05:20.520> and<00:05:20.600> we<00:05:20.720> also<00:05:20.960> were<00:05:21.120> on<00:05:21.240> Engineering<00:05:21.720> Student<00:05:22.000> Council<00:05:22.360> together. 00:05:22.760 --> 00:05:29.360 So,<00:05:23.240> we<00:05:23.320> had<00:05:23.440> really<00:05:23.680> gotten<00:05:23.919> to<00:05:24.000> know<00:05:24.160> each<00:05:24.320> other<00:05:24.520> socially<00:05:24.960> and<00:05:25.040> then<00:05:25.160> also<00:05:25.520> in<00:05:25.600> like<00:05:25.840> a<00:05:26.880> kind<00:05:27.000> of<00:05:27.080> like<00:05:27.520> team<00:05:27.840> project<00:05:28.440> form. 00:05:29.360 --> 00:05:32.120 Um<00:05:29.560> and<00:05:29.680> when<00:05:29.800> I<00:05:29.840> moved<00:05:30.000> to<00:05:30.080> San<00:05:30.200> Francisco,<00:05:30.640> he<00:05:30.840> had<00:05:30.919> already<00:05:31.120> been<00:05:31.240> living<00:05:31.480> there. 00:05:32.120 --> 00:05:34.720 Uh<00:05:32.240> so,<00:05:32.360> he<00:05:32.480> helped<00:05:32.640> me<00:05:32.720> find<00:05:32.919> my<00:05:33.040> first<00:05:33.360> car,<00:05:33.720> my<00:05:33.840> first<00:05:34.040> apartment. 00:05:34.720 --> 00:05:41.520 And<00:05:34.800> we<00:05:34.880> just<00:05:35.040> kept<00:05:35.200> in<00:05:35.280> touch<00:05:35.480> throughout<00:05:35.680> the<00:05:35.760> years.<00:05:36.480> And<00:05:36.880> we<00:05:37.080> would<00:05:37.200> get<00:05:37.320> dinner,<00:05:37.680> talk<00:05:37.919> a<00:05:37.960> lot<00:05:38.080> about<00:05:38.320> work,<00:05:38.680> and<00:05:39.520> um<00:05:39.720> yeah,<00:05:39.880> naturally<00:05:40.360> this<00:05:40.520> problem<00:05:40.880> of<00:05:41.000> integrations 00:05:41.520 --> 00:05:45.600 was<00:05:41.640> both<00:05:42.000> coming<00:05:42.280> up<00:05:42.440> at<00:05:42.600> both<00:05:42.800> of<00:05:42.880> our<00:05:42.960> companies,<00:05:43.520> and<00:05:43.880> we<00:05:44.000> realized<00:05:44.440> we<00:05:44.600> there<00:05:44.760> might<00:05:44.880> be<00:05:45.000> something<00:05:45.320> there. 00:05:45.600 --> 00:05:51.320 But<00:05:45.919> we'd<00:05:46.080> always<00:05:46.280> known<00:05:46.440> each<00:05:46.560> other<00:05:46.720> for<00:05:46.880> a<00:05:46.919> really<00:05:47.160> long<00:05:47.480> time,<00:05:47.760> and<00:05:47.840> I<00:05:47.880> think<00:05:48.040> that<00:05:48.160> was<00:05:48.280> really<00:05:48.480> lucky<00:05:48.960> so<00:05:49.160> that<00:05:49.280> our<00:05:49.360> company<00:05:49.640> was<00:05:49.800> built<00:05:50.040> on<00:05:50.120> a<00:05:50.200> foundation<00:05:50.600> of<00:05:50.720> trust. 00:05:51.320 --> 00:05:54.680 And<00:05:51.440> it's<00:05:51.520> just<00:05:51.720> really<00:05:51.960> fun<00:05:52.200> working<00:05:52.520> with<00:05:52.680> someone<00:05:52.960> who<00:05:53.120> is<00:05:53.240> one<00:05:53.360> of<00:05:53.440> your<00:05:53.560> best<00:05:53.760> friends. 00:05:54.680 --> 00:06:00.680 Yeah,<00:05:55.000> that's<00:05:55.280> awesome.<00:05:56.160> Tell<00:05:56.320> me,<00:05:57.200> uh<00:05:57.280> what<00:05:57.440> does<00:05:57.560> a<00:05:57.600> typical<00:05:58.000> day<00:05:58.200> look<00:05:58.400> like<00:05:58.600> for<00:05:58.760> you? 00:06:00.680 --> 00:06:04.760 It's<00:06:00.920> chaos.<00:06:02.000> Uh<00:06:02.080> so,<00:06:02.219> [laughter]<00:06:02.480> I<00:06:02.600> wake<00:06:02.960> up,<00:06:03.480> I<00:06:03.560> go<00:06:03.680> to<00:06:03.760> the<00:06:03.880> gym<00:06:04.200> every<00:06:04.440> day. 00:06:04.760 --> 00:06:09.080 I<00:06:04.840> think<00:06:05.000> that's<00:06:05.200> really<00:06:05.400> important<00:06:05.800> for<00:06:05.960> me<00:06:06.120> to<00:06:06.280> just<00:06:06.440> be<00:06:06.520> able<00:06:06.640> to<00:06:06.720> like<00:06:06.840> reset<00:06:07.280> and<00:06:07.360> like<00:06:07.560> set<00:06:07.760> some<00:06:07.880> time<00:06:08.080> for<00:06:08.200> myself. 00:06:09.080 --> 00:06:15.280 Um<00:06:09.280> and<00:06:09.400> then<00:06:09.520> after<00:06:10.080> go<00:06:10.200> to<00:06:10.320> work,<00:06:10.840> immediately<00:06:11.240> try<00:06:11.440> to<00:06:11.520> respond<00:06:11.800> to<00:06:11.920> all<00:06:12.160> emails,<00:06:12.560> addressing<00:06:12.920> all<00:06:13.080> slacks,<00:06:13.440> and<00:06:13.560> also<00:06:13.760> catching<00:06:14.080> up<00:06:14.200> on<00:06:14.320> reading<00:06:14.800> from<00:06:15.000> the<00:06:15.080> night 00:06:15.280 --> 00:06:18.160 before<00:06:15.680> that<00:06:15.840> I<00:06:15.920> might<00:06:16.080> not<00:06:16.200> have<00:06:16.320> had<00:06:16.480> the<00:06:16.560> head<00:06:16.720> space<00:06:17.040> to<00:06:17.440> to<00:06:17.560> do. 00:06:18.160 --> 00:06:23.880 Um<00:06:18.320> I<00:06:18.360> also<00:06:18.600> try<00:06:18.720> to<00:06:18.880> allocate<00:06:19.280> time<00:06:19.480> in<00:06:19.520> the<00:06:19.600> mornings<00:06:20.000> for<00:06:20.120> like<00:06:20.400> reading<00:06:20.800> and<00:06:20.919> just<00:06:21.120> like<00:06:21.240> catching<00:06:21.520> up<00:06:21.640> on<00:06:21.720> the<00:06:21.800> industry,<00:06:22.480> really<00:06:22.720> just<00:06:22.840> making<00:06:23.080> sure<00:06:23.240> that<00:06:23.400> I<00:06:23.520> feel 00:06:23.880 --> 00:06:27.080 like<00:06:24.200> I'm<00:06:24.840> caught<00:06:25.080> up<00:06:25.280> in<00:06:25.400> the<00:06:25.480> things<00:06:25.640> that<00:06:25.760> I<00:06:25.840> need<00:06:25.960> to<00:06:26.040> 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a<00:07:04.200> lot<00:07:04.720> of<00:07:05.000> deep<00:07:06.000> uh<00:07:06.080> experience<00:07:07.160> and,<00:07:07.800> you<00:07:07.880> know,<00:07:08.080> intelligence<00:07:08.680> behind<00:07:09.640> the<00:07:09.760> product<00:07:10.480> itself. 00:07:11.040 --> 00:07:15.200 So,<00:07:11.160> are<00:07:11.320> you<00:07:11.440> getting<00:07:11.680> in<00:07:11.800> there<00:07:12.000> and<00:07:12.080> actually<00:07:12.360> like<00:07:12.560> pushing<00:07:13.880> uh<00:07:13.960> push<00:07:14.240> in<00:07:14.480> all<00:07:14.600> that<00:07:14.760> type<00:07:14.919> of<00:07:15.040> stuff? 00:07:15.200 --> 00:07:17.480 That's<00:07:15.400> That's<00:07:15.600> amazing.<00:07:16.440> Yeah,<00:07:16.840> I<00:07:17.000> am. 00:07:17.480 --> 00:07:20.000 Um<00:07:17.640> so,<00:07:17.760> technically,<00:07:18.200> I'm<00:07:18.280> actually<00:07:18.560> the<00:07:18.680> non-technical<00:07:19.320> co-founder. 00:07:20.000 --> 00:07:24.520 So,<00:07:20.200> I<00:07:20.280> never<00:07:20.600> worked<00:07:20.919> as<00:07:21.040> a<00:07:21.080> software<00:07:21.440> engineer<00:07:21.760> in<00:07:21.840> a<00:07:21.880> professional<00:07:22.360> environment<00:07:22.840> other<00:07:23.000> than<00:07:23.240> a<00:07:23.320> few<00:07:23.520> internships. 00:07:24.520 --> 00:07:29.919 I<00:07:24.720> actually<00:07:24.960> went<00:07:25.120> into<00:07:25.360> banking<00:07:25.720> right<00:07:25.880> after<00:07:26.080> college<00:07:26.480> and<00:07:26.560> then<00:07:27.040> um<00:07:27.240> growth<00:07:27.480> equity<00:07:27.919> before<00:07:28.240> moving<00:07:28.480> into<00:07:28.600> like<00:07:28.760> a<00:07:28.800> finance<00:07:29.160> and<00:07:29.240> operating<00:07:29.680> role. 00:07:29.919 --> 00:07:33.440 So,<00:07:30.400> never<00:07:30.919> got<00:07:31.240> to<00:07:31.400> code<00:07:31.800> in<00:07:31.919> like<00:07:32.200> a<00:07:32.600> professional<00:07:33.080> setting. 00:07:33.440 --> 00:07:39.480 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work,<00:07:54.760> but<00:07:54.880> it<00:07:55.120> really<00:07:55.360> helped<00:07:55.640> me<00:07:55.840> understand<00:07:56.400> what<00:07:56.560> we<00:07:56.640> were<00:07:56.760> building<00:07:57.160> and<00:07:57.280> also<00:07:57.520> get<00:07:57.680> opinions<00:07:58.120> around<00:07:58.480> it<00:07:58.800> and<00:07:58.880> make<00:07:59.000> it<00:07:59.080> a<00:07:59.120> little<00:07:59.280> bit<00:07:59.440> easier 00:07:59.720 --> 00:08:04.040 for<00:07:59.840> me<00:07:59.960> to<00:08:00.080> contribute<00:08:00.520> to<00:08:00.640> answering<00:08:00.960> questions<00:08:01.440> as<00:08:01.600> we<00:08:01.680> started<00:08:01.960> onboarding<00:08:02.360> more<00:08:02.520> engineers<00:08:02.880> to<00:08:02.960> the<00:08:03.080> team. 00:08:04.040 --> 00:08:10.920 Um<00:08:04.480> I<00:08:04.560> think<00:08:04.760> it's<00:08:04.880> a<00:08:04.920> really<00:08:05.160> helpful<00:08:05.440> part<00:08:05.680> of<00:08:05.720> 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all<00:08:20.280> this<00:08:20.480> look<00:08:20.640> like<00:08:20.840> 5-10<00:08:21.280> years<00:08:21.520> from<00:08:21.640> now? 00:08:22.680 --> 00:08:24.600 I<00:08:22.960> think<00:08:23.240> there's<00:08:23.480> still<00:08:23.720> way<00:08:23.919> more<00:08:24.080> to<00:08:24.200> go. 00:08:24.600 --> 00:08:30.120 I<00:08:24.720> think<00:08:24.880> we've<00:08:25.040> probably<00:08:25.360> just<00:08:25.520> started<00:08:25.800> in<00:08:25.880> the<00:08:25.960> beginning.<00:08:26.400> I<00:08:26.480> know<00:08:26.680> it<00:08:26.760> feels<00:08:27.040> like<00:08:27.240> we're<00:08:27.400> all<00:08:27.600> talking<00:08:27.919> about<00:08:28.120> AI,<00:08:28.520> there's<00:08:28.720> blah<00:08:28.919> blah<00:08:29.040> blah<00:08:29.200> blah,<00:08:29.520> but<00:08:29.840> I<00:08:29.919> just 00:08:30.120 --> 00:08:32.479 think<00:08:30.280> there's<00:08:30.480> way<00:08:30.680> more<00:08:30.919> impact<00:08:31.320> that<00:08:31.440> AI<00:08:31.640> can<00:08:31.800> have. 00:08:32.479 --> 00:08:38.800 Um<00:08:32.640> people<00:08:32.840> are<00:08:32.919> still<00:08:33.120> nervous<00:08:33.360> about<00:08:33.520> using<00:08:33.800> AI<00:08:34.000> in<00:08:34.080> their<00:08:34.159> day-to-day<00:08:34.599> work<00:08:34.880> and<00:08:35.000> some<00:08:35.120> companies<00:08:35.479> are<00:08:35.560> still<00:08:35.760> banning<00:08:36.200> AI<00:08:36.560> in<00:08:36.760> their<00:08:37.560> um<00:08:37.800> in<00:08:37.919> their<00:08:38.159> laptops<00:08:38.719> and 00:08:38.800 --> 00:08:46.200 their<00:08:38.960> software.<00:08:39.680> And<00:08:39.840> so<00:08:40.080> I<00:08:40.320> I<00:08:40.440> think<00:08:40.640> there's<00:08:40.880> just<00:08:41.080> way<00:08:41.280> more<00:08:41.919> room<00:08:42.240> and<00:08:42.320> we're<00:08:42.440> not<00:08:42.680> even<00:08:42.880> really<00:08:43.159> fully<00:08:44.440> utilizing<00:08:45.080> it<00:08:45.160> to<00:08:45.240> its<00:08:45.360> full<00:08:45.560> extent. 00:08:46.200 --> 00:08:52.680 I<00:08:46.280> also<00:08:46.520> think<00:08:46.680> there<00:08:46.800> are<00:08:46.880> a<00:08:46.920> few<00:08:47.120> barriers<00:08:47.600> to<00:08:47.920> utilizing<00:08:48.440> AI<00:08:48.680> fully<00:08:49.040> and<00:08:49.240> part<00:08:49.440> of<00:08:49.520> that<00:08:49.720> is<00:08:49.839> integrations,<00:08:50.400> which<00:08:50.560> is<00:08:50.680> why<00:08:50.880> I'm<00:08:51.000> so<00:08:51.160> excited<00:08:51.640> about<00:08:52.160> what<00:08:52.280> our<00:08:52.400> product 00:08:52.680 --> 00:09:01.080 really<00:08:52.880> offers<00:08:53.200> and<00:08:53.280> how<00:08:53.400> we<00:08:53.480> can<00:08:53.600> help<00:08:54.200> um<00:08:54.240> help<00:08:54.520> unlock<00:08:55.000> a<00:08:55.040> lot<00:08:55.160> of<00:08:55.240> these<00:08:55.400> cases<00:08:55.720> that<00:08:55.839> are<00:08:56.880> are<00:08:57.200> available,<00:08:57.839> but<00:08:58.000> require<00:08:58.400> a<00:08:58.440> lot<00:08:58.640> of<00:08:58.960> a<00:08:59.000> lot<00:08:59.160> of<00:08:59.240> additional<00:08:59.640> work<00:08:59.880> too. 00:09:01.080 --> 00:09:03.080 How<00:09:01.240> do<00:09:01.320> you<00:09:01.440> feel<00:09:01.560> about<00:09:01.800> like<00:09:01.960> the<00:09:02.080> economic<00:09:02.640> environment? 00:09:03.080 --> 00:09:09.400 Obviously<00:09:03.440> it's<00:09:03.760> been<00:09:03.920> a<00:09:03.960> little<00:09:04.680> um<00:09:06.080> chaotic<00:09:06.920> at<00:09:07.000> least<00:09:07.320> for<00:09:07.440> the<00:09:07.520> first<00:09:07.760> half<00:09:07.920> of<00:09:08.000> the<00:09:08.080> year<00:09:08.360> with<00:09:08.480> like<00:09:08.640> the<00:09:08.720> tariffs<00:09:09.080> and<00:09:09.200> stuff. 00:09:09.400 --> 00:09:16.040 I<00:09:09.440> don't<00:09:09.560> know<00:09:09.640> if<00:09:09.680> that<00:09:09.800> affected<00:09:10.240> you<00:09:10.320> 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00:10:31.120 Everyone<00:10:28.480> is<00:10:28.600> super<00:10:28.840> friendly.<00:10:29.200> Everyone<00:10:29.520> really<00:10:29.760> tries<00:10:30.040> to<00:10:30.120> help<00:10:30.240> each<00:10:30.360> other<00:10:30.600> out. 00:10:31.120 --> 00:10:33.520 Um,<00:10:31.480> but<00:10:31.840> everybody<00:10:32.200> really<00:10:32.560> works<00:10:32.920> hard. 00:10:33.520 --> 00:10:38.720 Uh,<00:10:33.600> like<00:10:33.760> when<00:10:33.880> it<00:10:33.960> comes<00:10:34.240> to<00:10:34.560> like<00:10:34.720> the<00:10:34.800> business<00:10:35.320> and<00:10:35.400> making<00:10:35.600> sure<00:10:35.720> everyone<00:10:35.920> is<00:10:36.000> successful<00:10:36.560> and<00:10:36.640> also<00:10:36.840> just<00:10:37.000> making<00:10:37.240> sure<00:10:37.360> that<00:10:37.480> like<00:10:37.600> when<00:10:37.680> it<00:10:37.760> comes<00:10:37.920> to<00:10:38.040> hours, 00:10:38.720 --> 00:10:45.080 everyone<00:10:39.160> is<00:10:39.320> a<00:10:39.400> 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00:11:02.240 --> 00:11:04.920 And<00:11:02.320> that's<00:11:02.480> also<00:11:02.720> why<00:11:03.240> you<00:11:03.320> have<00:11:03.400> to<00:11:03.480> come<00:11:03.640> to<00:11:03.760> the<00:11:03.880> office<00:11:04.160> every<00:11:04.400> day. 00:11:04.920 --> 00:11:10.160 Uh,<00:11:05.000> we<00:11:05.120> are<00:11:05.240> an<00:11:05.360> in-person<00:11:05.960> culture.<00:11:06.560> Uh,<00:11:06.720> you<00:11:06.800> can't<00:11:07.360> work<00:11:07.440> here<00:11:07.640> remotely<00:11:08.080> unless<00:11:08.360> you're<00:11:08.520> on<00:11:08.640> like<00:11:08.800> one<00:11:09.040> select<00:11:09.440> team. 00:11:10.160 --> 00:11:12.480 Um,<00:11:10.280> it's<00:11:10.440> very,<00:11:10.720> very<00:11:11.040> cohesive<00:11:11.480> in<00:11:11.560> that<00:11:11.720> way. 00:11:12.480 --> 00:11:15.160 Um,<00:11:12.680> so<00:11:12.839> it<00:11:13.000> does<00:11:13.280> create<00:11:13.520> a<00:11:13.560> lot<00:11:13.720> of<00:11:13.800> 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00:13:00.480 --> 00:13:04.800 So<00:13:00.680> glad,<00:13:01.040> yeah.<00:13:01.880> And<00:13:02.000> also,<00:13:02.640> uh,<00:13:02.720> have<00:13:02.920> you<00:13:03.000> tried<00:13:03.200> the<00:13:03.280> Libby<00:13:03.600> app? 00:13:04.800 --> 00:13:09.760 No.<00:13:05.760> Okay,<00:13:06.000> so<00:13:06.120> it's<00:13:06.200> the<00:13:06.280> public<00:13:06.640> library<00:13:07.120> app<00:13:07.360> which<00:13:07.520> is<00:13:07.600> the<00:13:07.680> best<00:13:07.960> app<00:13:08.160> of<00:13:08.280> all<00:13:08.400> time<00:13:08.640> and<00:13:08.800> it's<00:13:09.080> free. 00:13:09.760 --> 00:13:14.839 And<00:13:09.957> so<00:13:10.153> they<00:13:10.350> have<00:13:10.546> a<00:13:10.743> lot<00:13:10.939> of<00:13:11.136> audiobooks<00:13:11.332> that<00:13:11.529> you<00:13:11.725> can<00:13:11.922> listen<00:13:12.118> to<00:13:12.315> for<00:13:12.511> free<00:13:12.708> and<00:13:12.904> it's<00:13:13.101> a<00:13:13.297> lot<00:13:13.494> 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might<00:14:43.720> hate<00:14:43.880> my<00:14:44.160> job<00:14:44.800> and 00:14:44.960 --> 00:14:47.240 life.<00:14:45.320> So,<00:14:45.760> I'm,<00:14:46.040> I'm<00:14:46.160> very<00:14:46.360> lucky<00:14:46.600> that<00:14:46.720> I<00:14:46.800> had<00:14:47.000> that. 00:14:47.240 --> 00:14:51.560 So,<00:14:47.360> I<00:14:47.400> think<00:14:47.560> that<00:14:47.680> was<00:14:47.800> probably<00:14:48.080> the<00:14:48.160> best<00:14:49.280> example<00:14:49.640> of<00:14:49.720> someone<00:14:49.920> really<00:14:50.120> taking<00:14:50.360> a<00:14:50.400> chance<00:14:50.640> on<00:14:50.760> me. 00:14:51.560 --> 00:14:53.800 That's<00:14:51.960> amazing.<00:14:52.320> Shanna,<00:14:52.560> thank<00:14:52.760> you<00:14:52.839> so<00:14:52.960> much<00:14:53.160> for<00:14:53.280> coming<00:14:53.560> on. 00:14:53.800 --> 00:14:58.680 What<00:14:53.920> an<00:14:54.000> incredible<00:14:54.440> company<00:14:54.839> you've<00:14:55.000> built.<00:14:56.280> Congrats<00:14:56.760> on<00:14:56.839> the<00:14:56.920> launch<00:14:57.240> too<00:14:57.480> of<00:14:57.640> the<00:14:57.800> Agent<00:14:58.120> Handler. 00:14:58.680 --> 00:15:05.280 My<00:14:59.000> word,<00:14:59.320> I<00:14:59.360> think<00:14:59.600> that's<00:14:59.839> is<00:14:59.960> so<00:15:00.120> important.<00:15:00.680> I'm<00:15:00.839> sure<00:15:01.000> you're<00:15:01.160> already<00:15:01.440> seeing<00:15:01.760> some<00:15:01.920> early<00:15:02.160> success<00:15:02.560> in<00:15:02.680> that,<00:15:02.880> but<00:15:03.440> I<00:15:03.560> can't<00:15:03.839> imagine<00:15:04.200> that<00:15:04.360> not<00:15:04.520> being<00:15:04.720> successful 00:15:05.280 --> 00:15:09.520 given<00:15:05.560> where<00:15:05.720> everything<00:15:06.080> stands.<00:15:06.480> So,<00:15:07.400> good<00:15:07.640> luck<00:15:07.880> there<00:15:08.360> and<00:15:08.720> let's<00:15:08.960> have<00:15:09.080> you<00:15:09.160> back<00:15:09.360> on. 00:15:09.520 --> 00:15:12.080 That'd<00:15:09.640> be<00:15:09.720> fun.<00:15:10.520> All<00:15:10.560> right,<00:15:10.720> thank<00:15:10.960> you<00:15:11.040> so<00:15:11.200> much<00:15:11.400> for<00:15:11.520> having<00:15:11.880> me. 00:15:12.080 --> 00:15:14.839 I<00:15:12.160> really<00:15:12.360> appreciate<00:15:12.839> it. ``` ### Breakthrough Leadership Group Founder Jill Schulman: Why bravery is a trainable leadership skill URL: https://www.ceo.com/episodes/breakthrough-leadership-group-founder-principal-jill-schulman-why-bravery-is-a-trainable-leadership-skill/ Last updated: 2026-08-23T17:44:29.000Z # Making bravery ordinary Ask people to picture bravery, and they picture a firefighter running into a burning building, or a Marine charging into battle. Jill Schulman defines it differently: "Real bravery is taking voluntary action in the presence of fear toward a noble and worthwhile goal," she told the CEO.com Podcast. Speaking up in a meeting qualifies. So does making a decision before you feel ready. Schulman was a United States Marine Corps officer for five years, all of them in peacetime. She is the founder and principal of [Breakthrough Leadership Group](https://jillschulman.com/about/?ref=ceo.com), a leadership development firm, and the author of [The Bravery Effect](https://jillschulman.com/bravery-effect/?ref=ceo.com), a parable about overcoming fear. The book grew out of her capstone research in the [Master of Applied Positive Psychology program](https://www.lps.upenn.edu/degree-programs/mapp?ref=ceo.com) at the University of Pennsylvania, where she studied the science of happiness and kept running into its opposite. "One of the biggest blockers preventing people from reaching self-actualization, happiness, wellbeing, and their highest potential was fear," she said. Her grandfather fought at the [Battle of Tarawa](https://www.history.navy.mil/browse-by-topic/wars-conflicts-and-operations/world-war-ii/1943/tarawa.html?ref=ceo.com), where 1,009 Marines died in three days of fighting. He rarely talked about it. Schulman grew up in a small town in Minnesota watching her parents work jobs they didn't enjoy because they needed the paycheck. She wanted college paid for and a career that meant something, so she applied for a full Marine Corps scholarship, won it, and flew to San Diego. For CEOs, she argues, fear concentrates in two places. The first is uncertainty. The military calls it VUCA: volatility, uncertainty, complexity, ambiguity. Fear makes leaders freeze, and inaction is often the worst available choice. "In the Marines, we never had complete information about the enemy situation. We built the best plan possible and then moved," she said. "You don't wait for perfect certainty. You execute, adapt, and adjust." The second is the difficult conversation. Leaders avoid accountability talks because they're afraid of coming across as either harsh or weak, a framework Schulman rejects. "Brave leadership means being willing to have difficult conversations because you genuinely care," she said. "Hold people accountable, but lead with love." About 12 years ago, Schulman was running leadership development for a large immunology division in the pharmaceutical industry. The job was in Chicago. Her family was in Southern California, where her husband owned furniture stores. One Friday she flew home early and surprised her younger daughter, Brooke, then in kindergarten, at pickup. Brooke ran up, hugged her, and handed her a drawing of the family. It showed Brooke, her sister Sydney, and their dad. No mom. Not long after, her older daughter developed epilepsy. She has since recovered, but between the two moments, Schulman quit corporate America and stayed home. It lasted about six months. "I deeply respect parents who do it full time," she said, "but I realized quickly it wasn't the right fit for me. I felt like I was losing myself." Then Tim Garrett, a former colleague at AbbVie, called and asked if she would come back once a month as a consultant to teach leadership programs. "Sometimes the greatest gift someone can give you is simply believing in you enough that you start believing in yourself too," she said. She said yes. That was the start of Breakthrough Leadership Group. ```chapters 00:00:00 Introduction and Guest Background 00:00:21 Discovering the Study of Bravery 00:01:03 The Role of Fear in Happiness and Self-Actualization 00:01:56 Defining Bravery 00:02:08 Writing "The Bravery Effect" 00:02:41 The Book Writing Process 00:04:04 Collaborating with a Ghostwriter 00:05:05 Publishing Challenges 00:05:27 Practical Examples of Brave Leadership 00:06:07 Leading Through Uncertainty 00:08:14 Having Difficult Conversations 00:09:46 Motivation to Join the Marines 00:11:29 Founding Breakthrough Leadership Group 00:14:57 A Typical Day in Jill's Life 00:16:35 Speaking Engagements 00:17:25 Impact of AI on Work 00:19:23 Reading Preferences and Recommendations 00:22:05 The Importance of Giving and Taking Chances 00:22:23 Acknowledging Key Supporters 00:23:04 Closing Remarks ``` ```vtt WEBVTT 00:00:00.000 --> 00:00:02.200 Jill,<00:00:00.560> thank<00:00:00.760> you<00:00:00.800> so<00:00:00.920> much<00:00:01.080> for<00:00:01.200> coming<00:00:01.480> on<00:00:01.560> the<00:00:01.640> show. 00:00:02.200 --> 00:00:07.360 What<00:00:02.400> an<00:00:02.520> honor<00:00:02.760> to<00:00:02.880> have<00:00:03.200> you.<00:00:03.440> You're<00:00:03.560> the<00:00:03.680> founder<00:00:04.200> and<00:00:04.320> principal<00:00:04.840> of<00:00:05.000> Breakthrough<00:00:05.760> Leadership<00:00:06.360> Group. 00:00:07.360 --> 00:00:09.440 You've<00:00:07.640> written<00:00:07.840> a<00:00:07.880> book<00:00:08.160> called<00:00:08.360> The<00:00:08.440> Bravery<00:00:08.920> Effect. 00:00:09.440 --> 00:00:13.320 You're<00:00:09.640> you're<00:00:09.800> probably<00:00:10.080> the<00:00:10.280> world's<00:00:10.720> most<00:00:10.920> renowned<00:00:11.440> expert<00:00:12.040> on<00:00:12.280> bravery. 00:00:13.320 --> 00:00:17.800 You've<00:00:13.520> served<00:00:13.800> in<00:00:13.960> the<00:00:14.600> United<00:00:14.960> States<00:00:15.240> Marine<00:00:15.640> Corps<00:00:16.040> as<00:00:16.160> an<00:00:16.320> officer. 00:00:17.800 --> 00:00:21.360 Give<00:00:18.040> us<00:00:18.200> a<00:00:18.240> sense<00:00:18.520> for,<00:00:18.880> hey,<00:00:19.760> why<00:00:20.400> is<00:00:20.520> this<00:00:20.720> your<00:00:20.840> passion? 00:00:21.360 --> 00:00:24.960 How<00:00:21.612> how<00:00:21.865> did<00:00:22.117> all<00:00:22.369> of<00:00:22.622> this<00:00:22.874> come<00:00:23.126> about?<00:00:23.378> [sighs<00:00:23.631> and<00:00:23.883> gasps]<00:00:24.135> Uh,<00:00:24.388> great<00:00:24.640> question. 00:00:24.960 --> 00:00:30.880 Well,<00:00:25.120> so<00:00:25.480> great<00:00:25.760> to<00:00:25.880> be<00:00:26.040> here.<00:00:26.560> I'm<00:00:27.200> I've<00:00:27.400> been<00:00:27.520> so<00:00:27.680> excited<00:00:28.040> all<00:00:28.160> weekend<00:00:28.560> to<00:00:28.960> to<00:00:29.080> be<00:00:29.160> able<00:00:29.320> to<00:00:29.480> finally<00:00:29.800> talk<00:00:30.040> to<00:00:30.200> you. 00:00:30.880 --> 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realized<00:01:56.640> that,<00:01:56.800> I'm<00:01:56.880> like,<00:01:57.160> "Wow,<00:01:57.520> this<00:01:57.840> is<00:01:58.080> that<00:01:58.400> fear. 00:01:59.720 --> 00:02:05.120 It<00:02:00.000> holds<00:02:00.440> back<00:02:01.120> all<00:02:01.600> of<00:02:01.760> us<00:02:02.520> from<00:02:02.760> sometimes<00:02:03.400> living<00:02:03.720> our<00:02:03.840> happiest<00:02:04.560> lives." 00:02:05.120 --> 00:02:13.320 So,<00:02:05.960> um<00:02:06.600> I<00:02:06.760> ended<00:02:07.040> up<00:02:07.920> doing<00:02:08.200> my<00:02:08.399> capstone,<00:02:09.200> so<00:02:09.320> my<00:02:09.479> master's<00:02:09.880> thesis,<00:02:10.160> my<00:02:10.360> deep<00:02:10.960> dive<00:02:11.280> and<00:02:11.440> research<00:02:12.080> on<00:02:12.959> how<00:02:13.200> to 00:02:13.320 --> 00:02:19.320 overcome<00:02:14.720> fears,<00:02:16.080> which<00:02:16.480> led<00:02:16.680> me<00:02:16.800> to<00:02:17.320> bravery,<00:02:17.760> science<00:02:18.000> of<00:02:18.080> bravery. 00:02:19.320 --> 00:02:22.560 Yeah.<00:02:19.720> [So,<00:02:20.000> give<00:02:20.200> me<00:02:20.320> a<00:02:20.360> sense<00:02:20.600> for<00:02:20.840> what<00:02:21.200> went<00:02:21.440> into<00:02:21.800> writing<00:02:22.120> the<00:02:22.240> book.] 00:02:22.560 --> 00:02:26.440 Like,<00:02:22.760> what<00:02:22.880> was<00:02:23.000> that<00:02:23.200> process<00:02:23.760> like?<00:02:24.120> And<00:02:24.240> it's<00:02:24.400> out,<00:02:24.760> everybody<00:02:25.120> should<00:02:25.320> go<00:02:25.680> get<00:02:25.920> it. 00:02:26.440 --> 00:02:29.440 I<00:02:26.560> believe<00:02:26.920> wherever<00:02:27.280> you<00:02:27.360> can<00:02:27.440> get<00:02:27.600> books,<00:02:27.920> you<00:02:28.000> can<00:02:28.080> get<00:02:28.240> your<00:02:28.360> book,<00:02:28.640> right<00:02:28.840> there. 00:02:29.440 --> 00:02:35.959 [Yeah,<00:02:29.680> the<00:02:29.760> bravery<00:02:30.080> book.]<00:02:30.160> Um<00:02:30.800> 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that<00:03:21.280> was 00:03:21.400 --> 00:03:28.400 very<00:03:21.640> palatable,<00:03:22.800> and<00:03:22.959> I<00:03:23.000> thought<00:03:23.280> about<00:03:23.519> the<00:03:23.640> very<00:03:23.959> best<00:03:24.400> business<00:03:24.880> books<00:03:25.320> that<00:03:25.519> make<00:03:25.720> the<00:03:25.800> biggest<00:03:26.160> impact<00:03:26.560> on<00:03:26.600> my<00:03:26.720> clients,<00:03:27.160> cuz<00:03:27.320> I've<00:03:27.480> had<00:03:27.600> a<00:03:27.640> leadership<00:03:28.040> development 00:03:28.400 --> 00:03:35.400 company<00:03:28.720> for<00:03:28.840> the<00:03:28.920> last<00:03:29.160> 11<00:03:29.480> years.<00:03:30.440> Some<00:03:30.640> of<00:03:30.720> the<00:03:30.760> best<00:03:31.040> books<00:03:31.280> that<00:03:31.360> I<00:03:31.400> have<00:03:31.480> my<00:03:31.600> clients<00:03:31.959> read<00:03:32.239> are<00:03:32.560> like<00:03:32.800> The<00:03:32.880> One<00:03:33.040> Minute<00:03:33.239> 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Blanchard<00:04:22.560> and 00:04:22.760 --> 00:04:25.800 and<00:04:22.919> just<00:04:23.080> saying,<00:04:23.240> "Gosh,<00:04:23.720> I<00:04:24.120> I'm<00:04:24.280> struggling<00:04:24.919> at<00:04:25.000> the<00:04:25.080> story<00:04:25.480> writing. 00:04:25.800 --> 00:04:30.600 I<00:04:25.880> know<00:04:26.160> that<00:04:26.560> the<00:04:26.640> strategies<00:04:27.320> are<00:04:27.480> sound,<00:04:27.880> but<00:04:28.080> I'm<00:04:28.200> not<00:04:28.440> good<00:04:28.680> at<00:04:28.960> making<00:04:29.240> characters<00:04:29.600> come<00:04:29.720> to<00:04:29.840> life." 00:04:30.600 --> 00:04:35.520 So,<00:04:31.200> um<00:04:31.919> his<00:04:32.200> team<00:04:32.600> along<00:04:32.840> with<00:04:32.960> Spencer<00:04:33.480> Johnson's<00:04:34.040> team<00:04:34.400> recommended<00:04:34.919> a<00:04:34.960> ghost<00:04:35.280> writer. 00:04:35.520 --> 00:04:39.720 So,<00:04:36.280> I<00:04:36.440> end<00:04:36.560> up<00:04:36.720> 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I<00:05:35.120> love<00:05:35.360> your 00:05:35.480 --> 00:05:41.120 definition<00:05:36.000> of<00:05:36.160> it.<00:05:36.880> Um<00:05:38.080> how<00:05:38.240> does<00:05:38.400> that<00:05:38.600> show<00:05:38.919> up<00:05:39.120> like<00:05:39.320> on<00:05:39.440> a<00:05:39.480> day-to-day<00:05:39.960> basis<00:05:40.400> as<00:05:40.520> a<00:05:40.600> CEO? 00:05:41.120 --> 00:05:46.560 Cuz<00:05:41.280> it<00:05:41.400> cuz<00:05:41.560> I<00:05:41.640> imagine<00:05:42.000> like<00:05:42.200> a<00:05:42.240> lot<00:05:42.480> of<00:05:42.600> CEOs<00:05:44.240> um<00:05:44.760> are<00:05:44.919> fearful<00:05:45.400> of<00:05:45.520> all<00:05:45.640> sorts<00:05:45.960> of<00:05:46.040> things. 00:05:46.560 --> 00:05:50.320 [Mhm]<00:05:47.200> And<00:05:47.360> that's<00:05:47.560> part<00:05:47.720> of<00:05:47.760> your<00:05:47.840> definition<00:05:48.200> is<00:05:48.440> where<00:05:48.600> fear<00:05:48.920> is<00:05:49.040> involved,<00:05:49.920> right? 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does<00:06:05.280> that<00:06:05.480> mean? 00:06:07.459 --> 00:06:10.160 [sighs<00:06:07.633> and<00:06:07.807> gasps]<00:06:07.981> Let<00:06:08.155> me<00:06:08.330> give<00:06:08.504> a<00:06:08.678> couple<00:06:08.852> of<00:06:09.026> practical<00:06:09.200> examples. 00:06:10.160 --> 00:06:16.120 Like<00:06:10.560> one<00:06:11.960> here<00:06:12.200> here's<00:06:12.400> common<00:06:12.800> things<00:06:13.080> I<00:06:13.160> hear<00:06:13.520> from<00:06:14.120> leaders<00:06:15.120> as<00:06:15.440> as<00:06:15.600> I<00:06:15.680> work<00:06:15.840> with<00:06:15.960> them. 00:06:16.120 --> 00:06:21.520 Number<00:06:16.320> one<00:06:16.480> is<00:06:16.600> the<00:06:16.720> fear<00:06:17.000> of<00:06:17.200> uncertainty.<00:06:18.880> So,<00:06:19.080> we<00:06:19.280> don't<00:06:19.520> know<00:06:19.640> what's<00:06:19.840> happening<00:06:20.280> with<00:06:20.520> volatile<00:06:21.040> times. 00:06:21.520 --> 00:06:27.480 In<00:06:21.600> the<00:06:21.680> 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--> 00:07:58.240 So,<00:07:50.320> make<00:07:50.640> the<00:07:50.720> decision<00:07:51.160> in<00:07:51.440> in<00:07:51.800> uncertainty,<00:07:52.320> start<00:07:52.720> executing,<00:07:53.280> and<00:07:53.360> then<00:07:53.560> know<00:07:54.520> that<00:07:54.680> your<00:07:54.880> plan<00:07:55.360> will<00:07:55.440> have<00:07:55.600> to<00:07:55.720> shift<00:07:56.920> once<00:07:57.480> you<00:07:57.640> get<00:07:57.800> a<00:07:57.880> little<00:07:58.120> bit 00:07:58.240 --> 00:08:00.200 of<00:07:58.400> information<00:07:59.360> from<00:07:59.680> the<00:07:59.760> market. 00:08:00.200 --> 00:08:03.040 Like,<00:08:00.360> this<00:08:00.480> is<00:08:00.600> working,<00:08:00.880> this<00:08:01.000> is<00:08:01.080> working,<00:08:01.280> this<00:08:01.400> is<00:08:01.440> not<00:08:01.600> working.<00:08:01.840> So,<00:08:01.960> you<00:08:02.080> just<00:08:02.240> make<00:08:02.400> the<00:08:02.480> adjustments. 00:08:03.040 --> 00:08:09.520 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conversations. 00:08:36.200 --> 00:08:45.680 Like,<00:08:36.400> avoiding<00:08:37.360> challenges.<00:08:37.919> If<00:08:38.039> there's<00:08:38.320> tension<00:08:39.120> between<00:08:39.479> you<00:08:39.800> and<00:08:41.080> a<00:08:41.200> member<00:08:41.640> of<00:08:42.120> your<00:08:42.360> executive<00:08:42.960> team,<00:08:43.719> you<00:08:43.840> know,<00:08:45.200> avoiding 00:08:45.680 --> 00:08:51.640 it<00:08:45.920> is<00:08:46.200> not<00:08:46.400> helping.<00:08:46.720> So,<00:08:47.000> having<00:08:47.520> the<00:08:47.640> courage<00:08:47.960> to<00:08:48.040> have<00:08:48.160> the<00:08:48.240> conversation,<00:08:49.240> but<00:08:49.400> also<00:08:49.640> skillfully<00:08:50.200> knowing<00:08:50.480> how<00:08:50.560> to<00:08:50.680> do<00:08:50.839> it. 00:08:51.640 --> 00:08:58.760 A<00:08:51.680> lot<00:08:51.880> of<00:08:51.960> leaders<00:08:52.240> actually<00:08:52.520> make<00:08:52.680> this<00:08:52.839> mistake<00:08:53.360> 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00:13:40.480 That<00:13:33.240> was<00:13:33.360> probably<00:13:33.520> the<00:13:33.680> only<00:13:33.880> job<00:13:34.200> I<00:13:34.320> failed<00:13:34.960> in<00:13:35.240> because,<00:13:36.240> I<00:13:36.320> mean,<00:13:36.440> it<00:13:36.520> was<00:13:36.720> wonderful<00:13:37.240> for<00:13:37.360> the<00:13:37.480> first<00:13:37.760> month,<00:13:38.080> but<00:13:38.280> I'm<00:13:38.440> just,<00:13:38.640> maybe<00:13:38.920> it's<00:13:39.880> the<00:13:39.920> little<00:13:40.120> girl<00:13:40.320> that 00:13:40.480 --> 00:13:45.400 wanted<00:13:40.680> to<00:13:40.760> be<00:13:40.840> a<00:13:40.880> Marine<00:13:41.080> 'cause<00:13:41.200> it<00:13:41.280> was<00:13:41.400> challenging.<00:13:41.880> I<00:13:42.000> really<00:13:43.800> felt<00:13:44.040> like<00:13:44.200> I<00:13:44.280> was<00:13:44.480> losing<00:13:44.840> myself. 00:13:45.400 --> 00:13:53.000 So,<00:13:46.120> um,<00:13:47.280> after<00:13:47.520> doing<00:13:47.800> 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you've<00:23:15.160> had,<00:23:15.560> life<00:23:15.840> you've<00:23:16.040> had,<00:23:16.360> and<00:23:16.520> leader<00:23:16.800> you<00:23:17.000> are. 00:23:17.360 --> 00:23:19.640 Really,<00:23:17.640> it<00:23:17.720> means<00:23:17.960> a<00:23:18.000> lot<00:23:18.160> to<00:23:18.240> have<00:23:18.440> you<00:23:18.520> here.<00:23:19.440> All<00:23:19.480> right. 00:23:19.640 --> 00:23:22.080 Well,<00:23:19.760> thank<00:23:20.000> you<00:23:20.080> so<00:23:20.200> much<00:23:20.400> for<00:23:20.480> having<00:23:20.760> me,<00:23:20.880> and<00:23:21.000> thanks<00:23:21.200> for<00:23:21.320> the<00:23:21.400> book<00:23:21.560> recommendation. 00:23:22.080 --> 00:23:24.640 I<00:23:22.120> can't<00:23:22.320> wait<00:23:22.440> to<00:23:22.480> read<00:23:22.640> it. ``` ### ICED Media Founder & CEO Leslie Ann Hall: How AI is transforming beauty discovery URL: https://www.ceo.com/episodes/iced-media-founder-ceo-leslie-ann-hall-how-ai-is-transforming-beauty-discovery/ Last updated: 2026-08-23T17:59:08.000Z # Inside the agency preparing beauty brands for the zero-click era It took Leslie Ann Hall 15 years to figure out what her agency should be. She will tell you that herself. "For many years, gosh, over 20 years running the business, we were really generalists in an industry where I've come to learn specialists truly have an advantage," Hall said on the CEO.com Podcast. "It probably took me a little too long, but around 15 years in, we really figured out that when we specialized in beauty and performance marketing, we were unmatched in our acumen." Hall is the founder and CEO of [ICED Media](https://www.icedmedia.com/leadership?ref=ceo.com). The agency has worked with [L'Oréal, Moroccanoil, CoverGirl, Neutrogena, Saie, and Topicals](https://cew.org/people/leslie-ann-hall/?ref=ceo.com) across more than two decades, and its strategy work has contributed to several billion-dollar exits. Specialization, she said, created a flywheel. ICED Media became a Meta Business Partner, a TikTok Marketing Partner, and in 2023 one of the first badged TikTok Shop Partners in the United States. That last bet paid. NielsenIQ now ranks TikTok Shop the [fourth-largest health and beauty e-commerce retailer in the U.S.](https://nielseniq.com/global/en/insights/infographic/2026/niq-perspective-how-tiktok-shop-is-reshaping-beauty-ecommerce-in-the-u-s/?ref=ceo.com), with sales past $4.4 billion and category growth of 84 percent year over year. Hall thinks the next shift is bigger. "I genuinely believe this is the single biggest disruption in our lifetimes in terms of how consumers discover beauty products and services," she said. "We are at the dawn of a completely new era of discovery." When OpenAI launched shopping inside ChatGPT in September 2025, it put the audience at [more than 700 million weekly users](https://openai.com/index/buy-it-in-chatgpt/?ref=ceo.com). Hall says they are asking it about acne, hyperpigmentation, and GLP-1-related skin issues. ICED Media [launched a Search and Discovery practice](https://www.prnewswire.com/news-releases/beautys-big-shake-up-iced-media-launches-search-taps-vet-emily-rose-campbell-302549780.html?ref=ceo.com) around that shift, centered on Generative Engine Optimization, or GEO, the work of getting brands to rank inside large language model results. It has since run [a sold-out event series with Shopify and CEW](https://cew.org/event/the-ai-shopping-playbook-how-beautys-leading-brands-are-winning-at-ai-geo-conversational-commerce/?ref=ceo.com) teaching beauty brands how to do it. "That's really the beginning of what we're calling the zero-click era of commerce," Hall said. "I think it's going to democratize digital selling for beauty brands and create entirely new ways for brands to communicate with consumers." The transaction layer has proven harder than the discovery layer. OpenAI [retired Instant Checkout in March 2026](https://www.cnbc.com/2026/03/24/openai-revamps-shopping-experience-in-chatgpt-after-instant-checkout.html?ref=ceo.com) after struggling to onboard merchants, and now routes buyers to retailers' own storefronts. Discovery moved. Checkout, so far, has not. Inside the agency, Hall's leadership team started with a different question. If AI automates certain tasks, what should people do with the time? The answer was to collaborate with coworkers and build deeper relationships with clients. "Understanding that AI allows us to reinvest in ourselves as humans is a really powerful opportunity," she said. Every January, Hall presents the year's goals to her team. "Our number one goal never changes because we are a service business: employee retention and client retention," she said. "If we don't retain employees, we won't retain clients." ICED Media retained 100 percent of its employees in 2023 and 2024\. Hall credits a culture of accountability. "Whenever there's a mistake or hiccup internally, you'll hear multiple people immediately say, 'That was my fault. Here's what I could have done better,'" she said. "I personally believe everything is my responsibility because it's my company." For most of her career, Hall was a practitioner, not the public face of the company. Then she formalized her relationships with senior beauty executives into an advisory board that meets quarterly, in person when possible, with formal agendas. The board told her something she did not want to hear. They could advocate for the agency all day, and it would never carry the weight of Hall doing it herself. She listened. Today she speaks to audiences of thousands, contributes to [The Business of Fashion, Women's Wear Daily, Shoptalk, and CEW](https://cew.org/people/leslie-ann-hall/?ref=ceo.com), and takes the stage on digital discovery at [Shoptalk Fall in Nashville](https://fall.shoptalk.com/speaker-list/leslie-ann-hall?ref=ceo.com) on September 30. Shoptalk took 17 emails. "One of my major goals was speaking at Shoptalk, one of the biggest conferences in digital marketing. I believe I contacted the head of programming 17 times. Seventeen," she said. "If I had stopped after two emails because I thought, 'He probably isn't interested,' I never would have gotten that opportunity." An entrepreneur on her advisory board gave her the line she repeats: "Having no shame is a superpower." Women, Hall said, are often taught to make themselves smaller than their male counterparts. Sometimes success requires continuing to ask. The CEO.com Podcast ends every conversation the same way, asking who gave the guest a chance. Hall named Andrea Nagel, who runs programming for [Cosmetic Executive Women](https://cew.org/?ref=ceo.com), the 9,000-member organization she calls the largest professional network in beauty. Hall was green then. Nagel told her not many people knew who she was yet. Hall pitched a webinar anyway, and Nagel said yes. It became one of CEW's best-attended ever. "I'll always be grateful to her for that opportunity," Hall said. "And I hope I can give similar opportunities to others throughout my own career." ```chapters 00:00:00 Introduction and Guest Welcome 00:00:20 Leslie Anne Hall's Background and Iced Media Overview 00:01:04 Specialization in Beauty and Performance Marketing 00:01:57 AI Integration in Iced Media 00:03:08 AI's Impact on Consumer Discovery in Beauty 00:04:45 Search and Discovery Discipline at Iced Media 00:05:51 A Day in the Life of Leslie Anne Hall 00:07:06 Building Relationships and Company Culture 00:10:30 Challenges in the Beauty Industry 00:12:31 Reading Recommendations 00:15:25 Proud Projects and Advisory Board 00:18:24 Advice for Aspiring Thought Leaders 00:22:01 Acknowledging Those Who Gave a Chance 00:24:11 Closing Remarks and Gratitude ``` ```vtt WEBVTT 00:00:00.000 --> 00:00:01.920 Leslie,<00:00:00.560> thank<00:00:00.720> you<00:00:00.800> so<00:00:00.920> much<00:00:01.120> for<00:00:01.240> coming<00:00:01.480> on<00:00:01.560> the<00:00:01.640> show. 00:00:01.920 --> 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I<00:06:01.880> usually 00:06:02.320 --> 00:06:08.080 am<00:06:02.440> good<00:06:02.600> about,<00:06:02.960> not<00:06:03.200> always.<00:06:04.560> Um<00:06:04.720> but<00:06:04.880> that's<00:06:05.160> really<00:06:05.400> important<00:06:05.840> for<00:06:05.960> me<00:06:06.200> just<00:06:06.600> to<00:06:06.760> fill<00:06:07.000> my<00:06:07.200> soul. 00:06:08.080 --> 00:06:16.560 And<00:06:08.320> then<00:06:09.520> now<00:06:10.360> a<00:06:10.480> lot<00:06:10.920> more<00:06:11.240> of<00:06:11.360> my<00:06:11.560> time<00:06:12.120> is<00:06:12.280> spent<00:06:12.880> on<00:06:13.240> thought<00:06:13.560> leadership<00:06:14.280> and<00:06:14.440> public<00:06:14.840> speaking<00:06:15.600> and<00:06:15.840> really<00:06:16.120> trying 00:06:16.560 --> 00:06:20.760 to<00:06:16.760> be<00:06:17.720> a<00:06:17.880> resource<00:06:18.520> to<00:06:18.760> the<00:06:18.960> beauty<00:06:19.440> industry. 00:06:20.760 --> 00:06:28.919 I'm<00:06:21.040> 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00:12:25.040 also<00:12:21.960> make<00:12:22.280> sure<00:12:22.640> that<00:12:22.800> they're<00:12:22.960> not<00:12:23.200> getting<00:12:23.520> left<00:12:23.840> behind. 00:12:25.040 --> 00:12:31.000 Mhm.<00:12:26.120> What<00:12:26.240> do<00:12:26.320> you<00:12:26.480> read?<00:12:27.520> And<00:12:27.680> what<00:12:27.880> reading<00:12:28.160> recommendations<00:12:28.800> do<00:12:28.880> you<00:12:29.000> have<00:12:29.120> for<00:12:29.320> us? 00:12:31.000 --> 00:12:39.520 I<00:12:31.160> am<00:12:31.720> such<00:12:32.120> an<00:12:32.240> avid<00:12:32.640> reader,<00:12:33.720> mostly<00:12:34.280> non-fiction,<00:12:35.640> what<00:12:36.160> back<00:12:36.480> in<00:12:36.560> the<00:12:36.680> day<00:12:36.880> I'm<00:12:37.120> aging<00:12:37.480> myself,<00:12:38.080> but<00:12:38.360> would<00:12:38.600> probably<00:12:39.240> be 00:12:39.520 --> 00:12:45.040 called<00:12:40.160> self-help<00:12:41.120> and<00:12:42.200> business<00:12:42.640> 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back<00:24:16.880> on<00:24:17.000> again,<00:24:17.280> too.<00:24:17.560> I<00:24:17.640> like<00:24:17.840> I'm<00:24:18.000> so<00:24:18.160> impressed<00:24:18.520> with<00:24:18.600> what<00:24:18.720> you've<00:24:18.920> done. 00:24:20.160 --> 00:24:25.080 Uh<00:24:20.360> the<00:24:21.080> uh<00:24:21.160> leader<00:24:21.480> you<00:24:21.680> are,<00:24:22.440> the<00:24:22.560> people<00:24:22.880> you<00:24:23.000> speak<00:24:23.320> with,<00:24:23.760> the<00:24:23.840> lives<00:24:24.160> that<00:24:24.280> you<00:24:24.400> change. 00:24:25.080 --> 00:24:28.920 Thank<00:24:25.331> you<00:24:25.583> so<00:24:25.834> much<00:24:26.086> for<00:24:26.337> coming<00:24:26.589> on<00:24:26.840> ceo.com.<00:24:27.091> <00:24:27.343> Thank<00:24:27.594> you<00:24:27.846> for<00:24:28.097> having<00:24:28.349> me,<00:24:28.600> Clint. 00:24:28.920 --> 00:24:31.800 This<00:24:29.080> has<00:24:29.200> been<00:24:29.400> so<00:24:29.520> much<00:24:29.800> fun. ``` ### LearnUpon Co-Founder & CEO, Brendan Noud: How AI will transform personalized learning URL: https://www.ceo.com/episodes/learnupon-co-founder-ceo-brendan-noud-how-ai-will-transform-personalized-learning/ Last updated: 2026-08-23T18:13:41.000Z # Brendan Noud built LearnUpon on customers, not capital Brendan Noud and Des Anderson left an established learning management system provider in 2012 and started LearnUpon at a kitchen table. Noud had spent eight years there on the sales side, Anderson 12 on the technical side, and from the front of the sales process Noud could see demand his employer had no interest in meeting. "We could see there was a pent-up demand for a cloud SaaS solution that was easy to use and quick to set up," Noud said on the CEO.com podcast. "Our previous employer had an on-premise solution, and we just felt cloud was the future. So we decided to leave and start around the kitchen table as a two-person startup." Noud lives in Kildare, about an hour south of Dublin. He and Anderson went through the [NDRC](https://www.ndrc.ie/?ref=ceo.com) accelerator at the start, a cohort of about 14 companies. The funding was roughly $20,000. "Honestly, the real value was the network," Noud said. "When you're starting a business for the first time, having great mentors and other founders around you is hugely valuable. We got great advice early on, especially around focusing on a specific ICP. And there's something motivating about being surrounded by other founders who are living on beans and toast and working around the clock trying to build traction." In 2013 they raised a little over half a million dollars, friends-and-family money matched by Enterprise Ireland. For the next seven years, that was it. The business funded itself by adding customers. Around 20 or 30 customers in, the motion started to feel repeatable. Leads came in every week, the close rate was high, and the feedback was good even though the founders knew the platform wasn't where they wanted it yet. In 2014, LearnUpon won its first enterprise deal, a quick-service restaurant chain in the U.S. "They had procurement teams, legal teams, all of that," Noud said. "And we won that deal against much larger incumbents. That was a huge moment where we thought, okay, this is real. We can compete here." By 2020 the company had [grown annual recurring revenue by more than 50 percent year over year for 12 consecutive quarters](https://www.learnupon.com/blog/learnupon-closes-growth-equity-investment-summit-partners/?ref=ceo.com), and it took its first institutional money, a [$56 million minority investment from Summit Partners](https://www.businesswire.com/news/home/20201020005291/en/LearnUpon-Closes-%2456-Million-Growth-Equity-Investment-from-Summit-Partners-to-Help-Businesses-Unlock-the-Power-of-Learning?ref=ceo.com). Today LearnUpon serves more than 25 million learners, handles more than a billion requests a month, and employs over 300 people across Dublin, Philadelphia, and Salt Lake City. Philadelphia opened in 2016, after years of Irish employees working night shifts to cover U.S. customers. Salt Lake City came about three years ago, and LearnUpon relocated a few Dublin employees there first to hire and embed the culture before building out the local team. That culture is written down. Years ago, Noud and Anderson created a culture code, inspired in part by HubSpot's, after Noud heard Dharmesh Shah speak about it. The pillars are act like an owner, deliver quality, lead with curiosity, and put the customer at the center of everything. One of the company's earliest hires recently celebrated 12 years at LearnUpon. Several others have passed a decade. "We also talk a lot about everyone being guardians of the culture," Noud said. "It's not just the responsibility of leadership. Everybody owns it. And culture evolves. The culture at 20 people is very different from the culture at 300 people. So you have to continually work on it." The past year has been the busiest in the company's history. In November 2025 LearnUpon [acquired Courseau](https://www.learnupon.com/newsroom/learnupon-acquires-courseau/?ref=ceo.com), a Berlin-founded AI course authoring startup. In March it launched [Create+](https://www.learnupon.com/newsroom/learnupon-launches-ai-native-content-authoring/?ref=ceo.com), which turns PDFs, videos, and documents into structured courses in minutes. In July it announced its [Agentic Learning Platform](https://www.learnupon.com/blog/introducing-learnupons-agentic-learning-platform/?ref=ceo.com), which automates administrative workflows while keeping oversight with the humans running them. "We're very conscious of making sure there's still a human in the loop because our customers are cautious too," Noud said. "They don't want AI just running off and making every decision autonomously. But for repetitive admin-heavy tasks, it's an incredible opportunity." The company's biggest focus now is personalized learning at scale. "That's been something people in learning and development have talked about forever as this kind of holy grail, but historically it was very difficult to truly achieve," Noud said. "Now, with AI, we can get much closer to delivering the right learning to the right person at exactly the right time." When the conversation turned to AI in education more broadly, Noud reached for the calculator. Schools banned it, then accepted it as a tool, as long as students understood the theory underneath. "I think AI is very similar," he said. "Skills like creativity, critical thinking, and communication are probably going to become even more important." Every CEO.com conversation ends with the same question: who gave you a chance? Noud named Michael Atwire, his first manager at KPMG Consulting, where he started as a graduate consultant. "At that stage in your career, you often expect to spend your days photocopying or reading manuals," Noud said. "But my manager, Michael Atwire, immediately brought me out on-site into real client meetings. This was during the height of the Y2K era back in 1999\. He exposed me to boardroom meetings, strategy work, and client engagement right from day one. That experience shaped the rest of my career. I learned a tremendous amount from him, and I'm very grateful he took a chance on me so early." ```chapters 00:00:00 Introduction and Background 00:00:26 Founding LearnUpon 00:01:18 Initial Focus and Evolution 00:02:00 Funding and Tech Scene in Ireland 00:04:27 Realizing Success 00:05:42 Impact of AI on Learning Management 00:07:17 AI in General Education 00:08:48 A Day in the Life of a CEO 00:10:18 Reading Recommendations 00:11:00 Company Culture 00:12:23 Becoming a Global Company 00:13:49 Macroeconomic Environment 00:15:19 Learning from Failures 00:17:06 Future Roadmap 00:18:57 Final Question: Who Gave You a Chance? ``` ```vtt WEBVTT 00:00:00.000 --> 00:00:02.400 Brandon,<00:00:00.560> thank<00:00:00.720> you<00:00:00.800> so<00:00:00.920> much<00:00:01.120> for<00:00:01.240> coming<00:00:01.640> on<00:00:01.800> the<00:00:01.920> show. 00:00:02.400 --> 00:00:05.640 You<00:00:02.560> are<00:00:02.680> the<00:00:02.840> co-founder<00:00:03.520> and<00:00:03.680> CEO<00:00:04.400> 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it<00:01:59.040> a<00:01:59.080> go. 00:02:00.200 --> 00:02:03.320 And<00:02:00.480> how<00:02:00.560> did<00:02:00.760> you<00:02:01.080> think<00:02:01.320> about<00:02:02.080> funding<00:02:02.600> the<00:02:02.680> company? 00:02:03.320 --> 00:02:06.280 Like<00:02:03.840> and<00:02:03.960> did<00:02:04.120> you<00:02:04.560> you're<00:02:04.800> from<00:02:05.040> Ireland,<00:02:05.720> Dublin? 00:02:06.280 --> 00:02:09.840 Do<00:02:06.360> you<00:02:06.440> live<00:02:06.560> in<00:02:06.640> Dublin?<00:02:07.440> Uh<00:02:07.920> Kildare,<00:02:08.399> which<00:02:08.560> is<00:02:08.640> about<00:02:08.840> an<00:02:08.960> hour<00:02:09.119> south<00:02:09.399> of<00:02:09.440> Dublin. 00:02:09.840 --> 00:02:12.800 Yeah.<00:02:09.920> Okay.<00:02:10.679> Um<00:02:11.360> and<00:02:11.520> you<00:02:11.600> founded<00:02:12.000> it<00:02:12.120> there. 00:02:12.800 --> 00:02:18.040 To<00:02:12.920> give<00:02:13.080> us<00:02:13.200> a<00:02:13.240> sense<00:02:13.480> 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Relics. 00:02:46.120 --> 00:02:53.320 And<00:02:46.440> I<00:02:46.480> think<00:02:46.720> off<00:02:46.959> the<00:02:47.080> back<00:02:47.360> of<00:02:47.440> that,<00:02:48.320> you<00:02:48.400> have<00:02:48.520> a<00:02:48.600> lot<00:02:48.800> of<00:02:48.880> people<00:02:49.240> leave<00:02:49.600> to<00:02:49.720> do<00:02:50.200> startups<00:02:50.959> and<00:02:51.160> there's<00:02:51.360> good<00:02:51.560> accelerator<00:02:52.080> programs. 00:02:53.320 --> 00:03:00.880 Myself<00:02:53.760> and<00:02:53.880> Des<00:02:54.200> went<00:02:54.520> on<00:02:54.680> the<00:02:54.880> NDRC<00:02:56.080> um<00:02:56.160> accelerator<00:02:56.840> program<00:02:57.720> right<00:02:57.959> at<00:02:58.080> the<00:02:58.160> start<00:02:59.160> and<00:02:59.239> there<00:02:59.320> was<00:02:59.640> 14<00:03:00.080> other<00:03:00.239> companies. 00:03:00.880 --> 00:03:03.560 They<00:03:01.000> kind<00:03:01.200> of<00:03:01.320> take<00:03:01.600> intakes<00:03:02.239> every<00:03:02.519> 6<00:03:02.760> months. 00:03:03.560 --> 00:03:09.959 And<00:03:04.200> not<00:03:04.480> much<00:03:04.720> funding,<00:03:05.160> about<00:03:05.440> 15,000<00:03:07.480> euros,<00:03:07.959> so<00:03:08.080> maybe<00:03:08.239> $20,000. 00:03:09.959 --> 00:03:14.080 But<00:03:10.200> it<00:03:10.320> was<00:03:10.480> more<00:03:10.800> actually,<00:03:11.440> I<00:03:11.519> suppose<00:03:11.760> the<00:03:11.880> network<00:03:12.400> when<00:03:12.519> you're<00:03:12.640> starting<00:03:13.040> a<00:03:13.080> business<00:03:13.440> for<00:03:13.519> the<00:03:13.600> first<00:03:13.840> time. 00:03:14.080 --> 00:03:21.120 There<00:03:14.160> was<00:03:14.280> great<00:03:14.560> mentors.<00:03:15.560> We<00:03:15.760> got<00:03:16.040> lots<00:03:16.320> of<00:03:16.400> great<00:03:16.640> advice<00:03:17.120> in<00:03:17.200> the<00:03:17.320> early<00:03:17.480> days,<00:03:17.760> particularly<00:03:18.200> around<00:03:18.560> focusing<00:03:19.160> on<00:03:19.280> a<00:03:19.320> particular<00:03:20.040> ICP. 00:03:21.120 --> 00:03:28.680 And<00:03:21.480> and<00:03:21.560> then<00:03:21.720> you<00:03:21.800> have<00:03:21.959> that<00:03:22.120> support<00:03:22.519> structure<00:03:23.040> of<00:03:23.239> other<00:03:23.440> founders<00:03:23.959> who<00:03:24.160> are<00:03:25.239> living<00:03:25.560> on<00:03:25.680> beans<00:03:25.959> and<00:03:26.080> toast<00:03:26.519> and<00:03:27.239> you<00:03:27.320> know,<00:03:27.480> working<00:03:27.760> around<00:03:28.000> the<00:03:28.080> clock<00:03:28.360> to<00:03:28.440> try 00:03:28.680 --> 00:03:36.040 and<00:03:28.800> get<00:03:29.000> some<00:03:29.160> early<00:03:29.360> traction.<00:03:30.800> And<00:03:30.920> I<00:03:30.959> think<00:03:31.160> it's<00:03:31.480> it's<00:03:31.640> much<00:03:31.880> easier<00:03:32.200> to<00:03:32.360> do<00:03:32.560> that<00:03:33.440> in<00:03:33.600> an<00:03:33.680> accelerator<00:03:34.560> maybe<00:03:34.800> 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Partners,<00:04:24.040> which<00:04:24.240> was<00:04:24.360> the<00:04:24.440> first<00:04:24.680> time<00:04:24.840> we<00:04:24.919> took<00:04:25.120> professional<00:04:25.640> money<00:04:25.919> into<00:04:26.120> the<00:04:26.200> business. 00:04:27.640 --> 00:04:30.919 At<00:04:27.760> what<00:04:27.919> point<00:04:28.120> did<00:04:28.280> you<00:04:28.360> realize<00:04:28.720> you<00:04:28.840> had<00:04:29.080> something<00:04:29.440> that<00:04:29.640> and<00:04:29.800> that<00:04:29.919> it<00:04:29.960> was<00:04:30.120> going<00:04:30.320> to<00:04:30.440> work? 00:04:30.919 --> 00:04:36.320 And<00:04:31.200> obviously<00:04:31.560> as<00:04:31.640> an<00:04:31.760> entrepreneur<00:04:32.600> in<00:04:32.720> a<00:04:32.800> founder,<00:04:33.640> it<00:04:33.800> almost<00:04:34.160> feels<00:04:34.320> like<00:04:34.480> it's<00:04:34.600> never. 00:04:36.320 --> 00:04:40.440 Uh<00:04:36.720> you<00:04:36.840> know,<00:04:37.000> you<00:04:37.160> 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legal<00:05:21.040> teams.<00:05:21.240> I'm<00:05:21.320> like,<00:05:21.720> "Okay,<00:05:22.240> we're<00:05:22.440> we're<00:05:22.600> in<00:05:22.720> the<00:05:22.760> bigger<00:05:23.040> leagues<00:05:23.400> now." 00:05:23.600 --> 00:05:31.800 And<00:05:23.680> when<00:05:23.800> we<00:05:23.919> won<00:05:24.120> that<00:05:24.440> against,<00:05:25.080> you<00:05:25.160> know,<00:05:25.640> much<00:05:25.880> larger<00:05:27.040> uh<00:05:27.320> incumbents<00:05:28.200> um<00:05:28.360> to<00:05:28.520> win<00:05:28.760> that<00:05:29.080> business,<00:05:29.760> I<00:05:29.840> think<00:05:30.040> again<00:05:30.360> it<00:05:30.680> pointed<00:05:31.120> that,<00:05:31.280> "Okay,<00:05:31.600> there's 00:05:31.800 --> 00:05:36.040 definitely<00:05:32.160> something<00:05:32.560> here<00:05:33.240> and<00:05:33.760> and<00:05:33.840> we<00:05:33.919> just<00:05:34.120> need<00:05:34.280> to<00:05:34.360> really<00:05:34.560> go<00:05:34.760> for<00:05:34.919> this." 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we're<00:05:51.120> we're<00:05:51.320> looking<00:05:51.560> at<00:05:51.680> that. 00:05:52.320 --> 00:05:58.960 But<00:05:52.520> in<00:05:52.640> general,<00:05:52.960> trying<00:05:53.160> to<00:05:53.320> automate<00:05:53.800> a<00:05:53.880> lot<00:05:54.440> of<00:05:55.040> the<00:05:55.240> admin<00:05:55.640> tasks<00:05:56.160> around<00:05:57.000> delivering<00:05:57.480> learning<00:05:57.840> at<00:05:57.960> scale. 00:05:58.960 --> 00:06:07.440 Uh<00:05:59.040> particularly<00:05:59.520> around<00:06:00.480> um<00:06:00.800> we're<00:06:00.920> we're<00:06:01.320> looking<00:06:01.560> to<00:06:01.640> build<00:06:01.920> personalized<00:06:02.440> learning<00:06:02.760> journeys<00:06:03.280> driven<00:06:03.600> off<00:06:03.800> AI<00:06:04.360> based<00:06:04.680> on<00:06:05.480> um<00:06:06.080> what<00:06:06.240> people<00:06:06.480> are<00:06:06.600> interested<00:06:07.200> in, 00:06:07.440 --> 00:06:09.520 based<00:06:07.720> on<00:06:07.840> 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need<00:07:07.840> some<00:07:08.000> oversight<00:07:08.480> as<00:07:08.600> well.<00:07:08.880> So<00:07:09.520> it's<00:07:09.800> uh<00:07:10.000> but<00:07:10.240> for<00:07:10.760> for<00:07:10.919> those<00:07:11.320> kind<00:07:11.600> of<00:07:11.800> admin<00:07:13.000> time-consuming<00:07:13.680> tasks<00:07:14.200> that<00:07:14.320> can<00:07:14.440> be<00:07:14.600> automated,<00:07:15.360> it's 00:07:15.720 --> 00:07:18.280 it's<00:07:15.880> a<00:07:15.960> super<00:07:16.280> opportunity.<00:07:17.800> Yeah. 00:07:18.280 --> 00:07:24.120 Yeah,<00:07:18.640> AI<00:07:18.919> is<00:07:19.040> such<00:07:19.240> a<00:07:19.280> fascinating<00:07:20.760> uh<00:07:21.360> challenge<00:07:21.840> for<00:07:22.000> every<00:07:22.600> industry<00:07:23.040> and<00:07:23.120> every<00:07:23.320> business. 00:07:24.120 --> 00:07:31.080 And<00:07:24.240> I<00:07:24.280> know<00:07:24.440> you're<00:07:24.600> more<00:07:24.840> on<00:07:24.960> like<00:07:25.120> 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perspective,<00:08:05.520> it's<00:08:05.720> similar<00:08:06.160> like<00:08:06.600> there<00:08:06.680> was<00:08:06.760> obviously<00:08:07.000> people<00:08:07.240> talking<00:08:07.520> about<00:08:08.280> AI<00:08:08.600> doing<00:08:08.920> people's 00:08:09.320 --> 00:08:14.680 homework<00:08:09.673> and<00:08:10.027> assignments<00:08:10.380> and<00:08:10.733> and<00:08:11.087> are<00:08:11.440> they<00:08:11.793> actually<00:08:12.147> learning<00:08:12.500> um<00:08:12.853> as<00:08:13.207> a<00:08:13.560> result? 00:08:14.680 --> 00:08:22.000 Uh<00:08:14.760> and<00:08:14.880> I<00:08:14.919> think<00:08:15.080> it's<00:08:15.200> getting<00:08:15.440> that<00:08:15.600> balance<00:08:15.960> right.<00:08:16.240> I<00:08:16.280> think<00:08:16.520> the<00:08:16.600> skills<00:08:17.200> around<00:08:17.840> creativity,<00:08:19.360> critical<00:08:19.840> thinking,<00:08:20.400> communications,<00:08:21.320> I<00:08:21.400> think<00:08:21.600> they're<00:08:21.760> going 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00:20:09.920 --> 00:20:14.960 Uh,<00:20:10.440> uh,<00:20:10.760> right<00:20:11.040> from<00:20:11.280> right<00:20:11.480> from<00:20:11.600> day<00:20:11.760> one<00:20:12.440> uh,<00:20:12.640> in<00:20:12.760> my<00:20:12.960> in<00:20:13.080> my<00:20:13.160> first<00:20:13.440> job. 00:20:14.960 --> 00:20:17.560 Brendan,<00:20:15.240> thank<00:20:15.440> you<00:20:15.520> so<00:20:15.720> much<00:20:16.200> for<00:20:16.400> coming<00:20:16.680> on<00:20:16.760> the<00:20:16.840> show. 00:20:17.560 --> 00:20:21.440 Uh,<00:20:17.680> what<00:20:17.840> an<00:20:17.920> incredible<00:20:18.400> company<00:20:18.800> you've<00:20:19.000> built.<00:20:19.400> Let's<00:20:19.600> keep<00:20:19.800> in<00:20:19.880> touch<00:20:20.320> and<00:20:20.440> have<00:20:20.600> you<00:20:20.680> back<00:20:21.000> on. 00:20:21.440 --> 00:20:23.880 It<00:20:21.520> means<00:20:21.760> a<00:20:21.800> lot<00:20:21.920> to<00:20:22.000> have<00:20:22.120> you.<00:20:22.200> Thank<00:20:22.400> you<00:20:22.480> so<00:20:22.560> much.<00:20:23.360> Thanks,<00:20:23.600> Len. 00:20:23.880 --> 00:20:28.720 Appreciate<00:20:24.760> the<00:20:24.840> time<00:20:25.200> and<00:20:25.680> uh,<00:20:25.720> great<00:20:26.280> to<00:20:26.320> be<00:20:26.400> on<00:20:26.480> your<00:20:26.560> show<00:20:26.720> today. ``` ### Terrapin Station Entertainment CEO, Jonathan Shank: Why authentic creativity still wins URL: https://www.ceo.com/episodes/terrapin-station-entertainment-ceo-jonathan-shank-why-authentic-creativity-still-wins/ Last updated: 2026-08-23T18:32:30.000Z # Jonathan Shank started in the bathrooms of the House of Blues Jonathan Shank's first job in the music business was hanging flyers in the bathrooms of the House of Blues New Orleans. The club had just opened. It was 1994, and that year's lineup included Bob Dylan, Eric Clapton, Aerosmith, Bill Monroe, the Neville Brothers, Dr. John, and the Dirty Dozen Brass Band. "It all sounds very unglamorous," Shank told CEO.com. "But in between those things, I attended almost all of the soundchecks and got to observe the entire process: load-in, soundcheck, show execution, what was the venue's responsibility versus the artist's responsibility." Shank now runs [Terrapin Station Entertainment](https://terrapinent.com/?ref=ceo.com), a Los Angeles-based division of Sony Music Entertainment that will produce around 225 shows this year. His career contains a swerve almost nobody else in the business can claim. He spent five years managing Mickey Hart, drummer of the Grateful Dead, work that [won him a Grammy in 2009](https://shorefire.com/roster/jonathan-shank/bio?ref=ceo.com) for the Global Drum Project album. He also produces Peppa Pig Live! The route between those two points started with an internship for the record producer Kim Fowley, which mostly involved listening to Fowley work the phones. When Shank left New Orleans for Los Angeles, Fowley sent him off with a stack of his own business cards. On the back of each one he had written, "Hire this guy." The plan was for Shank to hand one over at job interviews. Shank never used them. He got hired anyway, landing in the agency business and booking classic rock acts: the Marshall Tucker Band, Dave Mason, Robbie Krieger and John Densmore of The Doors, Dave Davies of The Kinks, Jefferson Starship. He booked fairs, festivals, clubs, theaters, amphitheaters, arenas, and once, Marshall Tucker at the Super Bowl in Tampa Bay. Then came management. War, Isaac Hayes, LFO, and eventually Particle, an instrumental electronic band out of Los Angeles that played Coachella, Bonnaroo, and 10,000 Lakes within two years of signing with him. One year, they did 170 shows. Stints with Irving Azoff and [a decade at Red Light Management](https://news.pollstar.com/2020/09/08/qs-with-jonathan-shank-artist-manager-keeps-on-truckin-with-his-own-terrapin-station-entertainment-2/?ref=ceo.com) followed, with a client list that ran from Eve and Panic! at the Disco to Smashing Pumpkins and Victoria Justice. Hart was the client who left the deepest mark. Terrapin Station is a Grateful Dead album from 1977, and the debt goes past the name. In [a guest essay for Pollstar](https://news.pollstar.com/2023/07/14/guest-post-a-rare-and-different-tune-why-the-grateful-deads-legacy-matters/?ref=ceo.com), Shank argued that the band helped spawn what the industry now calls direct-to-consumer ticketing through its mail-order ticket service, and that tape-trading Deadheads were "at the forefront of what would become the seeds of social media." Terrapin Station Entertainment launched during the pandemic to license intellectual property and turn it into live stage productions, mostly for preschoolers and their parents. Franchises like Disney Junior Dance Party On Tour and Peppa Pig Live! have [grossed more than $80 million at the box office](https://shorefire.com/roster/jonathan-shank/bio?ref=ceo.com). In the summer of 2025, the company produced [The Heart of Town](https://shorefire.com/releases/entry/grahame-lesh-friends-celebrated-grateful-deads-60th-anniversary?ref=ceo.com) with Dayglo Presents, a three-night concert series hosted by Grahame Lesh at San Francisco's Pier 48, marking the Grateful Dead's 60th anniversary. That September, Terrapin and TEG Life Like Touring launched the [North American debut of Gabby's Dollhouse Live! Presented by Walmart](https://www.prnewswire.com/news-releases/gabbys-dollhouse-live-presented-by-walmart-kicks-off-80-show-north-american-tour-in-long-beach-ca-302454410.html?ref=ceo.com) across more than 75 cities, then [added a second leg of more than 40 cities](https://shorefire.com/releases/entry/gabbys-dollhouse-live-presented-by-walmart-adds-40-north-american-shows?ref=ceo.com) beginning January 2026\. Shank also [joined the board of Music Will](https://shorefire.com/roster/jonathan-shank/bio?ref=ceo.com) and co-chaired its [2025 benefit honoring Wyclef Jean, Sara Bareilles, Jackson Browne, and Kristin Chenoweth](https://variety.com/2025/music/news/sara-bareilles-jackson-browne-kristen-chenoweth-music-will-benefit-honorees-1236322461/?ref=ceo.com). And he hosts The Jam, a podcast about the jam band scene, which he told CEO.com is about to launch its fourth season. "I always say Terrapin was born out of the idea of bringing together mythical, magical, and iconic characters and giving them one place to gather," he said. When Shank arrived in Los Angeles in the '90s, A&R was the hottest job in music. There were lines around the corner for openings. Those jobs barely exist now, he says, because anyone with a smartphone can discover artists, and by the time a label gets involved, a fan base and infrastructure are often already built. He thinks the audience got sharper in the process. People can tell what's authentic. He is similarly unbothered by AI. The business he entered has already survived the jump from vinyl to cassette to CD to streaming, and it survived Napster. "That's the one thing I don't think AI can truly do," he said. "Think outside the box." "I think the people behind the scenes are the real rock stars," he said when asked about leadership. "They're the ones empowering what happens onstage and helping create inspiration for millions, potentially billions, of people." Every CEO.com interview ends with the same question, because the chances one gives are just as important as the chances one takes. Who gave you a chance? Shank had a list ready. Sonny at the House of Blues. Fowley. Michael Gaiman. Ron Rainey. The late Peter Shields. Steve Jensen, who still manages Katy Perry. "I've had the opportunity to sit down with most of them, look them in the eye, and thank them personally," Shank said. "That's a really important and powerful thing to do once you realize how much someone impacted your life." ```chapters 00:00:00 Introduction and Guest Background 00:00:34 Early Career at House of Blues 00:01:17 First Job Responsibilities 00:01:58 Learning the Music Business 00:02:33 Interning with Kim Fowley 00:03:26 Moving to Los Angeles 00:03:49 Representing Classic Rock Bands 00:04:10 Working on Jazz is Dead 00:04:32 Managing Second-Generation Rock Stars 00:05:25 Managing Particle and Festival Success 00:06:57 Transition to Producing Shows 00:07:50 Founding Terrapin Station Entertainment 00:09:07 Changes in the Music Industry 00:11:01 Impact of Technology and AI 00:11:55 Bob Dylan at House of Blues 00:14:26 Leadership and Company Growth 00:17:12 Impact of AI on the Industry 00:19:42 Typical Day in the Life 00:21:23 Promoting the Podcast "The Jam" 00:22:33 Acknowledging Mentors and Supporters 00:23:55 Closing Remarks ``` ```vtt WEBVTT 00:00:00.000 --> 00:00:02.200 Jonathan,<00:00:00.680> thank<00:00:00.800> you<00:00:00.920> so<00:00:01.000> much<00:00:01.200> for<00:00:01.320> coming<00:00:01.600> on<00:00:01.720> the<00:00:01.800> show. 00:00:02.200 --> 00:00:07.560 What<00:00:02.400> an<00:00:02.520> honor<00:00:02.720> to<00:00:02.840> have<00:00:03.160> you.<00:00:03.400> You<00:00:03.560> are<00:00:03.680> the<00:00:03.880> founder<00:00:04.320> and<00:00:04.480> CEO<00:00:04.960> of<00:00:05.120> Terrapin<00:00:05.760> Station<00:00:06.280> Entertainment. 00:00:07.560 --> 00:00:11.920 Prior<00:00:07.880> to<00:00:07.960> that,<00:00:08.280> you<00:00:08.400> were<00:00:08.640> with<00:00:08.840> the<00:00:08.960> House<00:00:09.280> of<00:00:09.440> Blues<00:00:09.920> in<00:00:10.040> New<00:00:10.280> Orleans,<00:00:10.960> an<00:00:11.080> iconic<00:00:11.560> venue. 00:00:11.920 --> 00:00:14.240 You've<00:00:12.200> done<00:00:12.360> a<00:00:12.440> lot<00:00:12.640> of<00:00:12.760> like<00:00:13.000> incredible<00:00:13.440> things. 00:00:14.240 --> 00:00:17.680 Tell<00:00:14.520> us,<00:00:15.240> uh<00:00:15.320> you<00:00:15.440> know,<00:00:15.720> what<00:00:15.960> is<00:00:16.200> Terrapin<00:00:16.600> Station<00:00:16.960> Entertainment? 00:00:17.680 --> 00:00:22.120 How<00:00:17.760> did<00:00:17.880> you<00:00:17.960> become<00:00:18.200> founder<00:00:18.520> and<00:00:18.640> CEO?<00:00:19.080> Give<00:00:19.320> us<00:00:19.440> your<00:00:19.760> Give<00:00:19.920> us<00:00:20.040> your<00:00:20.160> story,<00:00:20.560> man. 00:00:22.120 --> 00:00:28.040 All<00:00:22.424> right.<00:00:22.729> Well,<00:00:23.033> uh<00:00:23.338> you<00:00:23.642> know,<00:00:23.947> I<00:00:24.251> will<00:00:24.556> give<00:00:24.860> you<00:00:25.164> the<00:00:25.469> uh<00:00:25.773> the<00:00:26.078> Cliff<00:00:26.382> Notes<00:00:26.687> version,<00:00:26.991> so<00:00:27.296> to<00:00:27.600> speak. 00:00:28.040 --> 00:00:32.840 So,<00:00:29.280> thank<00:00:29.600> you<00:00:29.680> 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2,000<00:05:59.640> seat 00:05:59.880 --> 00:06:02.120 clubs<00:06:00.880> around<00:06:01.560> the<00:06:01.640> country. 00:06:02.120 --> 00:06:06.120 We<00:06:02.200> did<00:06:02.360> 170<00:06:03.880> shows<00:06:04.440> in<00:06:04.760> 1<00:06:05.000> year. 00:06:06.120 --> 00:06:12.680 Um<00:06:06.606> [laughter]<00:06:07.092> Oh,<00:06:07.578> wow.<00:06:08.065> And<00:06:08.551> um<00:06:09.037> they<00:06:09.523> had<00:06:10.009> an<00:06:10.495> amazing<00:06:10.982> run<00:06:11.468> at<00:06:11.954> that<00:06:12.440> time. 00:06:12.680 --> 00:06:16.040 Actually<00:06:13.000> played<00:06:13.600> three<00:06:13.920> of<00:06:14.000> the<00:06:14.120> first<00:06:14.440> four<00:06:14.680> Bonnaroo's. 00:06:16.040 --> 00:06:24.360 And<00:06:17.720> uh<00:06:17.800> really<00:06:18.360> at<00:06:18.600> the<00:06:19.560> at<00:06:19.800> the<00:06:20.680> dawn<00:06:21.080> of<00:06:21.200> Bonnaroo,<00:06:21.720> because<00:06:22.080> it<00:06:22.200> was<00:06:22.520> the<00:06:22.640> first<00:06:23.800> uh<00:06:24.040> first 00:06:24.360 --> 00:06:31.080 iterations<00:06:24.960> of<00:06:25.040> that<00:06:25.280> festival.<00:06:25.840> And<00:06:26.400> that<00:06:26.600> was<00:06:26.800> really<00:06:27.040> impactful<00:06:27.600> in<00:06:27.680> terms<00:06:28.000> of<00:06:28.120> seeing<00:06:28.960> artist<00:06:29.280> development,<00:06:29.880> etc. 00:06:31.080 --> 00:06:39.440 And<00:06:31.400> then,<00:06:32.000> you<00:06:32.120> know,<00:06:32.280> I<00:06:32.360> had<00:06:32.600> management<00:06:33.200> jobs<00:06:33.919> uh<00:06:34.080> with<00:06:34.840> uh<00:06:34.919> Irving<00:06:35.240> Azoff<00:06:35.760> and<00:06:35.960> and<00:06:36.120> Red<00:06:36.360> Light<00:06:36.680> and<00:06:37.000> and<00:06:37.240> did<00:06:37.760> both<00:06:38.000> day-to-day<00:06:38.720> and<00:06:39.120> direct 00:06:39.440 --> 00:06:48.960 management<00:06:40.120> for<00:06:41.120> um<00:06:42.440> everybody<00:06:42.919> 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conferences. 00:21:11.080 --> 00:21:18.800 I<00:21:11.160> do<00:21:11.360> a<00:21:11.400> lot<00:21:11.560> of<00:21:11.640> public<00:21:11.960> speaking,<00:21:13.480> um,<00:21:13.600> at<00:21:14.000> at<00:21:14.280> colleges<00:21:15.040> and<00:21:15.160> universities<00:21:15.960> at<00:21:16.360> various<00:21:16.720> music<00:21:17.000> business<00:21:17.360> programs. 00:21:18.800 --> 00:21:21.240 Um,<00:21:18.960> have<00:21:19.120> a<00:21:19.200> podcast<00:21:20.280> as<00:21:20.560> well. 00:21:21.240 --> 00:21:26.840 So,<00:21:21.560> fully,<00:21:22.480> uh,<00:21:22.840> support<00:21:23.320> and<00:21:23.440> respect<00:21:23.920> what<00:21:24.040> you're<00:21:24.200> doing,<00:21:24.680> you<00:21:24.760> know,<00:21:24.880> and<00:21:25.000> that's<00:21:25.080> Yeah,<00:21:25.120> tell<00:21:25.280> us<00:21:25.400> about<00:21:25.840> promote<00:21:26.160> your<00:21:26.280> podcast. 00:21:26.840 --> 00:21:31.720 Let's<00:21:27.040> let's<00:21:27.200> 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00:23:55.560 down<00:23:47.440> with<00:23:47.600> most<00:23:47.880> of<00:23:47.960> them<00:23:48.160> and<00:23:48.320> look<00:23:48.480> them<00:23:48.640> in<00:23:48.760> the<00:23:48.960> eye<00:23:49.160> and<00:23:49.520> say<00:23:49.720> thank<00:23:50.080> you<00:23:50.360> and<00:23:51.040> and<00:23:51.240> actually<00:23:52.240> pass<00:23:52.560> on<00:23:52.720> that<00:23:52.880> gratitude<00:23:53.480> a<00:23:53.520> bit<00:23:53.840> and,<00:23:54.440> um,<00:23:55.000> uh,<00:23:55.200> you<00:23:55.320> know, 00:23:55.560 --> 00:24:02.880 which<00:23:55.760> I<00:23:55.840> felt,<00:23:56.760> you<00:23:57.000> know,<00:23:57.120> once<00:23:57.400> you<00:23:57.520> come<00:23:57.680> to<00:23:57.760> that<00:23:57.920> self-realization<00:23:58.760> is<00:23:58.920> a<00:23:58.960> really<00:23:59.880> important<00:24:00.440> thing<00:24:00.600> to<00:24:00.720> do<00:24:00.920> and<00:24:01.120> powerful<00:24:01.600> thing<00:24:01.760> to<00:24:01.840> do. 00:24:02.880 --> 00:24:08.400 Yeah.<00:24:03.720> Uh,<00:24:03.800> that's<00:24:04.040> incredible.<00:24:04.440> Jonathan,<00:24:04.840> thank<00:24:05.000> you<00:24:05.080> so<00:24:05.240> much<00:24:06.080> for<00:24:06.200> joining<00:24:06.560> us,<00:24:07.080> uh,<00:24:07.320> for<00:24:07.520> being<00:24:07.720> a<00:24:07.760> part<00:24:08.000> of<00:24:08.080> this. 00:24:08.400 --> 00:24:11.120 Congratulations<00:24:09.200> everything<00:24:09.520> you've<00:24:09.640> done.<00:24:09.960> What<00:24:10.080> an<00:24:10.160> incredible<00:24:10.600> career. 00:24:11.120 --> 00:24:13.480 Keep<00:24:11.400> going,<00:24:11.680> man.<00:24:12.000> So<00:24:12.280> awesome.<00:24:13.080> Thank<00:24:13.400> you. 00:24:13.480 --> 00:24:18.800 Such<00:24:13.720> a<00:24:13.760> pleasure<00:24:14.080> to<00:24:14.160> be<00:24:14.320> here,<00:24:14.600> an<00:24:14.720> honor<00:24:15.160> and,<00:24:15.640> uh,<00:24:15.720> I<00:24:15.800> look<00:24:16.040> forward<00:24:16.200> to<00:24:16.280> see<00:24:16.440> you<00:24:16.520> down<00:24:16.720> the<00:24:16.800> road. ``` ### WorkMoney Founder & CEO Carrie Joy Grimes: Why collective power matters in the modern economy URL: https://www.ceo.com/episodes/workmoney-founder-ceo-carrie-joy-grimes-why-collective-power-matters-in-the-modern-economy/ Last updated: 2026-08-24T18:23:32.000Z # The union organizer who wants to negotiate your cable bill Carrie Joy Grimes bought her house 15 years ago. She couldn't save 20 percent down, so she paid mortgage insurance to get in. She says she couldn't afford that same house today. "I feel like I was part of the last wave of people who could still get in," Grimes said on the CEO.com Podcast. Grimes is the founder and CEO of [WorkMoney](https://workmoney.org/about-us?ref=ceo.com), a nonprofit that now counts more than 9 million members. Before that she was National Organizing Director at the Service Employees International Union, where she [helped launch the Fight for $15](https://www.emersoncollective.com/persons/carrie-joy-grimes-dd2024?ref=ceo.com), the campaign to raise the minimum wage. "WorkMoney is a nonprofit, kind of like the AARP," she said. "You know how the AARP helps folks navigate aging? Well, we help folks navigate money. We don't send you an envelope when you turn 50 that makes you feel old, but we do have coupons and discounts." It started during COVID, when Grimes built a simple website explaining stimulus checks and how relief programs worked. It exploded. People needed help understanding money, and a nonprofit with no product to sell was something they could trust. Today WorkMoney has about 100 employees, all remote, and Grimes says its content draws over a billion views a year. The numbers behind her argument are public. The Federal Reserve's [2025 household survey](https://www.federalreserve.gov/newsevents/pressreleases/other20260513a.htm) found that 63 percent of American adults said they would cover a $400 emergency expense using cash or its equivalent, unchanged from the year before. Prices remained the most common financial concern, cited by 91 percent. A [RAND working paper](https://www.rand.org/pubs/working%5Fpapers/WRA516-1.html?ref=ceo.com) Grimes cites often puts a number on the longer trend. Had income growth since 1975 stayed as equitable as it was in the first two post-war decades, aggregate income for Americans below the 90th percentile would have been $2.5 trillion higher in 2018 alone, or 67 percent more than they actually earned. Across the full period, the gap totals $47 trillion. "Over the last 50 years, it's gotten harder, not easier, for people to succeed financially," Grimes said. "That's not the promise of the American Dream. The promise was that if you worked hard, you'd have a reasonable shot at financial security and success. I don't think that feels reasonable anymore." She has no quarrel with wealth. "I'm all for people getting rich. Go build companies, make money, create value. But we can do that without extracting so much from everyone else. When people have enough security to take risks, build companies, and try new ideas, markets are stronger. When fewer companies control more of what happens, capitalism becomes brittle." So she is doing what organizers do. She is counting heads. WorkMoney already negotiates discounts on prescriptions, insurance, and phone plans. Its next product negotiates directly with cable, internet, and cell phone companies on a member's behalf, armed with what the organization knows about the retention deals those companies offer customers who threaten to cancel. Grimes wants to aim it higher from there. "I would love to start arguing with health insurance companies on behalf of members," she said. "As an individual, it's hard to fight giant corporations. But with 50 million people behind you? That changes the conversation." The nonprofit structure was deliberate. "During COVID, it mattered that people trusted the information they were getting. I wanted people to know the mission was the point." A for-profit subsidiary will build products and services. The nonprofit owns it. The bill negotiation service will pair humans with AI agents, and Grimes has few illusions about what is coming. Her daughter, a college freshman, asks what she should study to get a good job. Grimes admits she no longer knows. "AI is coming whether people like it or not," she said. "The important question is how we shape it." Her first book, [The Joy of Money](https://thejoyofmoney.com/?ref=ceo.com), came out from Harper Business on May 19\. Its premise is that two things are true at once: you are responsible for your money choices, and the system makes it too hard to get ahead. Every CEO.com Podcast conversation ends with the same question: who gave you a chance that led you to where you are? Grimes named Reid Hoffman, whose book Blitzscaling convinced her that WorkMoney could be big, and whose team later invested an early $50,000\. But her first answer was a woman in the bursar's office at Northern Illinois University who picked up the phone one day and took the time to explain college finances to a confused kid. Grimes never learned her name. ```chapters 00:00:00 Introduction and Guest Welcome 00:00:10 Founding of WorkMoney 00:00:25 Mission and Vision of WorkMoney 00:01:14 Economic Inequality and Wealth Transfer 00:02:04 Challenges for the Next Generation 00:02:41 WorkMoney's Membership and Scale 00:03:22 Negotiating for Members' Benefits 00:03:33 Impact of AI on Jobs and Economy 00:04:11 Personal Financial Struggles and Housing Market 00:05:03 Economic Challenges Over the Decades 00:06:18 Capitalism and Wealth Distribution 00:07:00 Rand Corporation Study on Income 00:08:37 WorkMoney's Response to COVID-19 00:09:41 Empowering Individuals Through Collective Action 00:10:53 Personal Definitions of a Good Life 00:12:06 Nonprofit vs. For-Profit Structure 00:13:23 Growth and Member Engagement 00:14:52 Remote Work and Organizational Culture 00:16:35 Advantages of Remote Work 00:16:55 A Day in the Life of the CEO 00:19:33 How to Become a WorkMoney Member 00:20:04 Negotiating on Behalf of Members 00:22:05 Future Plans for Negotiation Services 00:24:26 Revenue Model and Philanthropy 00:27:09 Role of AI in WorkMoney 00:28:28 Reading Recommendations 00:31:46 Reflecting on Who Gave a Chance 00:34:25 Closing Remarks and Gratitude ``` ```vtt WEBVTT 00:00:00.000 --> 00:00:02.920 Eri,<00:00:00.760> welcome<00:00:01.040> to<00:00:01.080> the<00:00:01.160> show.<00:00:01.480> Thank<00:00:01.720> you<00:00:01.760> so<00:00:01.880> much<00:00:02.040> for<00:00:02.200> coming<00:00:02.560> on. 00:00:02.920 --> 00:00:06.440 What<00:00:03.140> an<00:00:03.360> honor<00:00:03.580> to<00:00:03.800> have<00:00:04.020> you.<00:00:04.240> You're<00:00:04.460> the<00:00:04.680> founder<00:00:04.900> and<00:00:05.120> CEO<00:00:05.340> of<00:00:05.560> WorkMoney. 00:00:06.440 --> 00:00:08.960 I<00:00:06.480> believe<00:00:06.720> you<00:00:06.800> started<00:00:07.080> this<00:00:07.280> in<00:00:07.400> 2020,<00:00:08.000> is<00:00:08.120> that<00:00:08.280> right? 00:00:08.960 --> 00:00:16.520 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--> 00:02:13.040 generation<00:02:06.560> can't<00:02:08.520> you<00:02:08.600> know,<00:02:09.119> fulfill<00:02:09.840> the<00:02:09.960> American<00:02:10.440> dream<00:02:10.720> the<00:02:10.840> way<00:02:11.000> it<00:02:11.160> was<00:02:11.360> pitched<00:02:11.680> to<00:02:11.880> us. 00:02:13.040 --> 00:02:20.120 Which<00:02:13.200> is<00:02:13.320> you<00:02:13.440> could<00:02:13.840> afford<00:02:14.240> a<00:02:14.320> home.<00:02:15.120> You<00:02:15.280> could<00:02:16.040> you<00:02:16.160> know,<00:02:16.320> be<00:02:16.520> like<00:02:16.880> a<00:02:17.520> high<00:02:17.720> school<00:02:18.080> school<00:02:18.440> teacher<00:02:19.120> and<00:02:19.320> still<00:02:19.560> make<00:02:19.720> a<00:02:19.800> living. 00:02:20.120 --> 00:02:27.400 I<00:02:20.160> mean<00:02:20.280> that's<00:02:20.440> all<00:02:20.600> that's<00:02:20.840> a<00:02:20.880> bad<00:02:21.040> example<00:02:21.440> cuz<00:02:21.600> they<00:02:21.680> don't<00:02:21.840> 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to<00:02:36.560> understand<00:02:37.160> like<00:02:37.320> what<00:02:37.520> it<00:02:37.640> is. 00:02:37.840 --> 00:02:40.440 So<00:02:38.840> you<00:02:38.920> have<00:02:39.000> 9<00:02:39.240> million<00:02:39.520> members. 00:02:40.440 --> 00:02:43.680 We<00:02:40.520> do.<00:02:41.640> Which<00:02:41.880> is<00:02:42.840> oh<00:02:42.920> my<00:02:43.080> goodness. 00:02:43.680 --> 00:02:46.840 Congratulations.<00:02:44.520> That's<00:02:44.840> incredible.<00:02:45.640> That's<00:02:45.880> so<00:02:46.080> hard<00:02:46.320> to<00:02:46.400> do. 00:02:46.840 --> 00:02:49.480 I<00:02:46.920> don't<00:02:47.320> you<00:02:47.440> know,<00:02:47.680> I<00:02:47.760> can't<00:02:48.000> even<00:02:48.680> that's<00:02:48.880> hard<00:02:49.080> to<00:02:49.160> fathom. 00:02:49.480 --> 00:02:53.240 That's<00:02:49.720> wonderful<00:02:50.280> and<00:02:50.360> amazing.<00:02:51.840> Um<00:02:52.320> I<00:02:52.400> live<00:02:52.600> in<00:02:52.680> the<00:02:52.760> state<00:02:52.959> of<00:02:53.040> Utah. 00:02:53.240 --> 00:02:57.240 There's<00:02:53.400> 3<00:02:53.640> million<00:02:53.920> people<00:02:54.200> in<00:02:54.240> the<00:02:54.320> entire<00:02:54.600> state.<00:02:55.160> So<00:02:55.240> it's<00:02:55.320> nice<00:02:55.440> to<00:02:55.520> get<00:02:55.680> people<00:02:55.880> like<00:02:56.040> a<00:02:56.720> Yeah. 00:02:57.240 --> 00:02:59.472 sense<00:02:57.440> for<00:02:57.520> like<00:02:57.680> what<00:02:57.840> 9<00:02:58.160> million<00:02:58.880> is. 00:02:59.472 --> 00:03:02.560 [laughter]<00:02:59.560> Yeah,<00:02:59.680> that's<00:03:00.120> that's<00:03:00.320> a<00:03:00.400> lot<00:03:00.640> of<00:03:00.720> people.<00:03:01.040> So<00:03:01.160> there<00:03:01.360> yeah. 00:03:02.560 --> 00:03:10.200 Um<00:03:02.600> so<00:03:02.880> so<00:03:03.120> well<00:03:03.360> done<00:03:03.600> there.<00:03:04.720> And<00:03:05.000> give<00:03:05.160> me<00:03:05.320> give<00:03:05.480> us<00:03:05.600> 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like<00:05:47.080> these<00:05:47.480> like<00:05:47.680> the<00:05:47.880> numbers 00:05:48.480 --> 00:05:56.680 that<00:05:48.600> are<00:05:48.680> coming<00:05:48.960> out<00:05:49.080> like<00:05:49.320> Elon<00:05:49.600> Musk<00:05:49.840> will<00:05:49.960> soon<00:05:50.400> be<00:05:50.840> not<00:05:51.000> to<00:05:51.080> pick<00:05:51.240> on<00:05:51.360> him,<00:05:51.560> but<00:05:51.680> let's<00:05:51.880> do<00:05:52.040> it<00:05:52.920> cuz<00:05:52.960> he's<00:05:53.120> probably<00:05:53.560> used<00:05:53.800> to<00:05:53.960> it<00:05:54.320> and<00:05:55.000> whatever,<00:05:55.560> you<00:05:55.680> know,<00:05:55.960> but 00:05:56.680 --> 00:06:00.520 uh<00:05:57.640> Elon<00:05:57.840> Musk<00:05:58.040> is<00:05:58.160> about<00:05:58.440> to<00:05:58.520> be<00:05:58.600> the<00:05:58.720> first<00:05:59.080> trillionaire. 00:06:00.520 --> 00:06:06.160 Mhm.<00:06:01.520> You<00:06:01.680> know<00:06:01.760> what<00:06:01.880> I<00:06:01.920> mean?<00:06:02.320> Isn't<00:06:02.520> that<00:06:02.640> a<00:06:02.720> such<00:06:03.000> an<00:06:03.080> interesting<00:06:04.520> contra-<00:06:05.600> He<00:06:05.680> should<00:06:05.920> be<00:06:06.040> it. 00:06:06.160 --> 00:06:08.480 Like<00:06:06.360> I<00:06:06.400> have<00:06:06.560> nothing<00:06:06.880> against<00:06:07.200> trillionaires.<00:06:07.520> I<00:06:07.560> have<00:06:07.640> nothing<00:06:07.800> against<00:06:08.040> billionaires. 00:06:08.480 --> 00:06:16.960 Like<00:06:08.680> great,<00:06:09.080> that's<00:06:09.360> great.<00:06:10.040> What's<00:06:10.240> fascinating<00:06:10.720> is<00:06:10.800> we<00:06:10.960> live<00:06:11.120> in<00:06:11.240> a<00:06:11.280> society<00:06:12.480> where<00:06:13.800> 80<00:06:14.400> 85%<00:06:16.280> couldn't<00:06:16.600> afford 00:06:16.960 --> 00:06:19.960 a<00:06:17.000> $500<00:06:17.760> emergency.<00:06:18.960> Yeah,<00:06:19.080> that's<00:06:19.280> something<00:06:19.440> I<00:06:19.480> talked<00:06:19.640> about. 00:06:19.960 --> 00:06:24.440 I<00:06:20.000> mean,<00:06:20.200> capitalism<00:06:21.080> works<00:06:21.520> best<00:06:22.200> when<00:06:22.400> people<00:06:22.760> can<00:06:22.919> participate<00:06:23.520> in<00:06:23.640> it. 00:06:24.440 --> 00:06:31.200 When<00:06:24.840> when<00:06:25.120> when<00:06:25.320> folks<00:06:25.680> can<00:06:25.880> take<00:06:26.120> their<00:06:26.320> ideas<00:06:26.800> and<00:06:26.919> be<00:06:27.080> entrepreneurial<00:06:28.040> and<00:06:28.200> figure<00:06:28.520> out<00:06:28.640> how<00:06:28.720> they<00:06:28.880> get<00:06:29.080> the<00:06:29.160> resources<00:06:29.680> together<00:06:30.000> to<00:06:30.120> launch<00:06:30.440> new<00:06:30.560> businesses 00:06:31.200 --> 00:06:38.280 to<00:06:31.320> try<00:06:31.600> things.<00:06:32.560> And<00:06:32.760> when<00:06:33.000> fewer<00:06:33.480> companies<00:06:34.560> control<00:06:35.040> more<00:06:35.360> of<00:06:35.480> what<00:06:35.680> happens,<00:06:36.800> it's<00:06:37.040> not<00:06:37.320> as<00:06:37.440> good<00:06:37.600> for<00:06:37.720> capitalism. 00:06:38.280 --> 00:06:41.800 It<00:06:38.360> makes<00:06:38.560> capitalism<00:06:39.200> brittle.<00:06:39.840> It<00:06:40.080> it<00:06:40.280> puts<00:06:40.600> it<00:06:40.680> at<00:06:40.800> risk. 00:06:41.800 --> 00:06:47.840 And<00:06:42.080> I<00:06:42.320> am<00:06:42.640> a<00:06:42.760> huge<00:06:43.360> fan<00:06:44.160> of<00:06:44.360> how<00:06:44.560> markets<00:06:46.040> entrepreneurship<00:06:46.480> can<00:06:46.600> solve<00:06:46.880> problems. 00:06:47.840 --> 00:06:50.240 And<00:06:48.000> that's<00:06:48.400> to<00:06:48.520> me<00:06:48.840> like<00:06:49.080> when<00:06:49.200> this<00:06:49.400> country<00:06:49.720> is<00:06:49.840> so<00:06:50.000> great. 00:06:50.240 --> 00:06:57.240 But<00:06:50.360> people<00:06:50.600> have<00:06:50.720> enough<00:06:51.120> money<00:06:52.120> when<00:06:52.240> the<00:06:52.360> economy<00:06:53.040> is<00:06:53.280> working<00:06:53.600> for<00:06:53.720> enough<00:06:54.000> of<00:06:54.120> us<00:06:54.240> to<00:06:54.320> participate<00:06:54.760> in<00:06:54.880> it,<00:06:55.040> you<00:06:55.120> get<00:06:55.280> better<00:06:55.520> ideas,<00:06:56.080> you<00:06:56.160> get<00:06:56.320> better<00:06:56.560> technological 00:06:57.240 --> 00:07:04.400 advancements.<00:06:58.440> You<00:06:58.520> know,<00:06:58.640> the<00:06:58.800> purpose<00:06:59.560> of<00:07:00.480> of<00:07:00.680> our<00:07:00.840> country<00:07:01.240> is<00:07:01.880> is<00:07:02.040> for<00:07:02.240> all<00:07:02.520> is<00:07:02.760> life,<00:07:03.040> liberty,<00:07:03.280> and<00:07:03.360> the<00:07:03.440> pursuit<00:07:03.720> of<00:07:03.800> happiness. 00:07:04.400 --> 00:07:06.520 It's<00:07:04.640> it's<00:07:04.840> the<00:07:04.919> ability<00:07:05.240> for<00:07:05.440> the<00:07:05.600> many<00:07:05.919> to<00:07:06.040> thrive. 00:07:06.520 --> 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like<00:07:21.360> it's<00:07:22.040> it's<00:07:22.200> getting<00:07:22.440> harder. 00:07:22.800 --> 00:07:25.000 It<00:07:23.000> is.<00:07:23.480> But<00:07:23.600> I<00:07:23.680> think<00:07:23.840> there's<00:07:24.000> a<00:07:24.040> real<00:07:24.280> way<00:07:24.520> out<00:07:24.720> of<00:07:24.840> it. 00:07:25.000 --> 00:07:31.280 That's<00:07:25.215> part<00:07:25.430> of<00:07:25.644> why<00:07:25.859> I<00:07:26.074> built<00:07:26.289> WorkMoney.<00:07:26.504> But<00:07:26.719> before<00:07:26.933> I<00:07:27.148> talk<00:07:27.363> about<00:07:27.578> like<00:07:27.793> kind<00:07:28.007> of<00:07:28.222> why<00:07:28.437> and<00:07:28.652> how<00:07:28.867> I<00:07:29.081> built<00:07:29.296> WorkMoney,<00:07:29.511> let<00:07:29.726> me<00:07:29.941> just<00:07:30.156> say<00:07:30.370> like<00:07:30.585> the<00:07:30.800> numbers 00:07:31.280 --> 00:07:36.760 really<00:07:31.480> bear<00:07:31.640> this<00:07:31.880> out.<00:07:32.040> There's<00:07:32.200> this<00:07:32.440> really<00:07:32.840> interesting<00:07:33.360> study<00:07:33.720> by<00:07:33.880> the<00:07:34.040> RAND<00:07:34.400> Corporation<00:07:35.080> which<00:07:35.240> came<00:07:35.440> out<00:07:35.560> in<00:07:35.600> 2018. 00:07:36.760 --> 00:07:41.200 And<00:07:36.840> for<00:07:36.919> those<00:07:37.040> who<00:07:37.120> don't<00:07:37.240> know,<00:07:37.360> they're<00:07:37.480> like<00:07:37.720> a<00:07:38.200> they<00:07:38.760> specialize<00:07:39.200> in<00:07:39.280> defense<00:07:39.760> contracting<00:07:40.360> and<00:07:40.440> national<00:07:40.680> security. 00:07:41.200 --> 00:07:44.400 And<00:07:41.280> then<00:07:41.360> they<00:07:41.440> started<00:07:41.720> doing<00:07:41.919> some<00:07:42.040> other<00:07:42.200> kinds<00:07:42.520> of<00:07:42.600> things<00:07:42.960> just<00:07:43.120> to<00:07:43.160> talk<00:07:43.400> about<00:07:43.680> national<00:07:43.960> security. 00:07:44.400 --> 00:07:53.080 So,<00:07:44.480> 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it's<00:34:31.879> a<00:34:31.960> really<00:34:33.000> excellent<00:34:33.520> place<00:34:34.000> to<00:34:34.440> to<00:34:34.520> like<00:34:34.760> learn<00:34:35.120> and<00:34:35.240> listen<00:34:35.760> and<00:34:36.320> kind<00:34:36.520> of<00:34:36.600> get<00:34:36.800> my<00:34:36.960> game<00:34:37.280> up<00:34:37.560> and<00:34:37.919> helps<00:34:38.200> me<00:34:38.320> think<00:34:38.639> differently<00:34:38.960> about<00:34:39.120> the<00:34:39.200> future<00:34:39.520> of 00:34:39.600 --> 00:34:42.159 my<00:34:39.720> organization.<00:34:40.440> So,<00:34:40.560> I<00:34:40.600> really<00:34:40.760> appreciate<00:34:41.200> what<00:34:41.320> you<00:34:41.440> do. 00:34:42.159 --> 00:34:45.879 Um<00:34:42.360> thank<00:34:42.639> you,<00:34:42.720> my<00:34:42.840> friend.<00:34:43.120> I<00:34:43.200> really<00:34:43.440> appreciate<00:34:43.879> it. ``` ### Honor Technology CEO, Seth Sternberg: Why technology should be “world good” URL: https://www.ceo.com/episodes/honor-technology-ceo-seth-sternberg-why-technology-should-be-world-good/ Last updated: 2026-08-24T18:35:25.000Z # Seth Sternberg doesn't build dancing pixels anymore Seth Sternberg has a rule for what deserves his time. He set it with his co-founders after they sold their first company. Only work on a hard problem. Only work on something where you can look a person in the eye and know you are making their life fundamentally better. Only work on something that reaches millions of people. "I think if you use that as the bar for what you want to work on, it's a very, very high bar," Sternberg said on the CEO.com Podcast. "Bluntly, I think a lot of the things happening today, if people had held themselves to that bar, society might be in a better place." Sternberg knows what it feels like to clear a lower bar. His first company, Meebo, brought instant messaging to the web and [sold to Google in 2012](https://techcrunch.com/2021/10/05/senior-care-startup-honor-secures-370m-in-debt-and-equity-reaches-unicorn-status/?ref=ceo.com). By any conventional measure it was a success. He does not describe it that way. "At some point I stopped caring about it because I kind of saw it as what I now call a dancing pixels company," he said. "It was fun. It was cute. But it wasn't fundamentally altering people's lives for the better." The problem that cleared his new bar found him. While at Google, Sternberg ran into a care issue with his mother. He started looking at how society cares for older adults and discovered that technology had mostly ignored them. The demographics made the stakes obvious. The [U.S. Census Bureau projects](https://www.census.gov/newsroom/press-releases/2018/cb18-41-population-projections.html?ref=ceo.com) that by 2034, Americans 65 and older will outnumber children under 18 for the first time in the nation's history. The over-80 population, Sternberg notes, is growing even faster. People are living longer and having fewer kids at the same time. "How are we going to take care of those people?" Sternberg said. "Technology has got to be part of the answer." Honor Technology, which Sternberg co-founded in 2014, sends Care Pros into the homes of older adults to help with the activities of daily living: getting food, getting dressed, taking medications, bathing. If a person cannot do two of those activities, they can no longer live alone. Honor's job is to keep that day as far away as possible. The industry Honor entered was massive and broken in a specific way. Sternberg sizes home care at $85 billion, spread across hundreds of thousands of participants worldwide, nearly all of them tiny. Nobody had ever scaled in-home care delivery. Sternberg believes Honor is the first to do it, and he credits an AI system the company started building a decade ago, long before the technology became fashionable. The proof came in 2021, when Honor [acquired Home Instead](https://www.homeinstead.com/news-and-media/honor-acquires-home-instead/?ref=ceo.com), the world's largest home care network, creating a combined organization with more than $2.1 billion in home care services revenue. Two months later, Honor [closed $370 million in equity and debt financing](https://www.honorcare.com/news/honor-tech-series-e-unicorn-home-care/?ref=ceo.com), valuing the company at over $1.25 billion. Today the Home Instead network supports more than 100,000 Care Pros delivering over [60 million hours of care annually](https://www.homeinstead.com/news-and-media/home-instead-recognized-on-newsweeks-americas-best-customer-service-list/?ref=ceo.com). The AI is not decoration. Honor uses it to match each client with the right Care Pro, to design jobs that keep Care Pros from quitting, and to predict three days in advance whether a Care Pro is likely to miss a shift so the client still gets care. "When your product requires demystifying really complicated things that involve a ton of nuance and personalization, that's where AI absolutely shines," Sternberg said. Sternberg has little patience for how his industry allocates its attention. He notes that tech media celebrates investors more than builders. "We celebrate the Midas List. We celebrate the asset allocators rather than the operators actually building things," he said. "Why are we celebrating them instead of the players actually on the field building companies?" His diagnosis of the cause is blunt: part profit motive, part power motive. His prescription is the same test he applies to himself. Is what you are building world good? Is it world neutral? Or is it actively destructive? Inside Honor, Sternberg runs the company on leadership principles drawn from 20 years of lessons, embedded in hiring, performance management, and decision-making. One cultural rule stands out: talk it out directly in the room. If something presented to 20 people seems wrong, waiting to raise it privately means 18 people walk away with the wrong impression. Honor does not wait. His own days break into four categories: team, communication, unexpected problems, and what he calls "kink the curve" activities, ideas that might alter the company's trajectory. "I have tons of those ideas," he said. "Most of them suck. I hand them to the team, and occasionally one of them is actually good." On when CEOs should speak publicly, Sternberg draws the line at expertise. He will talk about the ethics of AI. He will talk about immigration, a topic most CEOs avoid, because his business depends on a workforce that demographics say the country does not have. "We literally need more people to help care for an aging population that's going to outnumber the young very soon," he said. "That's not partisan. It's just reality." Outside his lane, he is comfortable saying he does not know enough to weigh in. What worries him most is not a business problem. It is the default demonization of the other side in American life. He no longer wants his kids watching political debates. "When I was a kid, you watched presidential debates to hear substantive discussions about policy and learn how the world worked," he said. "Now I wouldn't let my kids watch one unless I wanted them learning how to name-call and insult people." His answer is not despair. It is the same focus he preaches in company building. Every successful person, he argues, should be working on one focused project that pushes the world forward. "Sitting around saying the world is messed up and I can't do anything about it is bullshit," he said. "You can do something about it, but you have to put energy into it." At CEO.com, we believe the chances one gives are just as important as the chances one takes. For Sternberg, that chance came at IBM, his first job out of Yale. Eight months in, his bosses handed the 23-year-old financial analyst a small $5 million M&A deal. Sternberg restructured it into a $30 million deal, then waited for someone to take it away from him. His boss Bob Pemberton and Dave Johnson, who ran corporate development, refused. Negotiate it end to end, they told him. Just go do it. "Those two guys let me do something they absolutely should not have let me do at IBM in the early 2000s," Sternberg said. "But it also showed me what I was capable of." It is a fitting origin story for a man whose closing argument is about legacy. Every person, Sternberg points out, will eventually be two weeks away from dying. The money will not matter. The power will not matter. "What do you want your legacy to be?" he asked. "If your legacy is that you genuinely improved people's lives, I think that matters enormously." ```chapters 00:00:00 Introduction and Honor Technology Overview 00:01:00 Aging Population and Societal Challenges 00:01:53 How Honor Technology Helps Older Adults 00:03:01 Seth's Background and Motivation 00:04:06 Importance of Meaningful Work 00:05:00 Silicon Valley's Focus on Valuations Over Impact 00:07:01 AI's Role in Honor Technology 00:08:30 AI's Transformational Impact 00:10:07 Balancing AI's Benefits and Risks 00:10:27 Typical Day as a CEO 00:13:00 Maintaining Company Culture 00:15:22 Reading Habits and Recommendations 00:16:47 Audio vs. Physical Reading 00:17:24 CEO's Role in Addressing Societal Issues 00:20:01 Encouraging Positive World Change 00:21:41 Mental Health Crisis and Societal Division 00:25:16 Importance of Constructive Dialogue 00:26:09 Social Media's Impact on Society 00:28:04 Legacy and Positive Change 00:29:22 Final Question: Who Gave You a Chance? 00:31:04 Closing Remarks ``` ```vtt WEBVTT 00:00:00.000 --> 00:00:02.440 Chad,<00:00:00.240> thank<00:00:00.440> you<00:00:00.520> so<00:00:00.600> much<00:00:00.760> for<00:00:00.880> coming<00:00:01.080> on<00:00:01.160> the<00:00:01.240> show.<00:00:01.640> Honored<00:00:01.960> to<00:00:02.040> have<00:00:02.320> you. 00:00:02.440 --> 00:00:05.840 You're<00:00:02.560> the<00:00:02.680> co-founder<00:00:03.360> and<00:00:03.480> CEO<00:00:04.240> of<00:00:04.440> Honor<00:00:04.720> Technology. 00:00:05.840 --> 00:00:10.800 Now,<00:00:05.920> list<00:00:06.120> what<00:00:06.360> Honor<00:00:06.560> Technology<00:00:07.160> is.<00:00:08.080> Yeah,<00:00:08.280> so<00:00:08.600> we<00:00:08.800> help<00:00:09.040> older<00:00:09.320> adults<00:00:09.680> stay<00:00:09.880> in<00:00:09.960> their<00:00:10.080> homes<00:00:10.280> as<00:00:10.400> they<00:00:10.520> age. 00:00:10.800 --> 00:00:17.720 That's<00:00:10.920> what<00:00:11.000> we<00:00:11.120> do<00:00:11.240> today.<00:00:12.160> 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things.<00:01:13.480> So,<00:01:13.600> yeah,<00:01:13.960> like<00:01:14.320> the<00:01:14.480> stat<00:01:14.840> on<00:01:14.960> that<00:01:15.320> is<00:01:15.640> is<00:01:16.040> the<00:01:16.240> older<00:01:16.600> you<00:01:16.760> go,<00:01:17.920> the<00:01:18.200> faster<00:01:18.920> that<00:01:19.160> population<00:01:19.760> is<00:01:19.880> growing. 00:01:20.240 --> 00:01:26.680 So,<00:01:20.400> for<00:01:20.520> example,<00:01:20.920> the<00:01:21.280> over<00:01:21.720> 80<00:01:22.000> population<00:01:22.600> will<00:01:22.760> roughly<00:01:23.080> triple<00:01:24.080> where<00:01:24.240> the<00:01:24.400> over<00:01:24.600> 65<00:01:25.200> population<00:01:25.720> will<00:01:25.840> roughly<00:01:26.160> double. 00:01:26.680 --> 00:01:32.080 So,<00:01:26.760> people<00:01:27.040> are<00:01:27.120> living<00:01:27.400> longer.<00:01:28.440> Um,<00:01:28.800> at<00:01:28.920> the<00:01:29.040> same<00:01:29.400> time<00:01:29.680> though,<00:01:29.960> people<00:01:30.200> are<00:01:30.240> having<00:01:30.520> many<00:01:30.720> less<00:01:30.920> kids. 00:01:32.080 --> 00:01:40.320 Right?<00:01:32.480> So,<00:01:32.600> you've<00:01:32.760> both<00:01:33.000> got<00:01:33.560> this<00:01:33.840> like<00:01:34.200> big<00:01:34.600> wave<00:01:35.040> from<00:01:35.160> the<00:01:35.280> baby<00:01:35.640> boom<00:01:35.880> era<00:01:36.520> kind<00:01:36.680> of<00:01:36.920> aging<00:01:37.520> into<00:01:38.200> being<00:01:38.480> an<00:01:38.600> older<00:01:38.880> adult<00:01:39.280> who<00:01:39.520> will<00:01:39.800> end<00:01:39.960> up<00:01:40.080> needing 00:01:40.320 --> 00:01:49.000 some<00:01:40.480> kind<00:01:40.640> of<00:01:40.720> help.<00:01:41.800> But,<00:01:42.400> you<00:01:42.560> also<00:01:42.800> have<00:01:43.320> a<00:01:43.440> much<00:01:43.880> lower<00:01:44.160> replacement<00:01:44.800> rate<00:01:46.000> in<00:01:46.320> childbirth. 00:01:49.000 --> 00:01:53.080 And<00:01:49.160> so,<00:01:49.360> how<00:01:49.520> do<00:01:49.680> you<00:01:50.000> help?<00:01:50.440> Like,<00:01:50.640> give<00:01:50.760> us<00:01:50.880> a<00:01:50.960> sense<00:01:51.240> for<00:01:51.440> what<00:01:51.800> what<00:01:52.040> Honor<00:01:52.280> does. 00:01:53.080 --> 00:02:01.200 Yeah,<00:01:53.476> so<00:01:53.872> we,<00:01:54.267> um,<00:01:54.663> first<00:01:55.059> created<00:01:55.455> the<00:01:55.851> the<00:01:56.246> kind<00:01:56.642> of<00:01:57.038> system<00:01:57.434> that<00:01:57.829> can<00:01:58.225> actually<00:01:58.621> scale<00:01:59.017> in-home<00:01:59.413> care<00:01:59.808> for<00:02:00.204> older<00:02:00.600> adults. 00:02:01.200 --> 00:02:05.000 So,<00:02:01.520> what<00:02:01.680> that<00:02:01.880> is<00:02:02.040> is<00:02:02.240> there's<00:02:02.440> this<00:02:02.560> home<00:02:02.840> there's<00:02:03.000> this<00:02:03.160> industry<00:02:03.520> called<00:02:03.720> home<00:02:03.880> care. 00:02:05.000 --> 00:02:13.560 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an<00:02:19.160> activity<00:02:19.640> of<00:02:19.720> daily<00:02:20.000> living. 00:02:21.000 --> 00:02:28.440 And<00:02:21.080> if<00:02:21.200> you<00:02:21.600> can't<00:02:22.120> do<00:02:22.560> two<00:02:23.080> ADLs,<00:02:24.520> that's<00:02:25.000> the<00:02:25.160> point<00:02:25.520> at<00:02:25.640> which<00:02:25.959> you<00:02:26.080> actually<00:02:26.360> can't<00:02:26.720> live<00:02:26.840> alone<00:02:27.120> any<00:02:27.280> longer. 00:02:28.440 --> 00:02:36.640 And<00:02:28.640> so,<00:02:29.360> what<00:02:29.600> we<00:02:29.800> do<00:02:30.000> is<00:02:30.120> help<00:02:30.360> people<00:02:30.800> with<00:02:31.120> those<00:02:31.400> ADLs,<00:02:31.880> with<00:02:32.000> those<00:02:32.200> activities<00:02:32.760> of<00:02:32.840> daily<00:02:33.080> living,<00:02:33.320> which<00:02:33.480> are<00:02:33.600> simple<00:02:34.040> as<00:02:34.280> get<00:02:34.600> food<00:02:35.400> to<00:02:35.560> as<00:02:35.680> complicated<00:02:36.440> as 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pro<00:02:48.959> who<00:02:49.240> works<00:02:49.560> with<00:02:49.680> that<00:02:49.880> person. 00:02:51.720 --> 00:02:58.000 So,<00:02:51.959> what<00:02:52.200> made<00:02:52.480> you,<00:02:52.800> cuz,<00:02:53.000> cuz<00:02:53.760> if<00:02:53.920> I<00:02:53.959> remember<00:02:54.280> this,<00:02:54.560> you<00:02:54.720> sold<00:02:54.959> your<00:02:55.160> you<00:02:55.320> sold<00:02:55.600> your<00:02:56.160> first<00:02:56.520> company<00:02:57.000> to<00:02:57.160> Google. 00:02:58.000 --> 00:03:03.280 Mhm.<00:02:58.840> Um,<00:02:59.320> you<00:02:59.440> went<00:02:59.560> to<00:02:59.680> Stanford,<00:03:00.519> uh,<00:03:01.000> for,<00:03:01.560> uh,<00:03:01.600> you<00:03:01.680> got<00:03:01.800> an<00:03:01.880> MBA<00:03:02.200> at<00:03:02.280> Stanford,<00:03:02.760> is<00:03:02.840> that<00:03:03.000> right? 00:03:03.280 --> 00:03:05.560 <00:03:03.550> Well,<00:03:03.820> I<00:03:04.090> dropped<00:03:04.360> out.<00:03:04.630> So,<00:03:04.900> 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think<00:03:49.880> a<00:03:50.000> a<00:03:50.080> of<00:03:50.160> things<00:03:50.360> that<00:03:50.440> are<00:03:50.519> happening<00:03:50.959> today,<00:03:51.320> like<00:03:51.519> if<00:03:51.640> people<00:03:51.920> had<00:03:52.080> held<00:03:52.320> themselves<00:03:52.720> to<00:03:52.800> that<00:03:53.000> bar,<00:03:53.280> maybe<00:03:53.600> society<00:03:54.080> would<00:03:54.200> be<00:03:54.320> in<00:03:54.400> a<00:03:54.440> better 00:03:54.680 --> 00:03:58.560 place.<00:03:55.400> Yeah,<00:03:55.600> for<00:03:55.760> sure.<00:03:56.080> Um,<00:03:56.120> but<00:03:56.440> it's<00:03:56.640> the<00:03:56.680> bar<00:03:56.880> I<00:03:56.920> hold<00:03:57.160> myself<00:03:57.560> to. 00:03:58.560 --> 00:04:04.760 Um,<00:03:59.320> and<00:03:59.440> so<00:03:59.560> when<00:03:59.680> I<00:03:59.720> was<00:03:59.840> at<00:03:59.920> Google<00:04:00.320> then,<00:04:00.800> after<00:04:01.040> having<00:04:01.280> sold<00:04:01.600> it<00:04:01.720> and<00:04:01.840> kind<00:04:02.000> of<00:04:02.080> said,<00:04:02.400> "Hey,<00:04:02.600> what<00:04:02.760> do<00:04:02.920> what<00:04:03.040> do<00:04:03.160> we,<00:04:03.440> like<00:04:03.680> the<00:04:03.760> co-founders<00:04:04.240> and<00:04:04.320> I,<00:04:04.400> want<00:04:04.600> to<00:04:04.640> work 00:04:04.760 --> 00:04:12.640 on<00:04:04.880> next?"<00:04:06.000> The<00:04:06.120> rules<00:04:06.480> were<00:04:07.160> a<00:04:07.280> hard<00:04:07.600> problem<00:04:08.520> where<00:04:08.680> we<00:04:08.800> could<00:04:08.920> look<00:04:09.480> a<00:04:09.520> person<00:04:09.800> in<00:04:09.840> the<00:04:10.080> eye<00:04:10.160> and<00:04:10.240> know<00:04:10.400> that<00:04:10.520> we<00:04:10.600> would<00:04:10.720> make<00:04:10.880> their<00:04:11.000> lives<00:04:11.320> fundamentally<00:04:11.800> better. 00:04:12.640 --> 00:04:20.239 And<00:04:12.720> it<00:04:12.840> had<00:04:13.000> to<00:04:13.040> be<00:04:13.160> millions,<00:04:13.560> 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know,<00:05:09.960> how<00:05:10.120> does<00:05:10.360> like<00:05:10.560> this,<00:05:11.160> you<00:05:11.280> know,<00:05:11.840> change<00:05:12.120> the<00:05:12.240> world? 00:05:12.600 --> 00:05:15.120 It<00:05:12.787> doesn't<00:05:12.973> doesn't<00:05:13.160> make<00:05:13.347> tons<00:05:13.533> of<00:05:13.720> sense."<00:05:13.907> But<00:05:14.093> <00:05:14.280> Yeah. 00:05:15.120 --> 00:05:18.000 it's<00:05:15.280> almost<00:05:15.720> like<00:05:16.080> we've<00:05:16.320> gone<00:05:16.560> the<00:05:16.720> opposite<00:05:17.280> way. 00:05:18.000 --> 00:05:20.120 Like<00:05:18.200> we<00:05:18.280> don't<00:05:18.480> even<00:05:18.760> care<00:05:19.240> about<00:05:19.560> that<00:05:19.720> anymore. 00:05:20.120 --> 00:05:28.880 Or<00:05:20.400> and<00:05:20.560> the<00:05:20.680> thing<00:05:20.880> that<00:05:21.040> we<00:05:21.200> celebrate<00:05:21.960> is<00:05:22.200> more<00:05:23.520> the<00:05:23.640> high<00:05:23.880> valuations,<00:05:25.000> who's<00:05:25.280> on<00:05:25.440> the<00:05:25.560> Forbes,<00:05:26.919> you<00:05:27.000> know,<00:05:27.440> richest<00:05:28.520> list 00:05:28.880 --> 00:05:32.200 every<00:05:29.160> year<00:05:29.520> and<00:05:29.640> like<00:05:29.800> for<00:05:29.919> some<00:05:30.160> reason<00:05:30.400> those<00:05:30.640> are<00:05:30.680> the<00:05:30.800> people<00:05:31.080> we<00:05:31.240> celebrate. 00:05:32.200 --> 00:05:35.080 Why<00:05:32.360> do<00:05:32.480> you<00:05:32.600> think<00:05:32.840> that's<00:05:33.120> happening?<00:05:34.000> Yeah,<00:05:34.120> it's<00:05:34.240> a<00:05:34.280> great<00:05:34.440> question. 00:05:35.080 --> 00:05:39.600 Um,<00:05:35.280> so<00:05:35.400> I<00:05:35.440> actually<00:05:35.640> think<00:05:35.760> it's<00:05:35.840> even<00:05:36.040> worse<00:05:36.240> than<00:05:36.360> that.<00:05:36.640> I<00:05:36.680> think<00:05:36.880> that<00:05:37.120> we<00:05:37.320> celebrate<00:05:38.080> the<00:05:38.320> like<00:05:38.880> Midas<00:05:39.320> list. 00:05:39.600 --> 00:05:44.880 So<00:05:39.720> we<00:05:40.040> celebrate<00:05:40.680> the<00:05:40.960> asset<00:05:41.400> allocators<00:05:42.160> rather<00:05:42.560> than<00:05:42.960> the<00:05:43.520> operators<00:05:43.960> who<00:05:44.040> are<00:05:44.120> building<00:05:44.440> the<00:05:44.520> things. 00:05:44.880 --> 00:05:50.440 Think<00:05:45.280> about<00:05:45.480> it,<00:05:45.600> most<00:05:45.840> of<00:05:45.919> the<00:05:46.000> media<00:05:46.360> is<00:05:46.520> actually<00:05:46.880> about<00:05:47.760> the<00:05:47.880> asset<00:05:48.160> allocators,<00:05:48.680> the<00:05:49.000> VCs<00:05:49.440> or<00:05:49.520> investors. 00:05:50.440 --> 00:05:56.840 And<00:05:50.560> I<00:05:51.040> they're<00:05:51.160> great<00:05:51.400> people.<00:05:52.680> But<00:05:52.840> why<00:05:52.960> are<00:05:53.080> we<00:05:53.200> celebrating<00:05:53.680> them<00:05:53.880> and<00:05:53.960> not<00:05:54.280> like,<00:05:54.560> 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drug<00:06:14.840> intervention<00:06:16.080> to<00:06:16.640> let's<00:06:16.880> make<00:06:17.160> health<00:06:17.400> care<00:06:17.640> significantly<00:06:18.440> more<00:06:18.680> efficient<00:06:19.120> so<00:06:19.240> we<00:06:19.320> can<00:06:19.480> actually<00:06:19.760> reduce<00:06:20.000> costs. 00:06:20.360 --> 00:06:27.240 I<00:06:20.400> have<00:06:20.520> a<00:06:20.600> lot<00:06:20.919> of<00:06:21.040> friends<00:06:21.280> like<00:06:21.440> that.<00:06:22.760> Um,<00:06:23.200> but<00:06:23.400> then<00:06:23.560> if<00:06:23.680> you<00:06:23.800> look<00:06:23.919> at<00:06:24.040> the<00:06:24.880> and<00:06:25.000> those<00:06:25.480> happen<00:06:25.720> to<00:06:25.800> be<00:06:25.880> the<00:06:25.960> people<00:06:26.240> I'm<00:06:26.360> friends<00:06:26.640> with. 00:06:27.240 --> 00:06:35.440 Mhm.<00:06:28.000> Um,<00:06:28.600> but<00:06:28.760> then<00:06:28.919> if<00:06:29.040> you<00:06:29.280> I<00:06:29.360> think<00:06:29.600> look<00:06:29.720> at<00:06:29.800> the<00:06:29.960> bulk<00:06:30.640> of<00:06:30.800> the<00:06:30.919> stuff<00:06:31.240> that's<00:06:31.480> happening<00:06:33.120> and<00:06:33.360> you<00:06:34.080> hold<00:06:34.400> it<00:06:34.520> up<00:06:34.640> to<00:06:34.760> the<00:06:34.880> world<00:06:35.240> good 00:06:35.440 --> 00:06:38.400 litmus<00:06:35.720> test,<00:06:36.600> it<00:06:37.000> it<00:06:37.120> doesn't<00:06:37.400> pass. 00:06:38.400 --> 00:06:44.440 Um,<00:06:39.440> and<00:06:40.320> you<00:06:40.400> know,<00:06:40.520> there<00:06:40.840> and<00:06:41.040> now<00:06:41.320> we<00:06:41.440> should<00:06:41.560> be<00:06:41.680> clear,<00:06:42.000> enabling<00:06:42.520> technologies<00:06:43.160> do<00:06:43.320> pass. 00:06:44.440 --> 00:06:47.640 It's<00:06:44.520> like<00:06:44.880> AI<00:06:45.840> fundamentally<00:06:46.520> a<00:06:46.560> world<00:06:46.840> good. 00:06:47.640 --> 00:06:50.440 Mhm.<00:06:47.831> <00:06:48.022> 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00:12:41.800 --> 00:12:45.760 right?"<00:12:42.080> I<00:12:42.120> didn't<00:12:42.320> have<00:12:42.520> it<00:12:42.640> pre-planned.<00:12:43.200> There<00:12:43.320> wasn't<00:12:43.600> like<00:12:43.800> a<00:12:44.400> 30-minute<00:12:44.839> back-to-back<00:12:45.280> all<00:12:45.360> day<00:12:45.480> long. 00:12:45.760 --> 00:12:51.680 I<00:12:45.800> think<00:12:45.920> that's<00:12:46.120> bad<00:12:46.680> at<00:12:46.800> this<00:12:46.960> point.<00:12:47.280> Like<00:12:47.400> if<00:12:47.520> I<00:12:47.600> if<00:12:47.800> my<00:12:47.920> schedule<00:12:48.320> is<00:12:48.400> like<00:12:48.560> 30-minute<00:12:49.040> back-to-back<00:12:49.560> every<00:12:49.760> day<00:12:50.080> and<00:12:50.280> I<00:12:50.320> was<00:12:50.440> just<00:12:50.600> like<00:12:50.760> running<00:12:50.960> around<00:12:51.200> with<00:12:51.320> chicken 00:12:51.680 --> 00:12:54.440 like<00:12:51.800> chicken<00:12:52.000> with<00:12:52.080> my<00:12:52.160> 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company. 00:14:07.720 --> 00:14:14.920 And<00:14:08.080> that<00:14:08.480> really<00:14:08.760> drives<00:14:09.080> culture.<00:14:09.840> There<00:14:10.080> is<00:14:10.200> this<00:14:10.400> other<00:14:10.640> part<00:14:10.920> which<00:14:11.120> is<00:14:12.280> like<00:14:12.520> we<00:14:12.760> are<00:14:13.240> and<00:14:13.360> it's<00:14:13.600> actually<00:14:13.800> number<00:14:14.000> one<00:14:14.120> of<00:14:14.160> our<00:14:14.200> leadership<00:14:14.440> principles. 00:14:14.920 --> 00:14:16.880 Like<00:14:15.160> we<00:14:15.280> are<00:14:15.400> super<00:14:15.800> mission-oriented,<00:14:16.600> right? 00:14:16.880 --> 00:14:19.360 Like<00:14:17.520> if<00:14:17.680> you<00:14:17.800> work<00:14:18.040> here,<00:14:18.160> you<00:14:18.280> better<00:14:18.440> care<00:14:18.560> about<00:14:18.800> the<00:14:18.880> mission. 00:14:19.360 --> 00:14:21.520 You<00:14:19.560> will<00:14:19.760> work<00:14:19.960> harder<00:14:20.240> because<00:14:20.560> 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00:26:44.680 And<00:26:40.440> once<00:26:40.680> again,<00:26:41.080> what<00:26:41.200> the<00:26:41.280> people<00:26:41.600> are<00:26:41.680> choosing<00:26:42.000> to<00:26:42.120> click<00:26:42.360> on<00:26:43.440> is<00:26:43.640> the<00:26:43.760> divisive<00:26:44.240> stuff,<00:26:44.520> right? 00:26:44.680 --> 00:26:49.320 It<00:26:44.760> goes<00:26:44.960> straight<00:26:45.280> back<00:26:45.640> to<00:26:45.840> the<00:26:46.200> conversation<00:26:46.760> we're<00:26:46.880> having<00:26:47.160> about<00:26:47.480> kind<00:26:47.640> of<00:26:47.720> where<00:26:47.840> has<00:26:48.000> our<00:26:48.120> politics<00:26:48.560> gone? 00:26:49.320 --> 00:26:57.720 It's<00:26:49.520> that<00:26:50.040> people<00:26:50.520> actually<00:26:51.520> reward<00:26:52.360> the<00:26:52.560> politician<00:26:53.280> or<00:26:53.440> reward<00:26:54.040> the<00:26:54.160> algorithm<00:26:55.000> by<00:26:55.440> clicking<00:26:55.840> on<00:26:56.000> the<00:26:56.080> 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like<00:31:01.480> they<00:31:01.800> really<00:31:02.160> helped,<00:31:02.600> you<00:31:02.680> know,<00:31:02.800> kind<00:31:02.960> of<00:31:03.040> create<00:31:03.200> a<00:31:03.240> trajectory<00:31:03.720> for<00:31:03.840> me. 00:31:04.560 --> 00:31:07.360 That's<00:31:04.760> incredible.<00:31:05.400> Seth,<00:31:05.760> thank<00:31:06.000> you<00:31:06.120> so<00:31:06.280> much<00:31:06.520> for<00:31:06.640> coming<00:31:06.840> on<00:31:06.920> the<00:31:07.000> show. 00:31:07.360 --> 00:31:11.760 What<00:31:07.520> an<00:31:07.640> honor<00:31:07.880> to<00:31:08.000> have<00:31:08.280> you.<00:31:08.800> What<00:31:08.920> an<00:31:09.000> incredible<00:31:09.440> company<00:31:09.800> you're<00:31:09.960> building<00:31:10.480> and<00:31:10.640> leader<00:31:10.920> you<00:31:11.080> are. 00:31:11.760 --> 00:31:13.840 Really,<00:31:12.080> it's<00:31:12.240> an<00:31:12.280> honor<00:31:12.480> to<00:31:12.560> have<00:31:12.760> you.<00:31:13.000> Thank<00:31:13.200> you.<00:31:13.440> Yeah,<00:31:13.560> totally. 00:31:13.840 --> 00:31:17.480 Thanks<00:31:14.040> for<00:31:14.120> having<00:31:14.320> me,<00:31:14.400> Glenn.<00:31:14.600> I<00:31:14.640> appreciate<00:31:15.080> it.<00:31:15.160> It's<00:31:15.240> so<00:31:15.320> much<00:31:15.480> fun. ``` ### Lightspeed CEO, Dax Dasilva: How Lightspeed built a $1.2B commerce platform URL: https://www.ceo.com/episodes/lightspeed-ceo-dax-dasilva-how-lightspeed-built-a-1-2b-commerce-platform/ Last updated: 2026-08-24T18:49:53.000Z # Dax Dasilva built Lightspeed twice Dax Dasilva has run Lightspeed twice. He founded the company in Montreal in 2005 and ran it until February 2022, when he stepped down, handed the job to his longtime second-in-command JP Chauvet, and went off to fund conservation work. Two years later, the board asked him to come back. Lightspeed had beaten its third-quarter forecasts, and the stock fell anyway, [down more than 85 percent from its 2021 peak](https://betakit.com/lightspeed-founder-dax-dasilva-returns-as-interim-ceo-replacing-jp-chauvet/?ref=ceo.com) after a tech downturn and a short-seller report. Chauvet stepped down. [Dasilva was reappointed the same day](https://www.lightspeedhq.com/news/lightspeed-announces-the-return-of-dax-dasilva-as-ceo/?ref=ceo.com), interim at first, [permanent by May](https://investors.lightspeedhq.com/English/management/board-of-directors/person-details/default.aspx?ItemId=9ee6c1bb-a675-4549-95cf-501587c1623f&ref=ceo.com). On the CEO.com Podcast, Dasilva talked about the company at 20 years old: roughly 145,000 customers, $1.2 billion in revenue, 3,500 employees, and a multi-year transformation he is running in full view of the public markets. The company started with Apple dealers. Before Apple opened its own stores, independent Mac dealerships operated everywhere, and Dasilva worked in them as a teenager, building their software. The first couple hundred Lightspeed installations went to those dealers. A year after launch, about 50 of them flew to Montreal for training, from Saudi Arabia, Ireland, Australia, Canada, and the U.S. "That was the moment where I thought, 'Okay, this could actually become something much bigger,'" Dasilva said. They didn't just want the software. They wanted to build businesses selling it. Twenty years later, his pitch for AI starts with an admission. Running a store or a restaurant got harder, and technology is partly to blame. Owners now manage social media, online marketing, scheduling, inventory across channels, and analytics. "People don't open restaurants because they love software administration panels," he said. "They open restaurants because they love Spanish cuisine or hospitality." Lightspeed is starting with AI assistants that help merchants navigate workflows, then moving toward agents that do the work themselves. The stranger position Dasilva holds is that he likes being public. Lightspeed listed on the Toronto Stock Exchange in 2019, and the NYSE in 2020, and a wave of Canadian companies followed. Some have since gone private. Lightspeed considered its options too. After a strategic review of its portfolio and ownership structure, [the board decided in February 2025](https://www.lightspeedhq.com/news/lightspeed-announces-results-of-strategic-review-and-third-quarter-2025-financial-results/?ref=ceo.com) to stay public and execute the transformation in the open, focused on retail in North America and hospitality in Europe. "The public-company phase has actually been my favorite part of the journey," Dasilva said on the CEO.com Podcast. "The market gives you very immediate and honest feedback." He conceded that shifting away from the growth-at-all-costs era while everyone watches in real time is not comfortable. He argued the visibility pays for itself in recruiting, sales, and credibility, and he has used it. In January, he led a session at [NRF 2026, Retail's Big Show](https://www.lightspeedhq.com/retails-big-show-2026/?ref=ceo.com), in New York. His two years away changed one thing about how he runs the place. "I realized how much I genuinely love the energy of being in the office," he said. Lightspeed expects employees in Tuesday through Thursday, and Dasilva's reasoning is tied to what the company sells. Lightspeed builds software for physical stores and restaurants, so it believes in rooms. "You can absolutely maintain a business remotely, but I think the truly exceptional ideas are usually created in person." He is skeptical of loud leadership for the same reason. "A lot of people think leadership means being the loudest person in the room, but I actually think the opposite is true," he said. People commit to decisions they disagree with when they know they were heard. He applies the same restraint to politics, weighing in only when an issue directly hits his customers. Tariffs qualify. Most things don't. The years away produced a book. [*Echoes from Eden*](https://ageofunion.com/articles/2025/04/22/tech-entrepreneur-and-environmentalist-dax-dasilva-announces-new-book-echoes-from-eden-as-a-call-to-action-to-protect-the-planets-vanishing-ecosystems/?ref=ceo.com) recounts his expeditions to endangered ecosystems from the Congo to Trinidad. "Conservation projects are actually very similar to startups," he said. "Small groups of passionate people can create extraordinary change." Every episode ends with the same question: who gave you a chance? Dasilva credited his father. His parents came to Canada as refugees from Uganda, and money was tight, but his father made sure he had access to computers. At 13, Dasilva was apprenticing at a startup. Macs were expensive then. His father found ways to get him one anyway. ```chapters 00:00:00 Introduction and Background of Lightspeed Commerce 00:00:54 Evolution and Expansion of Lightspeed's Services 00:01:26 Target Market and Customer Base 00:02:07 Early Success and Key Milestones 00:03:38 Impact of AI on Business Operations 00:04:45 Role of the CEO in Modern Times 00:06:03 Public Statements and Political Opinions 00:07:27 Going Public: Decision and Reflections 00:08:48 Benefits of Being a Public Company 00:10:09 Company Culture and Hybrid Work Model 00:10:25 Returning as CEO and Office Dynamics 00:12:28 A Day in the Life of a CEO 00:14:22 Reading Recommendations 00:15:35 Writing Books: Process and Inspiration 00:17:44 Qualities of a Great Leader 00:19:49 Building a Global Company from Canada 00:20:48 Economic Outlook and Consumer Sentiment 00:22:49 Acknowledging Those Who Gave a Chance ``` ```vtt WEBVTT 00:00:00.000 --> 00:00:02.240 Dax,<00:00:00.560> thank<00:00:00.760> you<00:00:00.840> so<00:00:00.960> 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public. 00:07:30.320 --> 00:07:33.280 Is<00:07:30.440> that<00:07:30.600> right?<00:07:31.160> Mhm.<00:07:31.560> Yeah.<00:07:32.120> What<00:07:32.280> went<00:07:32.440> into<00:07:32.640> that<00:07:32.840> decision? 00:07:33.280 --> 00:07:36.919 Are<00:07:33.400> you<00:07:33.600> glad<00:07:33.960> you<00:07:34.040> went<00:07:34.200> public?<00:07:35.280> Because<00:07:35.680> that's<00:07:35.919> a<00:07:36.000> whole<00:07:36.200> thing<00:07:36.480> now,<00:07:36.720> too. 00:07:36.919 --> 00:07:41.400 In<00:07:37.000> 2019,<00:07:37.520> I<00:07:37.560> think<00:07:37.760> that<00:07:37.840> was<00:07:38.000> like<00:07:38.120> the<00:07:38.280> obvious<00:07:39.440> thing<00:07:39.560> that<00:07:39.720> you<00:07:39.800> did<00:07:39.960> when<00:07:40.080> you're<00:07:40.200> a<00:07:40.280> company<00:07:40.640> like<00:07:40.840> at<00:07:40.919> your<00:07:41.080> size. 00:07:41.400 --> 00:07:48.080 Now<00:07:41.680> we<00:07:41.840> have<00:07:42.000> these<00:07:42.480> private<00:07:42.840> companies<00:07:43.280> that<00:07:43.400> are<00:07:43.520> worth<00:07:44.440> an<00:07:44.560> insane<00:07:44.920> amount<00:07:45.120> of<00:07:45.200> money<00:07:45.560> who<00:07:45.760> are<00:07:45.880> like<00:07:46.120> kind<00:07:46.240> of<00:07:46.360> like,<00:07:46.560> "Oh,<00:07:46.680> there's<00:07:46.880> no<00:07:47.160> reason<00:07:47.480> to<00:07:47.600> go<00:07:47.760> public." 00:07:48.080 --> 00:07:52.360 So,<00:07:48.560> so<00:07:48.680> how<00:07:48.800> do<00:07:48.920> you<00:07:49.040> think<00:07:49.240> about<00:07:49.520> that<00:07:49.720> now,<00:07:50.720> uh<00:07:50.800> 6<00:07:51.000> years<00:07:51.240> later? 00:07:52.360 --> 00:07:57.640 Yeah,<00:07:52.520> we<00:07:52.640> went<00:07:52.880> we<00:07:53.000> went<00:07:53.200> public<00:07:53.440> on<00:07:53.520> the<00:07:53.600> Toronto<00:07:53.880> Stock<00:07:54.120> Exchange<00:07:54.440> in<00:07:54.520> 2019<00:07:55.160> 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meetings. 00:12:36.560 --> 00:12:42.520 I<00:12:36.640> think<00:12:36.920> it's,<00:12:37.960> uh,<00:12:38.000> we<00:12:38.120> have<00:12:38.280> like<00:12:38.600> a,<00:12:39.360> um,<00:12:40.040> I<00:12:40.160> never.<00:12:40.800> No<00:12:41.040> week<00:12:41.280> is<00:12:41.400> ever<00:12:41.600> the<00:12:41.680> same. 00:12:42.520 --> 00:12:50.760 No<00:12:42.680> day<00:12:42.880> is<00:12:43.000> ever<00:12:43.200> the<00:12:43.320> same,<00:12:44.120> but<00:12:44.400> I<00:12:44.480> mean,<00:12:45.080> it's<00:12:45.320> meeting<00:12:45.680> with,<00:12:46.680> um,<00:12:48.120> it's<00:12:48.400> meeting<00:12:48.600> with<00:12:48.720> our<00:12:48.839> product<00:12:49.160> teams,<00:12:49.400> it's<00:12:49.560> meeting<00:12:49.800> with<00:12:49.920> our<00:12:50.200> our<00:12:50.560> our 00:12:50.760 --> 00:12:59.480 go-to-market<00:12:51.360> teams,<00:12:52.200> uh,<00:12:52.320> or<00:12:52.560> individual<00:12:53.080> leaders<00:12:53.440> 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and<00:22:51.680> that<00:22:51.920> is<00:22:52.120> at<00:22:52.320> CEO.com,<00:22:53.240> we<00:22:53.400> believe<00:22:53.680> the<00:22:53.800> chances<00:22:54.200> one<00:22:54.480> gives<00:22:55.000> is<00:22:55.120> just<00:22:55.320> as<00:22:55.400> important 00:22:55.720 --> 00:23:02.760 as<00:22:55.840> the<00:22:55.920> chances<00:22:56.320> one<00:22:56.520> takes.<00:22:57.560> When<00:22:57.800> you<00:22:57.920> hear<00:22:58.160> that,<00:22:58.440> who<00:22:58.600> gave<00:22:58.840> you<00:22:58.960> a<00:22:59.000> chance<00:22:59.320> to<00:22:59.440> get<00:22:59.560> you<00:22:59.680> to<00:22:59.800> where<00:22:59.960> you<00:23:00.120> are<00:23:00.240> today? 00:23:02.760 --> 00:23:11.440 I<00:23:02.880> I'd<00:23:03.000> have<00:23:03.120> to<00:23:03.200> I'd<00:23:03.360> have<00:23:03.520> to<00:23:03.600> give<00:23:03.720> credit<00:23:04.000> to<00:23:04.080> my<00:23:04.200> father,<00:23:04.800> you<00:23:04.920> know,<00:23:05.160> 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at<00:23:23.000> a<00:23:23.040> startup<00:23:23.440> at<00:23:23.760> between<00:23:24.000> 13<00:23:24.360> and<00:23:24.480> 15. 00:23:25.520 --> 00:23:33.440 Um,<00:23:26.000> and<00:23:26.240> you<00:23:26.320> know,<00:23:26.400> we<00:23:26.480> didn't<00:23:26.600> have<00:23:26.720> a<00:23:26.760> lot<00:23:26.920> of<00:23:26.960> money.<00:23:27.120> My<00:23:27.240> parents<00:23:27.480> were<00:23:27.560> refugees,<00:23:28.160> but<00:23:28.280> my<00:23:28.360> dad<00:23:28.600> made<00:23:28.760> sure<00:23:29.000> that<00:23:29.600> I<00:23:29.720> had<00:23:30.720> you<00:23:30.840> know,<00:23:31.880> a<00:23:31.960> Mac<00:23:32.280> equipment,<00:23:32.760> which<00:23:32.920> was 00:23:33.440 --> 00:23:38.640 more<00:23:33.720> expensive<00:23:34.320> than<00:23:34.480> any<00:23:35.200> cheap<00:23:35.480> PC<00:23:35.920> you<00:23:36.040> could<00:23:36.160> get<00:23:36.440> at<00:23:36.560> the<00:23:36.640> time<00:23:37.000> in<00:23:37.320> in<00:23:37.440> the<00:23:37.520> '90s. 00:23:38.640 --> 00:23:48.960 Uh,<00:23:38.960> and<00:23:39.160> so,<00:23:39.560> he<00:23:39.920> really<00:23:40.280> indulged<00:23:40.880> me<00:23:41.040> in<00:23:41.200> terms<00:23:41.480> of<00:23:41.560> all<00:23:41.680> the<00:23:41.800> things<00:23:42.040> that<00:23:42.160> I<00:23:42.240> thought<00:23:42.560> I<00:23:42.640> needed,<00:23:44.000> and<00:23:45.120> it<00:23:45.280> kept<00:23:45.560> my<00:23:45.720> excitement<00:23:47.280> for 00:23:48.960 --> 00:23:58.160 for<00:23:49.320> it<00:23:49.440> really,<00:23:49.960> you<00:23:50.080> know,<00:23:50.240> fueled,<00:23:50.960> and<00:23:53.080> I<00:23:53.160> have<00:23:53.320> to,<00:23:53.440> I<00:23:53.480> have<00:23:53.600> to<00:23:53.680> give<00:23:53.840> him<00:23:53.960> credit<00:23:54.280> for,<00:23:55.320> for<00:23:55.960> investing<00:23:56.400> in<00:23:56.480> me,<00:23:56.880> you<00:23:56.960> know. 00:23:58.160 --> 00:24:01.280 That's<00:23:58.440> awesome.<00:23:58.840> Dax,<00:23:59.200> thank<00:23:59.400> you<00:23:59.480> so<00:23:59.640> much<00:23:59.920> for<00:24:00.040> coming<00:24:00.360> on<00:24:00.560> the<00:24:00.640> show. 00:24:01.280 --> 00:24:04.320 Yeah,<00:24:01.320> thank<00:24:01.520> you.<00:24:01.760> For<00:24:01.840> an<00:24:01.920> incredible<00:24:02.320> company. ``` ### Theorem CEO, Jay Kulkarni: Why authentic brands will win in the AI era URL: https://www.ceo.com/episodes/theorem-ceo-jay-kulkarni-why-authentic-brands-will-win-in-the-ai-era/ Last updated: 2026-08-24T19:04:13.000Z # Jay Kulkarni doesn't think a machine can tell your story Jay Kulkarni started Theorem in 2002 from a spare bedroom in New Jersey. Before that, he had exactly one job: five years at DoubleClick, where he [ran product management](https://pulse2.com/theorem-profile-jay-kulkarni-interview/?ref=ceo.com) for advertiser solutions and email platforms. "I'm the first entrepreneur in my family," he said on the CEO.com Podcast. "I came to the U.S. as an immigrant." He never raised institutional money. "I bootstrapped the company. We've managed through multiple recessions and continued growing." Theorem grew into a global company, with teams in India, Australia, and the Dominican Republic. It is still headquartered in Chatham, New Jersey, where Kulkarni is in the office by 6:30 or 7:00 most mornings even though the company went hybrid after COVID. He leaves by mid-afternoon for the gym, and in the evenings he practices piano. He started three years ago. "It's one of the hardest things I've ever done." Theorem serves two kinds of customers: content companies and commerce companies. The content side is streaming platforms, publishers, media businesses, anyone selling advertising, which, as Kulkarni notes, "has increasingly overtaken subscriptions as a revenue stream, especially in streaming." When an ad deal closes, someone has to run it: insertion orders, creative deployment, audience targeting, campaign management, reporting, around the clock, in multiple languages. Theorem spent two decades doing that work by hand before deciding to automate itself. The result is Upward, a media monetization platform the company tested internally for 12 to 18 months before showing a customer. One of the largest audio streaming brands [has since moved its ad operations onto it](https://pulse2.com/theorem-profile-jay-kulkarni-interview/?ref=ceo.com), retiring the spreadsheets that used to carry its order-to-cash process. Most of Upward was built by people who have spent their careers at Theorem. "We've had at least 17 employees stay with the company for more than 15 years, which I'm incredibly proud of," Kulkarni said. The company runs on a framework it calls Ways of Working: purpose, process, people. Training sessions, client reviews, and team events happen in person, no exceptions. Kulkarni [told Pulse 2.0](https://pulse2.com/theorem-profile-jay-kulkarni-interview/?ref=ceo.com) the approach earned Theorem the No. 3 spot on 2024's Best Place to Work in America list. The next 20 years, as he sees them, run through video commerce. Not TikTok, not Instagram. The brand's own website. "Brands care deeply about having a one-to-one relationship with consumers, but they also want to control that interaction," he said. "If everything happens on TikTok or Instagram, they lose ownership of the experience and the data." He has the ground truth on his side: [95 percent of digital commerce still happens on ecommerce websites](https://theorem.digital/theorem-and-firework-partner-for-breakthrough-video-commerce/?ref=ceo.com), which is why Theorem partnered with Firework, the AI video commerce platform, to build shoppable video directly into brand storefronts. In August, MarTech Breakthrough named Theorem its [Overall Conversion Optimization Solution of the Year](https://www.globenewswire.com/news-release/2026/08/06/3340432/0/en/2026-martech-breakthrough-awards-recognize-the-world-s-most-innovative-marketing-sales-and-advertising-technology-companies.html?ref=ceo.com), [a win Kulkarni credited to the video commerce pilot](https://finance.yahoo.com/media-advertising/articles/theorem-wins-overall-conversion-optimization-140000669.html?ref=ceo.com). AI runs underneath all of it. Theorem trains models that let brands write their own content rules and enforce them automatically. Partial nudity is fine for an underwear brand and a problem almost everywhere else. But on whether AI will eventually make the videos itself, with no people involved, Kulkarni is a holdout. "I actually have a contrarian view on that. Humans still crave authenticity and human connection. Storytelling is fundamentally human. Hearing someone tell you a story is different from hearing it from a machine." Machines reduce friction, he said. They do not build trust. "If you look at great brands throughout history, the ones that survive wars, recessions, and economic upheaval are built on trust and ethos. I don't think machines replace that." He holds his own industry to the same rule: "Consumers should know when content was generated by AI." Every CEO.com Podcast ends with the same question: who gave you a chance? Kulkarni had been accepted to school in the United States, but his passport had expired, and without it he would miss his visa interview and lose the opportunity. His father was a school teacher. A retired colleague of his father's offered to help and came with them to the passport office, where the officer on duty turned out to be the man's former student. The passport was expedited. Kulkarni made it to America. When he thanked the man, he got the rest of the story. Years earlier, the man's own son had wanted to study in America, and a teacher's salary could not cover it. The son wrote letters asking for help. Princess Grace of Monaco paid for his education. "He told me, 'Someone helped my son, so I helped you.' That's always stayed with me." ```chapters 00:00:00 Introduction and Jay's Background 00:00:50 What is Theorem? 00:01:12 Theorem's Business Model 00:01:55 Upword: Theorem's Automation Solution 00:02:29 Video Commerce and Its Importance 00:03:24 Evolution and Future of Video Commerce 00:04:08 Benefits of On-Site Video Commerce 00:05:02 AI in Digital Marketing 00:06:08 AI and Brand Safety 00:07:03 AI in Advertising Processes 00:08:16 Human Touch vs. AI 00:09:38 Jay's Daily Routine 00:12:00 Hybrid Work Model 00:14:01 Building Company Culture 00:17:18 Internal Use of AI and Automation 00:19:38 Economic Environment and Future Outlook 00:20:58 The Importance of Giving Chances 00:21:13 Personal Story of Opportunity 00:22:56 Conclusion and Farewell ``` ```vtt WEBVTT 00:00:00.000 --> 00:00:03.080 Jay,<00:00:00.240> thank<00:00:00.440> you<00:00:00.520> so<00:00:00.640> much<00:00:00.800> for<00:00:00.920> coming<00:00:01.200> on<00:00:01.280> the<00:00:01.400> show.<00:00:01.720> 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--> 00:06:05.760 What<00:05:57.560> do<00:05:57.640> I<00:05:57.720> mean<00:05:57.960> by<00:05:58.080> that?<00:05:59.120> If<00:05:59.320> I'm<00:05:59.680> Jockey<00:06:00.160> or<00:06:00.320> Hanes,<00:06:01.400> partial<00:06:01.840> nudity<00:06:02.440> is<00:06:02.680> okay<00:06:03.240> because<00:06:03.720> I'm<00:06:03.880> showing<00:06:04.240> under<00:06:05.520> That's 00:06:05.760 --> 00:06:12.040 perfectly<00:06:06.240> okay.<00:06:07.040> But<00:06:07.160> partial<00:06:07.640> nudity<00:06:08.360> in<00:06:08.440> a<00:06:08.520> political<00:06:09.120> ad<00:06:10.080> context<00:06:10.600> is<00:06:10.720> not<00:06:11.040> okay. 00:06:12.040 --> 00:06:21.080 So,<00:06:12.160> we're<00:06:12.320> training<00:06:12.640> machine<00:06:13.000> language<00:06:13.400> models<00:06:14.880> where<00:06:15.000> a<00:06:15.040> brand<00:06:15.440> can<00:06:16.200> put<00:06:16.440> up<00:06:16.560> their<00:06:16.720> own<00:06:16.880> policies<00:06:17.480> 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00:14:46.680 --> 00:14:50.360 So,<00:14:46.839> it's<00:14:47.000> underpinned<00:14:47.520> by<00:14:47.839> we<00:14:48.000> run<00:14:48.360> our<00:14:48.480> business<00:14:48.920> with<00:14:49.160> MBOs<00:14:49.600> and<00:14:49.760> KPIs. 00:14:50.360 --> 00:14:56.200 So,<00:14:50.440> everybody,<00:14:51.560> uh,<00:14:51.640> three<00:14:51.880> levels<00:14:52.240> down<00:14:52.720> knows<00:14:53.839> what<00:14:54.040> their<00:14:54.200> role<00:14:54.520> is,<00:14:54.720> what<00:14:54.960> their<00:14:55.120> remit<00:14:55.520> is. 00:14:56.200 --> 00:15:00.480 And<00:14:56.320> as<00:14:56.400> some<00:14:56.600> companies<00:14:57.040> call<00:14:57.240> it<00:14:57.400> OKRs,<00:14:58.040> which<00:14:58.200> is<00:14:58.360> fine,<00:14:58.640> but<00:14:58.760> the<00:14:58.839> concept<00:14:59.320> is<00:14:59.400> the<00:14:59.480> same. 00:15:00.480 --> 00:15:07.640 How<00:15:00.720> is<00:15:00.960> my<00:15:01.480> day-to-day<00:15:01.880> 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00:15:29.960 So,<00:15:20.960> we<00:15:21.160> have,<00:15:21.880> uh,<00:15:22.360> uh,<00:15:23.280> little<00:15:24.480> incremental<00:15:24.920> gains<00:15:26.320> to<00:15:26.440> try<00:15:26.760> to<00:15:27.240> change<00:15:27.640> something,<00:15:28.160> things<00:15:28.400> don't<00:15:28.600> go<00:15:28.800> well. 00:15:29.960 --> 00:15:34.480 So,<00:15:30.040> we<00:15:30.120> try<00:15:30.320> to<00:15:30.480> optimize<00:15:31.000> today<00:15:31.960> and<00:15:32.120> build<00:15:32.320> for<00:15:32.440> tomorrow,<00:15:33.280> but<00:15:33.400> we<00:15:33.520> learn<00:15:33.760> from<00:15:33.920> mistakes. 00:15:34.480 --> 00:15:40.160 It's<00:15:34.600> an<00:15:34.760> iterative<00:15:35.280> process.<00:15:36.160> It's<00:15:36.320> almost<00:15:36.680> like<00:15:36.960> your<00:15:37.400> aggregation<00:15:38.200> of<00:15:38.400> incremental<00:15:39.000> gains,<00:15:39.520> and<00:15:39.640> that's<00:15:39.880> okay. 00:15:40.160 --> 00:15:43.480 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00:21:20.600 Um,<00:21:13.200> there<00:21:13.360> are<00:21:14.160> quite<00:21:14.360> a<00:21:14.440> few<00:21:14.760> people<00:21:15.600> who<00:21:15.800> jump<00:21:16.120> to<00:21:16.240> mind,<00:21:17.360> but<00:21:17.560> over<00:21:17.760> the<00:21:17.880> years,<00:21:18.680> there's<00:21:18.920> one<00:21:19.240> specific<00:21:19.840> instance<00:21:20.400> that 00:21:20.600 --> 00:21:24.280 has<00:21:20.720> stuck,<00:21:21.280> and<00:21:21.360> it's<00:21:21.480> a<00:21:21.520> very<00:21:23.240> long<00:21:23.440> story. 00:21:24.280 --> 00:21:27.640 So,<00:21:24.400> I<00:21:24.440> came<00:21:24.720> to<00:21:24.800> the<00:21:24.920> US<00:21:25.320> as<00:21:25.480> an<00:21:25.600> immigrant.<00:21:26.040> I<00:21:26.080> came<00:21:26.280> as<00:21:26.400> a<00:21:26.440> student. 00:21:27.640 --> 00:21:33.080 And,<00:21:28.280> uh,<00:21:28.360> I<00:21:29.160> Yeah,<00:21:29.520> and<00:21:30.120> I<00:21:30.600> applied<00:21:31.000> to<00:21:31.120> 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colleagues,<00:21:52.000> "Say,<00:21:52.440> this<00:21:52.640> is<00:21:52.720> the<00:21:52.800> situation. 00:21:54.240 --> 00:22:01.720 Anybody?"<00:21:55.560> And<00:21:55.720> one<00:21:55.800> of<00:21:55.880> his<00:21:56.000> colleagues<00:21:56.360> said,<00:21:56.600> "My<00:21:56.760> dad's<00:21:57.040> a<00:21:57.120> school<00:21:58.440> He<00:21:58.520> knows<00:21:58.720> a<00:21:58.800> lot<00:21:59.040> of<00:21:59.120> people<00:21:59.920> in<00:22:00.160> the<00:22:00.560> government." 00:22:01.720 --> 00:22:09.880 He<00:22:01.840> He<00:22:01.920> had<00:22:02.040> He<00:22:02.080> had<00:22:02.200> He<00:22:02.280> was<00:22:02.400> a<00:22:02.440> retired<00:22:02.840> school<00:22:03.200> school<00:22:03.520> teacher,<00:22:04.040> and<00:22:04.280> he<00:22:04.600> came<00:22:05.480> to<00:22:05.560> the<00:22:05.680> passport<00:22:06.240> office,<00:22:06.880> and<00:22:07.320> as<00:22:07.520> luck<00:22:07.760> would<00:22:07.920> have<00:22:08.160> 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but<00:22:26.840> on<00:22:26.960> a<00:22:27.000> school<00:22:27.320> teacher's<00:22:27.680> salary,<00:22:28.360> his<00:22:28.560> son 00:22:28.800 --> 00:22:37.320 couldn't<00:22:29.160> afford.<00:22:30.400> So,<00:22:30.520> his<00:22:30.680> son<00:22:30.880> had<00:22:31.040> written<00:22:31.480> a<00:22:31.560> lot<00:22:31.760> of<00:22:31.880> letters,<00:22:33.320> uh,<00:22:33.440> to<00:22:33.600> foundations<00:22:34.440> and<00:22:34.640> charitable<00:22:35.120> organizations<00:22:36.240> asking<00:22:36.640> for<00:22:36.800> financial 00:22:37.320 --> 00:22:39.760 help.<00:22:38.320> And<00:22:38.520> guess<00:22:38.760> who<00:22:38.880> had<00:22:39.080> sponsored<00:22:39.560> him? 00:22:39.760 --> 00:22:44.240 Princess<00:22:40.160> Grace<00:22:40.560> of<00:22:40.680> Monaco<00:22:41.280> had<00:22:41.440> funded<00:22:42.160> his<00:22:42.560> education<00:22:43.080> in<00:22:43.160> America. 00:22:44.240 --> 00:22:48.840 So,<00:22:44.360> the<00:22:44.440> retired<00:22:44.760> school<00:22:46.040> "Somebody<00:22:46.400> help<00:22:46.560> my<00:22:46.720> son,<00:22:47.680> I<00:22:47.840> help<00:22:48.080> you." 00:22:48.840 --> 00:22:54.240 So,<00:22:49.040> I<00:22:49.120> guess<00:22:49.960> "pay<00:22:50.160> it<00:22:50.240> forward"<00:22:50.600> was<00:22:50.760> our<00:22:50.920> phrase<00:22:51.320> he<00:22:51.440> knew,<00:22:51.800> but<00:22:52.480> you<00:22:52.600> could<00:22:53.240> call<00:22:53.440> it<00:22:53.560> "pay<00:22:53.760> it<00:22:53.840> forward." 00:22:54.240 --> 00:22:57.240 So,<00:22:55.160> it<00:22:55.280> comes<00:22:55.520> to<00:22:55.600> mind.<00:22:56.000> That's<00:22:56.240> beautiful,<00:22:56.760> man. 00:22:57.240 --> 00:22:59.800 That's<00:22:57.480> incredible.<00:22:58.080> Jay,<00:22:58.400> thank<00:22:58.640> you<00:22:58.760> so<00:22:58.880> much<00:22:59.040> for<00:22:59.160> joining<00:22:59.560> us. 00:22:59.800 --> 00:23:03.360 What<00:22:59.920> an<00:23:00.000> incredible<00:23:00.440> company<00:23:00.800> you've<00:23:01.000> built.<00:23:02.200> Um,<00:23:02.360> let's<00:23:02.520> have<00:23:02.680> you<00:23:02.760> back<00:23:03.000> on,<00:23:03.160> too. 00:23:03.360 --> 00:23:05.240 I'd<00:23:03.480> love<00:23:03.640> to<00:23:03.760> even<00:23:04.040> go<00:23:04.160> deeper<00:23:04.480> on<00:23:04.560> some<00:23:04.720> of<00:23:04.800> this<00:23:04.960> stuff. 00:23:05.240 --> 00:23:07.680 But<00:23:05.440> yeah,<00:23:05.600> what<00:23:05.720> a<00:23:05.800> pleasure.<00:23:06.360> Really,<00:23:06.680> really<00:23:06.880> great<00:23:07.080> to<00:23:07.160> meet<00:23:07.320> you. 00:23:07.680 --> 00:23:10.200 Yes,<00:23:08.000> all<00:23:08.120> the<00:23:08.200> best. ``` ### Susan Odle, CEO of StorMagic: Why humanity matters in leadership URL: https://www.ceo.com/episodes/susan-odle-ceo-of-stormagic-why-humanity-matters-in-leadership/ Last updated: 2026-08-24T19:17:31.000Z # Susan Odle runs the company that keeps the lights on A city in Germany, with about 10,000 residents, runs its infrastructure on StorMagic software. So does the retailer that still needs to sell a Zippo lighter when the network goes down, and the warehouse that still needs to ship. StorMagic sells something unfashionable in enterprise software: nothing happening. Systems that stay up in places where the cloud can't be trusted to reach. "The edge is not the data center," Susan Odle said on the CEO.com Podcast. Odle became [CEO of StorMagic](https://stormagic.com/company/news/stormagic-appoints-susan-odle-as-chief-executive-officer-to-accelerate-next-phase-of-innovation-and-growth/?ref=ceo.com) in April 2025, eight months after joining as [chief growth officer](https://stormagic.com/company/news/stormagic-appoints-susan-odle-as-chief-growth-officer/?ref=ceo.com). The company is 20 years old. "We're definitely not an overnight success story," she said. Its customers are retail stores, warehouses, manufacturing sites, and utilities, many in locations without reliable broadband or 5G. "Customers shouldn't have to wake up at 2:00 a.m. worrying about whether their systems are down. Their IT teams should be able to sleep and focus on the business." After two decades of selling reliability, the company got handed its moment by someone else's chaos. Broadcom bought VMware, prices and licensing shifted, and businesses running virtualized infrastructure at the edge started looking for the exit. StorMagic launched SvHCI, a full-stack alternative, in June 2024\. The company says its qualified pipeline grew 600%. Odle's promotion followed. The bet has since produced numbers. StorMagic reported [36% growth in annual recurring revenue](https://www.prnewswire.com/news-releases/stormagic-marks-20-years-of-edge-innovation-as-demand-grows-for-virtualization-alternatives-302741307.html?ref=ceo.com) for the fiscal year that ended in March 2026\. In July, the company announced that Sheetz is [replacing VMware across more than 830 stores](https://stormagic.com/company/news/sheetz-chooses-stormagic-svhci-to-replace-vmware-across-830-retail-stores/?ref=ceo.com) with SvHCI, migrating roughly 200 stores a month remotely on the Dell servers already in each location. Sheetz was already a customer, running StorMagic storage underneath VMware. Now the VMware layer is coming out. Odle had run companies before. Founder and CEO of 8020CS. COO of BDO Lixar, where she led a pandemic-era turnaround to hit earnout targets that a global pandemic did not soften. VP of operations at GFI Software and Youi.TV. The Software Report put her on its [Top 50 Women Leaders in SaaS list in 2020](https://theaisoftwarereport.com/the-top-50-women-leaders-in-saas-of-2020/?ref=ceo.com), and she wrote a book on change management called "Successful Change." Her mornings are analog. Meditation first, every day, non-negotiable. Then she writes in a physical notepad the conversations she cannot let slip. Before she shreds her old notes, she reads back through the stack looking for patterns she missed. StorMagic closed its offices during COVID and never reopened them. The company is fully remote, with employees in 11 countries, and Odle treats that as a design problem rather than a perk. Anyone in the company can book time with her. Anonymous channels exist for hard questions. There are deliberate in-person meetups, including one in the UK recently and one in Canada. "Ignoring culture is a management strategy whether people realize it or not," she said. Her leadership philosophy comes down to a claim that still counts as contrarian in some rooms: kindness and ambition are not opposites. She points to Jim Collins and Level 5 leadership. "You can be kind and still be highly driven," she said. "There's this stereotype that leaders have to be aggressive, ruthless, and constantly operating from an 'eat or be eaten' mentality. I don't believe that at all." She has worked inside cutthroat cultures, mostly private equity-backed, and won't go back. She also thinks the market is settling the argument for her. COVID changed people. Gen Z has no patience for the 1990s playbook. On AI, she is a skeptic of the framing, not the technology. ChatGPT convinced consumers that AI is one thing. It is many things, she argues, and operational AI in particular depends entirely on whether a company's underlying data can be trusted, which at most companies it cannot. "Unless you're a massive AI company, it's almost impossible to keep up with the pace of change," she said. StorMagic is deciding what to build and what to partner on. Carefully. Tariffs don't hit a software company directly. They hit the servers her software runs on, so customers are stretching hardware fleets from five years to seven instead of refreshing. StorMagic runs on virtually any x86 server, which turns that caution into a sales pitch: modernize the software, keep the metal. Odle has since named hardware scarcity and rising equipment costs, alongside the Broadcom acquisition, as the two conditions pushing customers toward alternatives. Every CEO.com Podcast conversation ends with the same question, built on the belief that the chances one gives matter as much as the chances one takes. Odle named Jan Kaminski, CEO of FastLane Technologies, her third job in tech. Kaminski gave her the channel sales team, her first real management job in the industry. Bookings went from $1 million to $10 million in 18 months. [Quest Software acquired FastLane](https://www.sec.gov/Archives/edgar/data/1088033/000119312504041892/d10k.htm?ref=ceo.com) in September 2000, in a deal [reported at roughly $100 million](https://www.lexpert.ca/big-deals/quest-software-acquires-fastlane-technologies/344138?ref=ceo.com). "Jan saw something in me and rearranged the chessboard because he believed in my potential," she said. "That changed everything for me." ```chapters 00:00:00 Introduction and Background 00:00:32 Joining StoreMagic 00:01:08 StoreMagic's Edge Solutions 00:02:41 Democratizing Business 00:03:23 StoreMagic's Stability and Reliability 00:04:09 Transition from CGO to CEO 00:06:05 Daily Routine and Meditation 00:07:43 Importance of Notepads 00:08:41 Company Culture and Remote Work 00:10:33 Management Strategy and Culture 00:12:41 Reading Recommendations 00:14:19 Changing Management Paradigms 00:15:03 AI and Operational Data 00:17:45 AI Implementation Strategy 00:18:24 Market and Economic Impact 00:21:00 Leadership Qualities 00:23:16 Reflecting on Opportunities Given 00:25:00 Closing Remarks and Future Topics ``` ```vtt WEBVTT 00:00:00.000 --> 00:00:02.160 Susan,<00:00:00.600> thank<00:00:00.800> you<00:00:00.840> so<00:00:00.960> much<00:00:01.160> for<00:00:01.280> coming<00:00:01.560> on<00:00:01.640> the<00:00:01.760> show. 00:00:02.160 --> 00:00:04.200 You're<00:00:02.540> the<00:00:02.920> CEO<00:00:03.300> of<00:00:03.680> StorMagic. 00:00:04.200 --> 00:00:10.120 You're<00:00:04.499> also<00:00:04.798> on<00:00:05.097> the<00:00:05.396> board.<00:00:05.695> Give<00:00:05.994> us<00:00:06.293> a<00:00:06.592> sense<00:00:06.891> for<00:00:07.189> how<00:00:07.488> you<00:00:07.787> became<00:00:08.086> CEO<00:00:08.385> of<00:00:08.684> StorMagic<00:00:08.983> and<00:00:09.282> what<00:00:09.581> StorMagic<00:00:09.880> is. 00:00:10.120 --> 00:00:13.000 Let's<00:00:10.320> start<00:00:10.520> there.<00:00:10.720> <00:00:10.920> Hi<00:00:11.120> Clinton.<00:00:11.320> Thanks<00:00:11.520> for<00:00:11.720> having<00:00:11.920> me<00:00:12.120> on<00:00:12.320> the<00:00:12.520> podcast. 00:00:13.000 --> 00:00:20.880 It's<00:00:13.445> great<00:00:13.890> to<00:00:14.335> be<00:00:14.780> here.<00:00:15.225> Uh,<00:00:15.670> so<00:00:16.115> StorMagic,<00:00:16.560> we<00:00:17.005> specialize<00:00:17.450> in<00:00:17.895> simple<00:00:18.340> virtualization<00:00:18.785> solutions<00:00:19.230> for<00:00:19.675> the<00:00:20.120> edge. 00:00:20.880 --> 00:00:27.400 And<00:00:21.040> really<00:00:21.240> what<00:00:21.360> that<00:00:21.560> means<00:00:21.840> is<00:00:21.960> we<00:00:22.080> help<00:00:22.280> our<00:00:22.400> customers<00:00:22.880> keep<00:00:23.080> their<00:00:23.240> applications<00:00:24.040> up<00:00:24.200> and<00:00:24.320> running<00:00:24.720> in<00:00:24.880> whatever<00:00:25.320> vertical<00:00:25.680> market<00:00:26.120> they<00:00:26.240> may<00:00:26.440> be<00:00:26.680> in. 00:00:27.400 --> 00:00:30.360 So<00:00:27.520> they<00:00:27.640> can<00:00:27.800> forget<00:00:28.120> about<00:00:28.440> infrastructure<00:00:29.160> and<00:00:29.240> just<00:00:29.440> focus<00:00:29.760> on<00:00:29.880> their<00:00:29.960> business. 00:00:30.360 --> 00:00:33.720 That's<00:00:30.633> what<00:00:30.905> we<00:00:31.178> do.<00:00:31.451> Um,<00:00:31.724> and<00:00:31.996> so<00:00:32.269> how<00:00:32.542> did<00:00:32.815> I<00:00:33.087> join<00:00:33.360> StorMagic? 00:00:33.720 --> 00:00:36.640 I<00:00:33.760> joined<00:00:34.080> last<00:00:34.560> year<00:00:34.920> as<00:00:35.200> Chief<00:00:35.440> Growth<00:00:35.680> Officer. 00:00:36.640 --> 00:00:43.880 Uh,<00:00:36.857> about<00:00:37.073> a<00:00:37.290> year<00:00:37.506> and<00:00:37.723> a<00:00:37.939> half<00:00:38.156> ago,<00:00:38.372> and<00:00:38.589> my<00:00:38.806> job<00:00:39.022> was<00:00:39.239> really<00:00:39.455> to<00:00:39.672> come<00:00:39.888> in<00:00:40.105> and<00:00:40.321> help<00:00:40.538> the<00:00:40.754> company<00:00:40.971> have<00:00:41.188> a<00:00:41.404> bit<00:00:41.621> of<00:00:41.837> a<00:00:42.054> broader<00:00:42.270> aperture<00:00:42.487> on<00:00:42.703> the<00:00:42.920> possibilities 00:00:43.880 --> 00:00:52.240 for<00:00:44.040> growth<00:00:44.360> in<00:00:44.440> the<00:00:44.520> marketplace.<00:00:45.880> Uh,<00:00:45.960> and<00:00:46.080> then<00:00:46.240> I<00:00:46.320> was,<00:00:46.880> um,<00:00:47.360> you<00:00:47.480> know,<00:00:47.800> I,<00:00:48.040> I<00:00:48.120> guess<00:00:48.360> offered<00:00:48.640> the<00:00:48.720> position<00:00:49.160> to<00:00:49.280> assume<00:00:49.760> the<00:00:49.880> role<00:00:50.120> of<00:00:50.240> CEO<00:00:51.320> earlier<00:00:51.720> this<00:00:51.960> year 00:00:52.240 --> 00:00:58.880 with<00:00:52.440> the<00:00:52.520> same<00:00:52.840> mandate,<00:00:53.640> but<00:00:53.840> now<00:00:54.160> I<00:00:54.280> have<00:00:54.560> accountability<00:00:55.240> to<00:00:55.320> the<00:00:55.440> board<00:00:55.840> and,<00:00:56.080> and<00:00:56.240> the<00:00:56.320> mandate<00:00:56.760> of<00:00:56.920> product<00:00:57.360> and<00:00:57.480> all<00:00:57.600> the<00:00:57.720> other<00:00:57.840> different<00:00:58.120> functions<00:00:58.560> across 00:00:58.880 --> 00:01:01.640 the<00:00:59.000> business.<00:00:59.760> The<00:00:59.880> mandate<00:01:00.320> is<00:01:00.480> really<00:01:00.720> the<00:01:00.800> same,<00:01:01.360> right? 00:01:01.640 --> 00:01:08.720 It's<00:01:01.880> find,<00:01:02.880> uh,<00:01:03.320> new<00:01:03.640> routes<00:01:03.960> to<00:01:04.080> market<00:01:04.720> to<00:01:05.239> grow<00:01:05.560> our<00:01:05.680> business,<00:01:06.720> grow<00:01:06.920> as<00:01:07.000> a<00:01:07.040> company,<00:01:07.560> and<00:01:07.720> expand<00:01:08.200> our<00:01:08.280> brand. 00:01:08.720 --> 00:01:13.200 <00:01:08.920> So<00:01:09.160> let's<00:01:09.280> go<00:01:09.320> a<00:01:09.480> little<00:01:09.640> bit<00:01:10.200> deeper<00:01:11.000> on,<00:01:11.240> uh,<00:01:11.480> what<00:01:11.760> StorMagic<00:01:12.200> does. 00:01:13.200 --> 00:01:20.400 So<00:01:13.360> you're<00:01:13.520> simplifying<00:01:14.200> how<00:01:14.800> organizations<00:01:15.440> kind<00:01:15.640> of<00:01:15.720> store<00:01:16.800> and<00:01:16.960> protect<00:01:17.440> and<00:01:17.560> manage<00:01:17.920> their<00:01:18.120> data<00:01:18.920> in<00:01:19.080> a<00:01:19.160> remote<00:01:19.680> work<00:01:19.920> environment. 00:01:20.400 --> 00:01:23.640 Is<00:01:20.606> that<00:01:20.812> accurate?<00:01:21.018> <00:01:21.225> That's<00:01:21.431> correct.<00:01:21.637> So<00:01:21.843> the<00:01:22.049> edge<00:01:22.255> is<00:01:22.462> not<00:01:22.668> the<00:01:22.874> data<00:01:23.080> center. 00:01:23.640 --> 00:01:31.640 So<00:01:23.840> if<00:01:24.040> you<00:01:24.120> think<00:01:24.400> about<00:01:25.000> enterprise<00:01:25.520> data<00:01:25.760> centers,<00:01:26.280> you,<00:01:26.440> you<00:01:26.520> know,<00:01:26.680> people<00:01:27.000> see<00:01:27.240> the<00:01:27.360> monolithic<00:01:28.560> computer<00:01:29.000> rooms<00:01:29.480> with<00:01:29.680> racks<00:01:30.080> and<00:01:30.200> racks<00:01:30.520> of<00:01:30.640> servers. 00:01:31.640 --> 00:01:35.200 That<00:01:31.880> is<00:01:32.000> a<00:01:32.080> very<00:01:32.440> different<00:01:32.960> application<00:01:33.640> of<00:01:33.760> virtualized<00:01:34.400> infrastructure. 00:01:35.200 --> 00:01:42.920 And<00:01:35.320> when<00:01:35.480> I<00:01:35.560> say<00:01:35.800> virtualized<00:01:36.520> infrastructure,<00:01:37.240> I<00:01:37.360> mean<00:01:38.040> from<00:01:38.200> our<00:01:38.320> perspective,<00:01:38.960> it's<00:01:39.120> hyper-converged<00:01:39.960> storage,<00:01:41.040> hyper-converged<00:01:41.760> infrastructure,<00:01:42.520> which<00:01:42.720> is 00:01:42.920 --> 00:01:48.920 everything<00:01:43.360> from<00:01:43.520> the<00:01:43.640> hypervisor,<00:01:44.960> the<00:01:45.120> operating<00:01:45.640> system,<00:01:46.560> to<00:01:46.720> the<00:01:46.800> networking<00:01:47.400> layer,<00:01:47.760> and<00:01:47.960> the<00:01:48.000> storage<00:01:48.520> layer. 00:01:48.920 --> 00:01:53.920 And<00:01:49.120> so<00:01:49.280> we<00:01:49.520> purpose-built<00:01:50.880> our<00:01:51.080> technology<00:01:51.960> to<00:01:52.120> address<00:01:52.720> the<00:01:52.880> needs<00:01:53.200> at<00:01:53.320> the<00:01:53.480> edge. 00:01:53.920 --> 00:02:03.520 And<00:01:54.080> the<00:01:54.200> edge<00:01:54.520> is<00:01:54.720> a<00:01:54.800> retail<00:01:55.200> store,<00:01:56.320> a<00:01:56.440> manufacturing<00:01:57.360> site,<00:01:57.920> a<00:01:58.560> warehouse,<00:02:00.560> a<00:02:00.840> power<00:02:01.360> supply<00:02:01.880> company<00:02:02.960> where 00:02:03.520 --> 00:02:10.880 you<00:02:03.840> cannot<00:02:04.320> be<00:02:04.479> assured<00:02:05.479> that<00:02:05.800> your<00:02:06.000> network<00:02:06.440> connectivity<00:02:07.800> is<00:02:07.960> what<00:02:08.119> it<00:02:08.200> would<00:02:08.360> be<00:02:08.880> in<00:02:09.039> a<00:02:09.080> big<00:02:09.320> city. 00:02:10.880 --> 00:02:14.360 5G<00:02:11.560> may<00:02:11.760> not<00:02:12.160> exist.<00:02:12.800> 3G<00:02:13.520> may<00:02:13.720> not<00:02:13.959> exist. 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example. 00:02:31.920 --> 00:02:38.520 <00:02:32.240> That's<00:02:32.560> remarkable.<00:02:32.880> What<00:02:33.200> a,<00:02:33.520> what<00:02:33.840> a<00:02:34.160> company.<00:02:34.480> Like<00:02:34.800> honestly,<00:02:35.120> you're<00:02:35.440> kind<00:02:35.760> of<00:02:36.080> democratizing<00:02:36.400> entrepreneurship<00:02:36.720> and,<00:02:37.040> and<00:02:37.360> business. 00:02:38.520 --> 00:02:41.040 So<00:02:38.640> that<00:02:38.760> it's<00:02:38.920> not<00:02:39.120> just<00:02:39.320> the<00:02:39.440> major<00:02:39.760> corporations,<00:02:40.520> right? 00:02:41.040 --> 00:02:44.040 <00:02:41.219> Well,<00:02:41.397> that's,<00:02:41.576> you<00:02:41.755> know,<00:02:41.933> we're<00:02:42.112> ahead<00:02:42.291> of<00:02:42.469> our<00:02:42.648> time.<00:02:42.827> We've<00:02:43.005> been<00:02:43.184> around<00:02:43.363> for<00:02:43.541> 20<00:02:43.720> years. 00:02:44.040 --> 00:02:47.600 So<00:02:44.160> we're<00:02:44.280> not,<00:02:45.400> we're<00:02:45.520> not<00:02:45.680> an<00:02:45.800> upstart. 00:02:47.600 --> 00:02:56.200 We've,<00:02:48.320> from<00:02:48.560> the<00:02:48.680> day<00:02:49.040> that<00:02:49.240> we<00:02:49.480> wrote<00:02:49.720> a<00:02:49.760> piece<00:02:50.000> of<00:02:50.120> code,<00:02:50.520> it<00:02:50.640> was<00:02:50.840> to<00:02:51.560> address<00:02:52.040> this<00:02:52.320> need<00:02:52.880> to<00:02:53.000> say,<00:02:54.120> you<00:02:54.640> know,<00:02:54.920> I<00:02:55.040> am<00:02:55.200> not<00:02:55.560> connected<00:02:56.080> to 00:02:56.200 --> 00:03:05.040 a<00:02:56.240> data<00:02:56.560> center.<00:02:57.080> I<00:02:57.160> don't<00:02:57.520> have<00:02:58.280> a<00:02:58.360> million<00:02:58.680> dollars<00:02:59.160> a<00:02:59.200> month<00:02:59.519> to<00:02:59.640> burn<00:03:00.080> on,<00:03:00.480> on<00:03:00.680> infrastructure,<00:03:02.000> but<00:03:02.160> I<00:03:02.239> need<00:03:02.880> when<00:03:03.040> a<00:03:03.080> customer<00:03:03.560> comes<00:03:03.840> into<00:03:04.040> my<00:03:04.200> store, 00:03:05.040 --> 00:03:08.200 I<00:03:05.120> need<00:03:05.360> to<00:03:05.440> sell<00:03:05.760> that<00:03:06.120> Zippo<00:03:06.440> lighter,<00:03:07.360> right? 00:03:08.200 --> 00:03:16.320 Or,<00:03:09.480> you<00:03:09.560> know,<00:03:09.720> if<00:03:09.920> I'm<00:03:10.760> a<00:03:10.800> distributor<00:03:11.600> of<00:03:12.680> fine<00:03:13.040> food<00:03:13.320> products,<00:03:13.800> I<00:03:13.880> need<00:03:14.120> to<00:03:14.239> make<00:03:14.480> sure<00:03:14.920> that<00:03:15.640> that<00:03:15.880> order<00:03:16.080> is<00:03:16.200> going 00:03:16.320 --> 00:03:20.160 to<00:03:16.400> go<00:03:16.600> out<00:03:16.760> in<00:03:16.920> time.<00:03:17.840> The<00:03:17.920> supply<00:03:18.320> chain<00:03:18.800> must<00:03:19.160> flow. 00:03:20.160 --> 00:03:28.880 We've<00:03:20.360> got<00:03:21.480> a<00:03:21.600> city<00:03:21.959> in<00:03:22.120> Germany<00:03:23.000> of<00:03:23.200> 10,000<00:03:23.800> people<00:03:24.280> that<00:03:24.440> runs<00:03:24.680> the<00:03:24.760> entire<00:03:25.000> infrastructure<00:03:26.560> on<00:03:26.760> our<00:03:26.880> technology<00:03:27.640> and<00:03:27.760> our<00:03:27.880> storage<00:03:28.280> solutions. 00:03:28.880 --> 00:03:32.120 So<00:03:28.959> they,<00:03:29.320> you<00:03:29.360> know,<00:03:29.480> we<00:03:29.600> protect<00:03:29.959> their<00:03:30.080> data,<00:03:30.320> we<00:03:30.440> make<00:03:30.600> sure<00:03:30.760> it's<00:03:30.880> available. 00:03:32.120 --> 00:03:37.480 Um,<00:03:32.560> and<00:03:32.720> that's<00:03:33.040> about,<00:03:33.840> you<00:03:33.959> know,<00:03:34.400> making<00:03:34.680> sure<00:03:34.840> the<00:03:34.959> lights<00:03:35.239> are<00:03:35.400> on<00:03:35.600> when<00:03:35.760> your<00:03:35.880> kids<00:03:36.160> come<00:03:36.320> home<00:03:36.519> and<00:03:36.640> you're<00:03:36.760> having<00:03:37.040> supper. 00:03:37.480 --> 00:03:40.800 So,<00:03:38.480> you<00:03:38.560> know,<00:03:38.640> we've<00:03:38.760> been<00:03:38.920> around<00:03:39.239> a<00:03:39.280> long<00:03:39.519> time<00:03:39.760> because<00:03:39.959> our<00:03:40.080> tech<00:03:40.360> is<00:03:40.440> stable. 00:03:40.800 --> 00:03:49.160 It<00:03:40.920> just<00:03:41.120> runs,<00:03:41.440> it<00:03:41.519> just<00:03:41.800> works.<00:03:42.880> And<00:03:43.080> what<00:03:43.200> we<00:03:43.320> do<00:03:43.600> is,<00:03:43.840> is<00:03:44.000> very<00:03:44.360> small<00:03:45.080> in,<00:03:45.239> in<00:03:45.360> terms<00:03:45.680> of<00:03:45.760> its<00:03:46.000> breadth,<00:03:46.480> but<00:03:46.640> we're,<00:03:46.959> it,<00:03:47.200> we're<00:03:47.360> very<00:03:47.800> good<00:03:48.040> at<00:03:48.239> it,<00:03:48.560> and<00:03:48.840> that's 00:03:49.160 --> 00:03:58.040 where<00:03:49.280> we<00:03:49.440> intend<00:03:49.760> to<00:03:49.840> stay,<00:03:50.080> and<00:03:50.200> it's,<00:03:50.400> it's<00:03:50.519> just<00:03:50.680> very<00:03:50.880> simply,<00:03:52.080> if<00:03:52.280> you<00:03:52.400> put<00:03:52.560> our<00:03:52.680> storage<00:03:53.040> solutions<00:03:53.600> in<00:03:53.760> or<00:03:53.880> a<00:03:53.920> hyper-converged<00:03:54.680> solution,<00:03:55.840> um,<00:03:56.640> it<00:03:56.800> will<00:03:57.080> run. 00:03:58.040 --> 00:04:03.480 You<00:03:58.200> don't<00:03:58.440> have<00:03:58.600> to<00:03:58.720> think<00:03:58.920> about<00:03:59.160> whether<00:03:59.320> you're<00:03:59.440> going<00:03:59.600> to<00:03:59.680> have<00:03:59.800> to<00:03:59.880> fly<00:04:00.120> back<00:04:00.760> and<00:04:01.200> turn<00:04:01.440> something<00:04:01.760> back<00:04:02.080> on<00:04:02.280> at<00:04:02.400> 2:00<00:04:02.920> in<00:04:03.000> the<00:04:03.080> morning. 00:04:03.480 --> 00:04:07.240 Your<00:04:03.680> IT,<00:04:04.440> IT<00:04:05.120> staff<00:04:05.440> can,<00:04:05.880> can<00:04:06.040> sleep. 00:04:07.240 --> 00:04:09.760 Focus<00:04:07.560> on<00:04:07.680> your<00:04:07.760> business,<00:04:08.120> let<00:04:08.280> us<00:04:08.400> focus<00:04:08.720> on<00:04:08.840> your<00:04:08.959> infrastructure. 00:04:09.760 --> 00:04:14.320 You<00:04:09.840> mentioned,<00:04:11.040> uh,<00:04:11.120> you<00:04:11.360> joined<00:04:11.760> in<00:04:11.840> 2024<00:04:12.760> as<00:04:12.959> the<00:04:13.080> Chief<00:04:13.440> Growth<00:04:13.800> Officer. 00:04:14.320 --> 00:04:17.280 You're<00:04:14.688> now<00:04:15.056> the<00:04:15.424> CEO.<00:04:15.792> <00:04:16.160> Yeah. 00:04:17.280 --> 00:04:21.560 Give<00:04:17.400> me<00:04:17.519> a<00:04:17.560> sense<00:04:17.840> for<00:04:18.000> how<00:04:18.400> like<00:04:18.680> your<00:04:18.799> day-to-day<00:04:19.359> changed<00:04:19.959> between<00:04:20.280> those<00:04:20.519> two<00:04:20.680> roles. 00:04:21.560 --> 00:04:26.080 Yeah.<00:04:22.000> Well,<00:04:22.280> as<00:04:22.480> Chief<00:04:22.760> Growth<00:04:23.080> Officer,<00:04:24.760> it,<00:04:24.960> it's<00:04:25.120> interesting. 00:04:26.080 --> 00:04:28.840 I,<00:04:26.360> I've<00:04:26.560> been<00:04:26.760> a<00:04:26.800> COO<00:04:27.480> in<00:04:27.600> a<00:04:27.640> past<00:04:28.080> life<00:04:28.320> as<00:04:28.520> well. 00:04:28.840 --> 00:04:38.000 So,<00:04:29.640> that<00:04:29.800> there's<00:04:29.960> a<00:04:30.040> lot<00:04:30.280> of<00:04:30.400> overlap<00:04:30.960> between<00:04:31.520> a<00:04:31.600> CEO,<00:04:32.400> a<00:04:32.480> COO,<00:04:33.440> and<00:04:33.560> a<00:04:33.600> CGO<00:04:34.919> because<00:04:35.200> it's<00:04:35.360> not,<00:04:35.760> it's<00:04:35.919> not<00:04:36.080> a<00:04:36.160> siloed<00:04:36.919> job. 00:04:38.000 --> 00:04:47.400 There<00:04:38.440> has<00:04:38.760> to<00:04:38.880> be<00:04:39.040> alignment<00:04:39.800> between<00:04:40.400> marketing,<00:04:41.360> product,<00:04:42.240> sales,<00:04:43.800> finance,<00:04:44.520> and<00:04:44.680> how<00:04:44.880> do<00:04:45.040> you<00:04:45.320> bring<00:04:45.640> all<00:04:45.800> of<00:04:45.919> that<00:04:46.160> together 00:04:47.400 --> 00:04:55.280 around<00:04:48.240> multiple<00:04:49.040> strategic<00:04:49.640> initiatives<00:04:51.000> that<00:04:51.160> can<00:04:51.280> drive<00:04:51.640> growth,<00:04:52.120> long-term<00:04:52.680> sustainable<00:04:53.200> growth<00:04:53.560> for,<00:04:54.640> for<00:04:54.720> the<00:04:54.800> business. 00:04:55.280 --> 00:05:02.919 So,<00:04:55.800> in<00:04:55.919> effect,<00:04:56.720> um,<00:04:57.400> you<00:04:57.520> know,<00:04:57.640> obviously<00:04:58.040> I<00:04:58.120> have<00:04:58.320> more<00:04:58.480> of<00:04:58.560> a<00:04:58.600> direct<00:04:58.919> mandate<00:04:59.360> now<00:04:59.640> as<00:04:59.800> well<00:04:59.960> as<00:05:00.160> as<00:05:00.320> far<00:05:00.440> as<00:05:00.560> product<00:05:00.919> and<00:05:01.000> engineering<00:05:01.480> goes<00:05:01.800> and<00:05:02.000> where<00:05:02.360> the<00:05:02.480> direction 00:05:02.919 --> 00:05:11.000 our<00:05:03.000> product<00:05:03.360> is<00:05:03.480> taking.<00:05:04.640> But,<00:05:04.720> the<00:05:04.800> mandate<00:05:05.240> is<00:05:05.400> really<00:05:05.919> the<00:05:06.040> same,<00:05:07.280> uh,<00:05:07.600> with<00:05:08.800> obviously<00:05:09.240> significantly<00:05:09.919> more<00:05:10.120> accountability<00:05:10.800> to<00:05:10.919> the 00:05:11.000 --> 00:05:20.840 board.<00:05:12.320> And,<00:05:12.600> uh,<00:05:12.760> and<00:05:12.880> that's<00:05:13.080> going<00:05:13.320> very<00:05:13.600> well,<00:05:13.880> you<00:05:13.960> know,<00:05:14.120> I<00:05:14.200> think<00:05:14.840> when<00:05:15.000> you<00:05:15.040> think<00:05:15.240> about<00:05:15.480> your<00:05:15.600> constituents,<00:05:17.560> it's<00:05:17.760> everybody<00:05:18.240> from<00:05:18.480> your<00:05:18.640> front-line<00:05:19.280> workers 00:05:20.840 --> 00:05:23.640 all<00:05:21.000> the<00:05:21.080> way<00:05:21.240> to<00:05:21.360> the<00:05:21.440> board,<00:05:22.120> right?<00:05:23.120> Uh,<00:05:23.280> Mhm. 00:05:23.640 --> 00:05:32.000 It<00:05:23.720> is<00:05:23.880> about<00:05:24.240> buying.<00:05:24.880> You<00:05:25.080> have<00:05:25.400> to,<00:05:27.120> you<00:05:27.440> have<00:05:27.600> to<00:05:27.720> do<00:05:27.919> enough<00:05:28.320> work<00:05:28.680> to<00:05:28.840> look<00:05:29.160> at<00:05:29.960> these,<00:05:30.560> the,<00:05:30.760> the<00:05:30.919> big<00:05:31.240> decisions<00:05:31.880> you're 00:05:32.000 --> 00:05:40.640 making<00:05:32.440> for<00:05:32.560> the<00:05:32.680> business<00:05:34.120> and<00:05:34.760> do<00:05:34.960> enough<00:05:35.360> homework<00:05:36.000> and<00:05:36.120> have<00:05:36.240> enough<00:05:36.600> of<00:05:36.720> a<00:05:36.800> case<00:05:37.160> behind<00:05:37.720> it<00:05:38.960> that<00:05:39.080> the<00:05:39.200> narrative<00:05:39.760> carries<00:05:40.440> from 00:05:40.640 --> 00:05:48.640 the<00:05:40.760> front-line<00:05:41.280> people<00:05:41.760> that<00:05:41.960> are,<00:05:42.840> uh,<00:05:43.040> doing<00:05:43.320> whatever<00:05:43.680> it<00:05:43.800> might<00:05:43.960> be<00:05:44.120> in<00:05:44.240> their<00:05:44.400> role<00:05:44.919> up<00:05:45.080> to<00:05:45.200> the<00:05:45.320> board<00:05:45.800> who's<00:05:46.000> going<00:05:46.240> to<00:05:46.320> be<00:05:46.520> supportive<00:05:47.200> of<00:05:47.360> that<00:05:47.680> decision<00:05:48.240> to<00:05:48.400> move 00:05:48.640 --> 00:05:55.880 in<00:05:48.760> a<00:05:48.800> certain<00:05:49.160> direction.<00:05:49.760> So,<00:05:50.840> I<00:05:51.040> think,<00:05:51.480> um,<00:05:51.840> it's<00:05:52.000> an<00:05:52.120> expanded<00:05:52.760> responsibility,<00:05:53.640> but<00:05:53.800> at<00:05:54.080> the<00:05:54.200> end<00:05:54.360> 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up<00:06:09.960> first<00:06:10.200> thing<00:06:10.360> in<00:06:10.400> the<00:06:10.480> morning. 00:06:10.880 --> 00:06:17.960 That's<00:06:11.120> my<00:06:11.200> number<00:06:11.480> one.<00:06:12.160> Uh,<00:06:13.240> you<00:06:13.280> know,<00:06:13.440> being<00:06:13.640> a<00:06:13.720> CEO<00:06:14.560> or<00:06:14.760> being<00:06:15.000> in<00:06:15.080> the<00:06:15.160> C-suite<00:06:15.680> at<00:06:15.800> all,<00:06:16.000> but<00:06:16.120> certainly<00:06:16.440> being<00:06:16.600> a<00:06:16.680> CEO,<00:06:17.080> it's<00:06:17.200> a<00:06:17.240> demanding<00:06:17.680> job. 00:06:17.960 --> 00:06:22.480 It's<00:06:18.080> 24/7.<00:06:19.160> You<00:06:19.280> never<00:06:19.480> know<00:06:19.560> what's<00:06:19.720> going<00:06:19.840> to<00:06:19.919> get<00:06:20.040> thrown<00:06:20.280> at<00:06:20.440> you<00:06:20.600> in,<00:06:20.840> in<00:06:21.000> a<00:06:21.040> given<00:06:21.320> minute. 00:06:22.480 --> 00:06:27.480 So,<00:06:22.640> I<00:06:22.720> think<00:06:23.160> whether<00:06:23.520> you<00:06:23.640> choose,<00:06:23.960> people<00:06:24.200> choose<00:06:24.440> to<00:06:24.560> meditate<00:06:25.040> or<00:06:25.120> they<00:06:25.280> have,<00:06:25.600> you<00:06:25.680> know,<00:06:26.160> I<00:06:26.240> have<00:06:26.400> never<00:06:26.640> been<00:06:26.800> a<00:06:26.840> 5:00<00:06:27.200> a.m. 00:06:27.480 --> 00:06:32.560 get<00:06:27.680> up<00:06:27.880> and<00:06:28.120> work<00:06:28.400> out<00:06:28.640> kind<00:06:28.800> of<00:06:28.880> person.<00:06:29.280> Some,<00:06:29.680> for<00:06:29.840> some<00:06:30.040> people<00:06:30.360> that's<00:06:30.720> the<00:06:30.840> thing<00:06:31.000> that<00:06:31.160> they<00:06:31.280> like<00:06:31.480> to<00:06:31.600> do. 00:06:32.560 --> 00:06:41.080 But,<00:06:32.640> I<00:06:32.720> find<00:06:33.000> meditation<00:06:33.640> is<00:06:33.760> incredibly<00:06:34.480> grounding<00:06:35.280> for<00:06:35.440> the<00:06:35.520> day<00:06:35.720> and<00:06:35.840> it<00:06:35.960> just,<00:06:36.360> it<00:06:36.480> just<00:06:36.960> puts<00:06:37.240> you<00:06:37.400> in<00:06:37.520> a,<00:06:37.800> in<00:06:37.880> a<00:06:37.960> nice<00:06:38.320> mindset<00:06:38.919> to<00:06:39.040> kind<00:06:39.240> of<00:06:39.320> absorb<00:06:39.880> what<00:06:40.960> or 00:06:41.080 --> 00:06:45.480 not<00:06:41.440> absorb<00:06:42.240> and<00:06:42.440> take,<00:06:42.720> you<00:06:42.800> know,<00:06:42.919> take<00:06:43.200> in<00:06:43.360> what's<00:06:43.560> coming<00:06:43.880> at<00:06:44.160> you,<00:06:44.280> but<00:06:44.440> not<00:06:44.600> react<00:06:45.160> to<00:06:45.280> it. 00:06:45.480 --> 00:06:49.000 So,<00:06:45.600> that's<00:06:45.760> number<00:06:45.960> one.<00:06:47.800> I<00:06:47.919> like<00:06:48.120> to<00:06:48.240> get<00:06:48.400> a<00:06:48.440> coffee. 00:06:49.000 --> 00:06:53.560 I<00:06:49.120> fast.<00:06:50.080> I,<00:06:50.360> I<00:06:50.440> have<00:06:50.640> a<00:06:50.960> routine<00:06:51.400> of<00:06:51.520> fasting<00:06:51.960> until<00:06:52.200> about<00:06:52.480> noon. 00:06:53.560 --> 00:06:58.120 Uh,<00:06:53.800> that<00:06:53.960> works<00:06:54.240> really<00:06:54.480> well<00:06:54.720> for<00:06:54.919> me<00:06:55.120> and<00:06:55.240> a<00:06:55.440> coffee<00:06:55.840> helps,<00:06:56.560> uh,<00:06:56.680> mitigate<00:06:57.040> your<00:06:57.160> hunger<00:06:57.560> response. 00:06:58.120 --> 00:07:00.320 So,<00:06:58.320> it's<00:06:58.480> just<00:06:58.680> a<00:06:58.720> nice<00:06:59.600> healthy<00:06:59.919> reset. 00:07:00.320 --> 00:07:07.000 So,<00:07:00.400> you<00:07:00.440> end<00:07:00.560> up<00:07:00.640> with<00:07:00.760> like<00:07:00.880> a<00:07:00.919> 16-hour<00:07:01.600> fast.<00:07:02.840> If<00:07:02.919> you<00:07:03.040> eat,<00:07:03.320> stop<00:07:03.600> eating<00:07:03.800> at<00:07:03.919> 7:00,<00:07:04.800> have<00:07:04.960> a<00:07:05.000> coffee<00:07:05.320> in<00:07:05.400> the<00:07:05.480> morning,<00:07:05.880> eat<00:07:06.000> around<00:07:06.280> noon. 00:07:07.000 --> 00:07:09.600 So,<00:07:07.080> I<00:07:07.160> find<00:07:07.440> that<00:07:07.720> works<00:07:08.040> really<00:07:08.320> well<00:07:08.520> for<00:07:08.800> me. 00:07:09.600 --> 00:07:13.240 And<00:07:09.720> then<00:07:09.840> from<00:07:10.000> a,<00:07:10.120> from<00:07:10.320> a<00:07:10.400> business<00:07:10.760> perspective,<00:07:11.320> I<00:07:11.400> definitely,<00:07:12.320> uh,<00:07:12.400> I<00:07:12.480> have<00:07:12.560> a<00:07:12.600> notepad. 00:07:13.240 --> 00:07:18.880 I'm<00:07:13.400> old<00:07:13.600> school<00:07:14.520> on<00:07:14.760> my,<00:07:15.160> my<00:07:15.360> desk<00:07:15.800> and<00:07:15.960> I,<00:07:16.200> what<00:07:16.560> must<00:07:17.640> I<00:07:17.760> address<00:07:18.240> today? 00:07:18.880 --> 00:07:26.360 And<00:07:19.040> that's<00:07:19.240> a<00:07:19.320> combination<00:07:20.000> of<00:07:20.840> conversations<00:07:21.600> that<00:07:21.720> I<00:07:21.760> need<00:07:21.960> to<00:07:22.080> have<00:07:22.440> with<00:07:23.360> people<00:07:23.680> that<00:07:23.840> might<00:07:24.000> be<00:07:24.080> external<00:07:24.800> as<00:07:24.960> well<00:07:25.120> as<00:07:25.240> internal. 00:07:26.360 --> 00:07:32.880 And<00:07:26.440> then<00:07:26.560> things<00:07:26.880> that<00:07:27.040> must<00:07:27.480> get<00:07:27.680> done.<00:07:28.560> And,<00:07:28.919> and<00:07:29.160> so,<00:07:29.640> I<00:07:29.760> make<00:07:30.040> sure<00:07:30.320> that<00:07:30.640> that,<00:07:30.960> that<00:07:31.240> is<00:07:31.400> front<00:07:31.720> and<00:07:31.880> center. 00:07:32.880 --> 00:07:40.000 And<00:07:33.040> if<00:07:33.160> it<00:07:33.280> gets<00:07:33.480> derailed<00:07:33.960> because<00:07:34.240> something<00:07:34.520> comes<00:07:34.720> up,<00:07:34.840> it<00:07:34.880> gets<00:07:35.040> 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everything.<00:09:15.120> I<00:09:15.280> truly<00:09:15.880> believe,<00:09:16.760> uh,<00:09:16.920> just<00:09:17.200> from<00:09:17.400> experience<00:09:18.040> and<00:09:18.160> just<00:09:18.400> this,<00:09:18.640> it's<00:09:18.839> how<00:09:19.040> I'm<00:09:19.200> wired. 00:09:20.000 --> 00:09:23.280 You<00:09:20.080> can<00:09:20.200> have<00:09:20.320> the<00:09:20.400> best<00:09:20.760> plan<00:09:21.480> in<00:09:21.640> the<00:09:21.760> world. 00:09:23.280 --> 00:09:32.720 If<00:09:23.440> you<00:09:23.560> don't<00:09:23.720> have<00:09:23.880> a<00:09:23.920> culture<00:09:24.440> where<00:09:24.600> people<00:09:24.960> feel<00:09:25.320> valued<00:09:26.200> and<00:09:27.480> the,<00:09:27.800> you<00:09:27.920> know,<00:09:28.400> I've,<00:09:28.680> in<00:09:28.920> my<00:09:29.160> mind<00:09:30.200> a<00:09:30.280> company<00:09:30.720> is<00:09:30.960> flat. 00:09:32.720 --> 00:09:36.400 Some<00:09:32.960> of<00:09:33.040> us<00:09:33.200> 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00:13:37.880 If<00:13:30.960> you're<00:13:31.120> humble,<00:13:31.760> you're<00:13:32.080> you're<00:13:32.280> probably<00:13:32.880> going<00:13:33.000> to<00:13:33.080> be<00:13:33.240> inclined<00:13:33.800> to<00:13:33.880> be<00:13:34.000> a<00:13:34.040> little<00:13:34.240> bit<00:13:34.360> more<00:13:34.560> empathetic<00:13:36.120> to<00:13:36.200> your<00:13:36.360> staff<00:13:36.760> and<00:13:36.880> to<00:13:37.000> your<00:13:37.160> customers. 00:13:37.880 --> 00:13:39.880 So,<00:13:38.640> you<00:13:38.760> know,<00:13:38.880> I'm<00:13:39.120> I'm<00:13:39.240> not<00:13:39.400> naive. 00:13:39.880 --> 00:13:48.440 There<00:13:40.560> There<00:13:40.720> are<00:13:40.840> cultures<00:13:41.560> in<00:13:41.720> business<00:13:42.800> that<00:13:42.960> are<00:13:43.040> very<00:13:43.320> openly,<00:13:44.880> um,<00:13:45.640> you<00:13:45.760> know,<00:13:45.960> if<00:13:46.120> you're<00:13:46.240> not<00:13:46.720> if<00:13:46.880> you're<00:13:47.000> 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growth<00:25:14.160> phase,<00:25:14.440> which<00:25:14.600> I<00:25:14.640> think<00:25:14.840> is,<00:25:15.400> is<00:25:15.640> really<00:25:15.920> great<00:25:16.400> and<00:25:16.520> interesting. 00:25:17.800 --> 00:25:23.400 Um,<00:25:18.080> not<00:25:18.280> that<00:25:18.600> CMO,<00:25:19.800> that's<00:25:20.000> still,<00:25:20.240> I<00:25:20.320> think,<00:25:20.560> a<00:25:20.600> valid<00:25:20.960> title<00:25:21.240> as<00:25:21.360> well,<00:25:21.560> but<00:25:21.760> I'd<00:25:21.880> love<00:25:22.040> to<00:25:22.120> talk<00:25:22.320> to<00:25:22.360> you<00:25:22.440> more<00:25:22.560> about<00:25:22.800> that. 00:25:23.400 --> 00:25:27.400 Absolutely.<00:25:24.000> But<00:25:24.200> thank<00:25:24.480> you,<00:25:24.640> thank<00:25:25.000> you<00:25:25.080> so<00:25:25.280> much<00:25:25.560> for<00:25:25.680> coming<00:25:26.000> on,<00:25:26.400> Susan. 00:25:27.400 --> 00:25:30.040 What<00:25:27.600> a<00:25:27.640> pleasure<00:25:28.320> and<00:25:28.720> let's<00:25:28.880> have<00:25:29.000> you<00:25:29.080> back<00:25:29.280> on<00:25:29.480> seriously. 00:25:30.040 --> 00:25:33.000 I'd<00:25:30.160> love<00:25:30.360> to.<00:25:30.840> I'd<00:25:30.960> love<00:25:31.120> to.<00:25:31.480> It<00:25:31.520> was<00:25:31.640> a<00:25:31.680> great<00:25:31.800> conversation,<00:25:32.360> anytime<00:25:32.720> Clint. 00:25:33.000 --> 00:25:35.200 Thank<00:25:33.200> you. ``` ### The machine is now the first audience URL: https://www.ceo.com/blog/the-machine-is-now-the-first-audience/ Last updated: 2026-08-14T00:17:51.000Z For most of the internet era, the path between a brand and its customer ran through a list of ten blue links. A person typed a question into Google, scanned the results, and clicked on one. The company that ranked highest won the visit. The one ranked eleventh might as well not have existed. [Gartner predicted](https://searchengineland.com/search-engine-traffic-2026-prediction-437650?ref=ceo.com) in early 2024 that traditional search engine volume would drop 25 percent by 2026 as AI chatbots absorbed more queries. By 2025, the data was already ahead of the prediction. [60 percent of Google searches now end without any click to a website](https://thedigitalbloom.com/learn/2025-organic-traffic-crisis-analysis-report/?ref=ceo.com). When AI Overviews appear in results, [that zero-click rate climbs to 93 percent](https://www.jarredsmith.com/blog/the-30-problem-why-most-brands-are-invisible-to-ai-search-in-2026-and-what-the-data-says-you-should-do-about-it?ref=ceo.com). People are no longer clicking through links to find an answer. They are asking for the answer directly, and a machine is delivering it. The machine decides which brands to mention. Most companies have not yet understood what that means for them. Eric Stine has been watching this shift come for a long time. He is the CEO of [Sitecore](https://www.sitecore.com/?ref=ceo.com), the digital experience platform that has spent 25 years helping major brands manage how they reach, engage, and serve their audiences across every channel. In a [recent CEO.com interview](https://www.ceo.com/c/podcast/sitecore-ceo-eric-stine-on-ai-answer-engines-and-why-clarity-is-currency), he named what is happening. "We now can move beyond keyword searching and paid placement and allow somebody else to do the research, the comparative analysis, the third-party authentication," he recently told CEO.com. "All of that is now shifting into a world that isn't just being road-mapped by machines, it's being read and written for machines." ### **What the machine wants** The answer engine does not rank pages. It synthesizes answers from sources it has determined to be authoritative, specific, and contextually coherent. Broad content that gestures vaguely at a topic is not what these systems reward. They reward content that answers a specific question cleanly, is authenticated by third parties, and holds together across every surface where it appears. The stakes of getting this wrong are severe. [Organic click-through rates fell by 61 percent for queries in which AI Overviews appeared](https://www.dataslayer.ai/blog/google-ai-overviews-the-end-of-traditional-ctr-and-how-to-adapt-in-2025?ref=ceo.com), according to Seer Interactive's analysis of 25 million impressions across 42 organizations. But brands cited inside those AI Overviews earned 35 percent more organic clicks and 91 percent more paid clicks. Being in the answer is everything. Being outside it is near-invisible. Stine frames the challenge as a single question every company has to answer honestly. "Do you know what question you're the answer to? Because now we are interacting in natural language, in ChatGPT, in Claude, in Perplexity, even in the Google search bar. People no longer want information; they want the answer." Most companies, he said, know what they sell. They do not know what they are the answer to. > *"These machines will, if you have a gap, not connect the dots for you. So context really, really matters." — Eric Stine, CEO, Sitecore.* ### **The HubSpot lesson** For more than a decade, HubSpot was the gold standard of content marketing. The company published constantly, ranked for thousands of keywords, and drove tens of millions of monthly visitors through organic search. Its approach became a template for the industry. Then, [organic traffic fell from approximately 13.5 million visits in November 2024 to fewer than 8.6 million by December](https://searchengineland.com/hubspot-seo-organic-traffic-drop-451096?ref=ceo.com), with some estimates putting the number as low as 6 million by early 2025. The cause was specificity failure. HubSpot had spent years publishing content on topics unrelated to its core business: cover letter templates, famous sales quotes, and resignation letter examples. These pages drove traffic. But they were not what HubSpot was the answer to. [HubSpot's CEO acknowledged on the company's earnings call](https://thedigitalbloom.com/learn/2025-organic-traffic-crisis-analysis-report/?ref=ceo.com) that organic search was "declining globally" and that "AI overviews are giving answers, and fewer people are clicking through to websites." The AI systems doing the brokering had no reason to treat HubSpot as an authority on resignation letters. Somebody else had a better answer to that question. The twist is instructive. [HubSpot still leads the market in AI-related brand visibility ](https://athenahq.ai/blog/hubspot-lost-70-of-its-seo-trafficbut-that-doesnt-mean-its-losing?ref=ceo.com)in its category, commanding a 35.3 percent share of voice in AI-generated answers for CRM and marketing software. Traffic collapsed because the company chased volume over specificity. Authority is held because the underlying expertise is real. The machines knew the difference. Content that does not know what question it is answering will no longer be rewarded for existing. ### **The question** This is a leadership problem before it is a marketing problem. [Bain's research](https://www.bain.com/insights/goodbye-clicks-hello-ai-zero-click-search-redefines-marketing/?ref=ceo.com) found that 80 percent of consumers rely on zero-click results at least 40 percent of the time. [By 2028, 50 billion of consumer spend is projected to flow through AI-powered search platforms](https://digiday.com/marketing/how-brands-are-trying-to-optimize-outsmart-ai-answer-engines-across-the-zero-click-landscape/?ref=ceo.com). The window to establish authority in these systems is open now. It will not stay open indefinitely. "Because we have the ability to contextualize that content from creation through publication, through optimization," Stine said. "We have the ability to help these brands control how their story is being told, no matter where consideration moves to." In the age of the answer engine, a brand must be legible to the machine before it can be legible to the customer. The machine is now the first audience. And it does not reward those who cannot clearly explain what question they exist to answer. ### Sitecore CEO Eric Stine: AI, answer engines, and why clarity is currency URL: https://www.ceo.com/episodes/sitecore-ceo-eric-stine-on-ai-answer-engines-and-why-clarity-is-currency/ Last updated: 2026-08-24T19:30:21.000Z # Eric Stine thinks search is over Eric Stine got into enterprise software after leaving politics. He worked in Washington during the impeachment and trial of a president, grew cynical, and left. A man he met in Dupont Circle hired him anyway. Stine had no background in technology. He knew government, knew how it bought, and was willing to listen. That was 25 years ago. Today he runs Sitecore, the digital experience platform behind how major brands reach, engage, and serve their audiences. [Sitecore named him CEO in May 2025](https://www.sitecore.com/company/newsroom/press-releases/2025/05/sitecore-appoints-eric-stine-as-chief-executive-officer?ref=ceo.com) after a run as chief operating officer during which revenues for its XM Cloud platform doubled in a year. Before that: [CEO of Elemica, chief commercial officer at Skillsoft, chief revenue officer at Qualtrics, and executive roles at SAP, Ciber, and Blackboard](https://www.sitecore.com/company/leadership?ref=ceo.com). He also co-produces Broadway musicals. The Outsiders, which he co-produced, won the 2024 Tony for Best Musical. Sitecore turns 25 on April 26\. His twins turn 10 the same day. The company was founded to help brands tell their story on a new thing called the internet, and Stine spends most of his time now on the newest version of that problem. For two decades, the internet worked because somebody indexed it. Google built the roadmap. Companies paid for shortcuts. Stine believes that era is over. "We no longer have to click multiple links to get the answer," he said on the podcast. "We can now move beyond keyword searching and paid placement and allow somebody else to do the research, the comparative analysis, the third-party authentication." People ask questions in natural language now, in ChatGPT, in Claude, in Perplexity, even in the Google search bar. They do not want information. They want the answer. So Stine asks every company the same thing he asks before agreeing to produce a show: Does it know why it is being made now? Does it know who it is for? "Do you know what question you're the answer to? Are they the questions you want to be the answer to?" Most companies fail this test because they lack specificity, he says. They grow, they want to be more to more people, and the message blurs. "Clarity is currency in today's market." He is spending real money on the thesis. In June, [Sitecore acquired Scrunch](https://www.sitecore.com/company/newsroom/press-releases/2026/06/sitecore-acquires-scrunch-to-help-brands-influence-discovery--and-buying-decisions?ref=ceo.com), a platform that shows brands how they appear in AI-generated answers across ChatGPT, Gemini, and Perplexity, then feeds those findings back into the content itself. [Bloomberg put the deal at roughly $225 million](https://www.techtarget.com/searchcustomerexperience/news/366643973/Sitecore-acquires-Scrunch-for-answer-engine-optimization?ref=ceo.com); Sitecore declined to confirm. He also killed seat-based pricing when he took the job. Sitecore now [prices on content interactions](https://www.techtarget.com/searchcontentmanagement/news/366641614/Sitecore-CEO-Marketing-content-experience-AI-prime-focus?ref=ceo.com), whether a human or a machine retrieves the content. None of this makes him a doomer about software. He has heard the talk of a SaaS apocalypse, and he answers it with a number. [A Bain & Company brief](https://www.bain.com/insights/where-have-all-the-sales-reps-gone/?ref=ceo.com) found that for almost a decade you could forecast a software company's growth by how fast it hired sales reps. Then the trend snapped. Between mid-2023 and mid-2025, sales hiring across the industry fell to 2 percent or less, in stretches negative. Stine's reading: the industry had built enough sales capacity for every product on the market, and headcount growth was over. "The great opportunity of AI is just like SaaS back in 2011, 2012, 2013," he said. "It is the refresh and the reset that enterprise software needed." His argument rests on edge cases. Nobody wants to vibe-code a supply chain system or a digital marketing platform when decades of expertise on the hard parts is already built into existing software. He learned that the details matter from thousands of pages of budget bills in Washington. He kept it. Ask Stine how he became CEO and he gives you a list of people. The man in Dupont Circle. A boss who coached him in ways he calls psychologically painful and forced him to face his insecurities as a leader. Steve Peck, who ran his business unit 24 years ago and sat him down at a coffee bar in Baltimore after a brutal negotiation with Johns Hopkins and told him everything he would need to know to lead, whether he wanted to hear it or not. And a woman he worked for who said the same sentence to every employee she met: "Thank you for everything you're doing." Stine thought the line was generic. Then he watched people light up when she said it. So he stole it. "People work best not just when they feel a sense of accomplishment or pride in what they're doing, but when the thing they are great at is seen and valued by the people around them." The theater habit started during the pandemic, between jobs, because of idle hands. He was a frustrated musical theater kid from New York whose parents couldn't really afford the great book musicals of the seventies, and he got to see them anyway. Now he helps sell a Tony winner week to week in digital media, hitting a ticket number to pay the cast and repay investors. He points out that this makes him his own customer. Asked to predict where AI goes from here, he refused. Whatever answer he gave would probably be wrong, he said, and if someone gets it right, give them the $10 trillion. "That would be like asking someone to accurately predict the future of commercial flight in 1915." He did offer one piece of evidence for what survives. Live musical theater began thousands of years ago with people sitting around on rocks. It is still here. ```chapters 00:00:00 Introduction to Sitecore and Eric Stine 00:01:45 The 25-Year History of Sitecore 00:04:52 How AI Transforms the Customer Experience 00:09:04 Predicting the Future of AI Technology 00:12:37 Eric Stine's Journey to Becoming CEO 00:16:31 Producing Tony Award-Winning Musical Theater 00:18:56 Why Clarity is Currency in Marketing 00:23:51 Navigating the Modern Macroeconomic Environment 00:27:09 Leadership Lessons from Washington DC ``` ```vtt WEBVTT 00:00:05.640 --> 00:00:07.804 Eric,<00:00:06.121> thank<00:00:06.346> you<00:00:06.426> so<00:00:06.682> much<00:00:07.003> for<00:00:07.147> coming<00:00:07.403> on<00:00:07.483> the<00:00:07.564> show. 00:00:08.429 --> 00:00:10.801 You<00:00:08.669> are<00:00:08.910> the<00:00:09.086> CEO<00:00:10.047> of<00:00:10.208> Sitecore. 00:00:11.394 --> 00:00:12.596 Let's<00:00:11.554> just<00:00:11.682> start<00:00:12.115> right<00:00:12.355> there. 00:00:13.012 --> 00:00:13.846 What<00:00:13.237> 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every<00:31:44.371> day. 00:31:45.093 --> 00:31:48.883 I<00:31:45.318> really<00:31:45.655> appreciate<00:31:46.217> you<00:31:46.298> giving<00:31:46.538> me<00:31:46.619> the<00:31:46.779> opportunity<00:31:47.438> to<00:31:47.502> tell<00:31:47.646> our<00:31:47.743> story<00:31:48.289> today,<00:31:48.626> Clint. 00:31:49.027 --> 00:31:50.168 Thank<00:31:49.333> you<00:31:49.750> so<00:31:49.927> much. ``` ### What the machine remembers URL: https://www.ceo.com/blog/what-the-machine-remembers/ Last updated: 2026-08-19T03:26:06.000Z For two centuries, Encyclopedia Britannica built one of the most successful direct sales forces in American history by targeting middle-income families with a proposition equal parts aspiration and guilt: the greatest gift you could give your children was access to knowledge. [By 1990, the company was selling 120,000 sets a year and generating $650 million in revenue](https://capitalismmagazine.com/2000/12/how-encyclopedia-britannica-was-blown-to-bits/?ref=ceo.com). A 32-volume set cost $1,500 to $2,200\. The company had not had an unprofitable year since the 1930s. Britannica was, in the most literal sense, the original answer engine. Someone had a question. They went to Britannica. The company had spent more than two centuries making itself the answer, across every topic, in every home that aspired to know. The brand was older than the United States. It felt like it would outlast everything. ### **The Offer** In 1985, [a Microsoft executive approached Britannica with a proposal](https://www.hbs.edu/ris/Publication%20Files/Reference%20Wars%20-%20Greenstein%5F6c4ac193-51eb-4758-a5a6-a4c412261411.pdf?ref=ceo.com) to license their content for a multimedia encyclopedia on CD-ROM. The company refused. As Britannica's director of public relations stated that year, "The Encyclopedia Britannica has no plans to be on a home computer." The home computer market was small. Only 4 or 5 percent of households had one. A digital product sold cheaply would undercut the premium print sets that the sales force was built to move. Protecting the sales force meant protecting the format. What complicates the story is that Britannica was not oblivious to digital media. [The company actually launched the first multimedia CD-ROM encyclopedia in 1989](https://tedium.co/2017/07/13/who-killed-the-encyclopedia/?ref=ceo.com), four years before Microsoft entered the market. But they released it under the Compton's brand name, a less prestigious encyclopedia they owned, specifically to keep the Britannica name from association with a cheaper medium. They had the technology and deliberately hid it. The mission was right. Protecting the format above all else was what failed them. Microsoft went to Funk and Wagnalls instead, licensed their content, and began building what would become Encarta. ### **The Collapse** Encarta launched in 1993 at $395, dropped to $99 within months, and was eventually bundled free with new computer purchases. The marginal cost to Microsoft of giving it away was roughly $1.50\. The marginal cost to Britannica of selling a print set was over $750, including commission. [Revenue fell 50 percent in three years](https://capitalismmagazine.com/2000/12/how-encyclopedia-britannica-was-blown-to-bits/?ref=ceo.com). By 1994, the company was selling only 51,000 sets. Its belated response illustrated exactly why the format had become the trap. [Britannica finally launched its own CD-ROM in 1994, priced at $995](https://tedium.co/2017/07/13/who-killed-the-encyclopedia/?ref=ceo.com), ten times the cost of Encarta. The price was set to avoid cannibalizing print sales and keep the sales force from revolting. It solved an internal problem and accelerated the external one. By 1995, the company put itself up for sale. Microsoft declined. So did every technology and media company approach. [In 1996, financier Jacob Safra purchased Britannica for $130 million](https://www.hbs.edu/ris/Publication%20Files/Reference%20Wars%20-%20Greenstein%5F6c4ac193-51eb-4758-a5a6-a4c412261411.pdf?ref=ceo.com), less than half its book value. The sales force was dissolved. The brand that had defined authoritative knowledge for two centuries was nearly worthless. ### **The Survival** Most people who know this story assume it ends there. It does not. The new ownership did what the old company could not: it separated the mission from the format. Britannica pivoted to institutional subscriptions, selling access to its content to schools and libraries at prices described by one executive as about the same as a glass of milk per subscriber. [When the company ended print entirely in 2012](https://singularityhub.com/2012/03/17/encyclopedia-britannica-ends-print-version-now-completely-digital/?ref=ceo.com), less than 1% of its revenue came from physical books. By 2022, [revenue was approaching $100 million](https://www.pymnts.com/news/ipo/2024/report-encyclopaedia-britannica-considering-june-ipo-1-billion-valuation/?ref=ceo.com), with [more than 500,000 institutional subscribers and 100 million students worldwide](https://www.prnewswire.com/news-releases/encyclopaedia-britannica-accelerates-its-digital-transformation-with-salesforce-300187911.html?ref=ceo.com). The company, now rebranded simply as Britannica, is pursuing an IPO. [The reported valuation: nearly $1 billion](https://gizmodo.com/encyclopedia-britannica-is-now-an-ai-company-2000542600?ref=ceo.com), driven by a pivot to artificial intelligence. The irony is complete. AI companies building large language models need one thing above all else: vetted, authoritative, human-edited content. Models trained on the raw internet produce hallucinations because the raw internet is full of errors and misinformation. Britannica's 256-year archive of expert-reviewed knowledge is exactly what the machines need to produce reliable answers. The company that was nearly destroyed when the medium for answering questions changed is now a valued supplier to the systems that broker answers today. ### **What the Mission Was Actually For** Britannica's failure was not a failure to understand digital technology. The company launched a CD-ROM encyclopedia in 1989\. It built an online version in 1994\. It understood the technology. What it failed to do was separate the mission from the format. The mission was to curate authoritative answers to questions people actually ask. The format was print. When protecting the format became the priority, the mission became impossible to serve. What the machine remembers is not the format. It does not care whether an answer arrived in 32 leather-bound volumes, on a CD-ROM, or through an institutional subscription portal. It cares whether the content is trustworthy, specific, and authenticated. Those qualities survived every disruption because they were never about the medium. They were about the mission. Britannica confused the two for a decade. When it finally stopped, it turned that mission into a company worth nearly a billion dollars. ### When the world breaks down, someone has to figure it out URL: https://www.ceo.com/blog/when-the-world-breaks-down-someone-has-to-figure-it-out/ Last updated: 2026-08-14T00:18:19.000Z The hat on your head, the phone in your hand, the chair you are sitting in. All of it moved across oceans and borders and distribution centers before it reached you. Most of the time, you never think about it. That is the goal. But right now, global shipping is anything but invisible. It is loud, expensive, and deeply unstable. The companies caught in the middle are making consequential decisions in real time, often without the data to make good ones. And the bill for those decisions is showing up in margins, in customer experience, and in competitive position. Hannah Testani has been watching all of it. She is the CEO of [Intelligent Audit](https://www.intelligentaudit.com/?ref=ceo.com), a company that analyzes global transportation data to help businesses identify what they did wrong and what they should do differently. She has spent her career inside one of the most complex and overlooked industries in the world. "Disruptions in supply chain are, selfishly, good for us," she [told CEO.com](https://www.ceo.com/c/podcast/why-every-disruption-is-a-hidden-opportunity-hannah-testani-ceo-of-intelligent-audit). "When things are easy, and anyone can do it, anyone can do it." ### **You are already behind** Since early 2025, broad [tariffs have reshaped ](https://www.globaltranz.com/resource-hub/2026-shipping-industry-report/?ref=ceo.com)the cost structure for U.S. importers, layering new duties on goods from China, Mexico, Canada, and dozens of other countries. The US-China truce, extended through November 2026, bought some time. It did not buy confidence. Analysts are already pricing in renewed volatility around July or August, well before the deadline arrives. The deeper problem is structural. Tariffs are [no longer a set-and-forget cost](https://shiptheory.com/blog/international-shipping-in-2026-your-business/?ref=ceo.com). Trade agreements, political decisions, and regional policies are changing frequently, often with little notice. Businesses are now expected to apply the correct tariff at the exact moment a shipment leaves the warehouse. Most companies are not built to carry that burden cleanly. What happens in practice is what Testani watches play out constantly with her clients. Disruption forces a company to rethink its supply chain, and the first instinct is speed, not strategy. "Most people solve problems quickly in the way that is easiest and makes the most sense. Almost never the most cost-effective. They are in firefighting mode, not engineering mode. You solve the problem in the moment and then look back later and realize there was a better way." If a company was sole-sourced from China before tariffs, it probably isn't anymore. It is now being manufactured in China, India, Latin America, and possibly the US. More carriers. More origin points. More complexity. And more opportunity for the wrong decision to compound into a very expensive one. ### **The long way around** The armed conflict in Gaza, combined with the persistent threat of piracy, has effectively rendered the Suez Canal corridor too dangerous for many carriers, forcing ships to reroute around the Cape of Good Hope, a longer and more expensive path. That [detour adds weeks to transit times](https://www.freshfruitportal.com/news/2026/01/07/global-shipping-outlook/?ref=ceo.com) and a high cost to every shipment that takes it. Some carriers are beginning to return. But the return is its own problem. A full reopening of the Red Sea would remove one of the last remaining supports for container rates by shortening voyages and freeing up vessel capacity, worsening what [analysts describe as structural overcapacity issues](https://gulfnews.com/business/markets/container-shipping-heads-toward-a-harder-2026-as-red-sea-reopening-pressures-rates-1.500441624?ref=ceo.com). The industry spent two years propped up by disruption-driven pricing. That support is unwinding. The companies that locked into a single routing approach when the Red Sea closed are now the ones scrambling to adapt as it reopens. Testani has watched this pattern repeat across every major disruption of the past decade. The companies that fare best are not the ones that predicted what was coming. They are the ones who could move once it arrived. "Maybe before you could ship something via airplane right from anywhere to the US. Now, maybe you have to break it up into ocean containers. And as you are making those changes, you are working with new providers, and your shipping characteristics look completely different." She pauses on this point. It sounds straightforward. In practice, at scale, with hundreds of lanes, dozens of carriers, and cost structures that shift week to week, it is anything but. "I do not think most executives realize how much money is being left on the table simply because no one has the time to go back and look at what actually happened." ### **Too many ships, not enough direction** Beneath the geopolitical noise lies a slower, structural problem that will outlast any ceasefire or trade truce. Around 1.5 million TEU of new vessels are due for delivery this year, and the total orderbook [now exceeds 31 percent of existing fleet](https://www.maritimeanalytica.com/p/is-container-shipping-quietly-heading?ref=ceo.com) capacity, the highest orderbook ratio since 2011\. Carriers are reaching for familiar tools. Slow steaming. Blank sailings. Idled vessels. Freight rates are already falling. For shippers, falling rates look like good news on the surface. But a market that swings this dramatically in either direction is hard to plan around. Overall [consumer spending is expected to decelerate](https://www.supplychaindive.com/news/supply-chain-trends-risks-2026-retail-manufacturing/808797/?ref=ceo.com) this year as affordability concerns and a softening labor market stress shoppers' wallets. The pressure is not just external. It is moving through the entire chain. ### **The capability gap** Every conversation about supply chain eventually gets to technology. Rarely does it get to the people behind the technology, and that is a mistake. [Labor is no longer a stable input](https://unival-logistics.com/2026-shipping-logistics-challenges?ref=ceo.com) for supply chain leaders. It is a strategic constraint. Shortages in dockworkers, drivers, and specialized technicians are affecting everything from container handling to last-mile delivery. The companies that are pulling ahead are the ones that figured out how to see more with the people they have. That is where AI enters the conversation in a way that actually matters. Testani is direct about how most companies are misreading that opportunity. She separates AI into two lanes: productivity and innovation. Most leaders, she says, are only operating in the first. "Productivity is what most people talk about today. It allows teams to be more effective at what they already do. But innovation is what you can do with technology that you simply could not do before. I think we should spend a lot more time thinking about that." Her own AI solution is built on that distinction. It operates more like credit card fraud detection than traditional logistics software, learning a company's shipping patterns and flagging anomalies in real time before they become expensive problems. "Supply chain is incredibly complex right now. There are tariffs, there are not tariffs, there are new tariffs, there is a war, there is a new war. Our AI watches those patterns and makes you aware when something does not add up." She is honest that even this is not a complete answer. The technology is only as useful as the willingness to act on what it surfaces. "You have to just start implementing and be ready to make changes. If you are paralyzed waiting for the next new thing, you will never make progress." She has watched companies buy sophisticated tools and then flinch at what the data tells them. The visibility is not the hard part. What you do with it is. ### **The opportunity inside the chaos** Pull all of this together, and the picture is not pretty. Tariffs that reprice every shipment with little warning. Major trade routes in flux. A fleet too large for the demand it is serving. A labor market that cannot fill the gaps. And underneath all of it, the relentless pressure to make good decisions faster than the competition. The businesses being punished hardest right now are the ones built for a stable world. Sole-sourced in one country. Running the same carriers on the same routes with the same assumptions baked in for a decade. Not because bad luck found them. Because stability was the plan and stability is gone. Winners in 2026 will be [those who recognize the critical decision points](https://unival-logistics.com/2026-shipping-logistics-challenges?ref=ceo.com) happening right now, identify them early, and act on them to reshape their operations quickly. Testani would not disagree with that framing. But she would push it further. This is not a 2026 problem with a 2027 resolution. Disruption is no longer an exception in shipping and logistics. It is the operating environment. "When there is any kind of disruption, companies now have to go solve a new problem. Supply chains become more complex. They are going to have more carriers, more locations they are shipping from and to. Complexity is good for us." The world is not getting simpler. The question every executive running a company that ships anything needs to answer is whether they are building the capability to use it, or still waiting for things to calm down. They are not going to calm down. ### Hannah Testani, CEO of Intelligent Audit: Why every disruption is a hidden opportunity URL: https://www.ceo.com/episodes/why-every-disruption-is-a-hidden-opportunity-hannah-testani-ceo-of-intelligent-audit/ Last updated: 2026-08-24T19:45:32.000Z # Hannah Testani built a company that gets stronger when supply chains break A hat gets manufactured somewhere in the world. It crosses the ocean in a container or the sky in a freighter, lands at a distribution center, and rides a truck to a store or a front porch. Multiply that by millions of hats and the errors compound: one order that arrives in four shipments, a small item rattling around a massive box, an invoice charging for a service never rendered. Intelligent Audit makes its money finding those errors. By the company's count, it [audited more than 2.1 billion shipments last year, and 20 percent of the Fortune 50 are customers](https://www.intelligentaudit.com/?ref=ceo.com). Hannah Testani did not plan on any of this. She studied finance at Carnegie Mellon and joined Goldman Sachs in 2008, just in time to watch the financial system come apart. Her father had founded Intelligent Audit in 1996, and he offered her a job. ["At first, I hated it,"](https://www.mckinsey.com/industries/logistics/our-insights/logistics-disruptors-using-big-data-to-spot-shipping-anomalies?ref=ceo.com) she told McKinsey in 2023\. Nobody outside the industry thought about supply chains then, because supply chains had not yet failed them. They fail all the time now, and Testani is candid about what that means for her. "Disruptions in supply chain generally are selfishly good to us," she said on the CEO.com Podcast. A company sole-sourced in China spreads its manufacturing to India, Latin America, and the United States. New carriers, new lanes, new invoices, new mistakes. "When things are easy, and anyone can do it, anyone can do it." What she has noticed about companies in crisis is that they solve problems the fastest way, almost never the cheapest way. "They're in firefighting mode. They're not in engineering mode." Her software goes back through the wreckage afterward and shows what the smarter decision would have been, so the next fire costs less. Testani splits AI into two categories. The first is productivity, the drill that replaces the screwdriver, and it is what everyone talks about. The second is innovation, the things technology makes possible that were never possible before, and she wishes executives spent more time there. Her company's [anomaly detection system, DeepDetectAI](https://www.intelligentaudit.com/products/anomaly-detection?ref=ceo.com), belongs to the second category, and she explains it the way a bank explains fraud detection. You never asked your credit card company to flag a one-dollar charge in Nebraska. The system learned you, and it speaks up when something does not fit. DeepDetectAI does the same across millions of shipping transactions. Asked whether AI will take jobs, she said yes. Then she said something more interesting: she has never met an executive whose first constraint was anything other than bandwidth. Every company has a backlog of problems it cannot staff. "The pizza pie just got a lot bigger. Now we have to figure out how we are going to continue feeding everyone and then also making more money off of the pizza." Her real worry is paralysis. What AI can do today is vastly different from what it could do three weeks ago, and leaders who wait for it to settle will wait forever. "You have to just start implementing it and moving it forward and be ready to make changes afterwards." About three years ago, Intelligent Audit adopted [EOS, the Entrepreneurial Operating System](https://www.eosworldwide.com/what-is-eos?ref=ceo.com), which Testani calls the most impactful decision the organization has made. Under it, her calendar has one meeting that matters: 90 minutes a week with her executive team, walking through quarterly goals and a handful of measurables. The rest of her job, as she describes it, is pointing the ship, hiring stewards for each part of it, and watching the horizon for obstacles. She compares a CEO to a soccer coach. Recruit talent, run practice, then stay off the field. "You're not a player. You're not going to be in the game. And the longer you are, your team's not going to win." She has a diagnosis for CEOs who keep getting pulled into the day-to-day. Either the wrong people are in the wrong seats, or the trust is missing, or nobody ever agreed on the work in the first place. "Most people want to win. You just have to align expectations, communicate effectively, and then hold them accountable." Before every quarterly meeting, managers at every level of the company run whiteboarding sessions where their teams surface problems. Issues get solved at the lowest level that can solve them and escalate only when they must; after the quarter is set, priorities trickle back down. "Every employee doesn't just feel heard, but is heard," she said. Testani reads founder biographies, Musk and Jobs and Sam Walton, and finds the same thing in all of them. "It's not that they don't listen to the word no, but they question why the answer is no when someone says no to them. Because it is very easy to say no. It's very hard to problem solve." She heard plenty of no herself. When she was up for the top job, the people around her said a young woman and a mother was probably not right for the position. Asked who gave her a chance, she named her husband. "He was like, go prove them wrong," she told the CEO.com Podcast. "Most spouses, I have learned, either are your biggest advocates or the reason why you don't succeed." ```chapters 00:00:00 Introduction to Intelligent Audit 00:02:03 How AI and Automation Transform Supply Chains 00:06:16 Managing Employee Expectations Around AI 00:07:59 Navigating Supply Chain Disruptions and Tariffs 00:10:09 A Day in the Life of a CEO 00:12:10 Leading on the Business with EOS 00:17:30 Recommended Reading and Mindset for Leaders 00:18:44 Navigating Macroeconomic Uncertainty and Fear 00:21:08 The Power of Support and Final Thoughts ``` ```vtt WEBVTT 00:00:05.632 --> 00:00:07.734 Hannah,<00:00:06.290> thank<00:00:06.514> you<00:00:06.546> so<00:00:06.707> much<00:00:06.996> for<00:00:07.092> coming<00:00:07.397> on<00:00:07.477> the<00:00:07.557> show. 00:00:08.055 --> 00:00:09.210 It's<00:00:08.199> such<00:00:08.376> an<00:00:08.520> honor<00:00:08.681> to<00:00:08.761> have<00:00:09.098> you. 00:00:09.339 --> 00:00:12.291 You<00:00:09.499> are<00:00:09.660> 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So<00:02:48.131> either<00:02:48.388> you<00:02:48.533> have<00:02:48.709> the<00:02:48.854> option<00:02:49.271> to<00:02:49.432> be<00:02:49.577> able<00:02:49.737> to<00:02:49.817> do,<00:02:50.476> build<00:02:50.877> more,<00:02:51.841> or<00:02:52.002> to<00:02:52.146> just,<00:02:52.387> you<00:02:52.419> know,<00:02:52.644> go<00:02:52.869> have<00:02:53.046> fun. 00:02:53.303 --> 00:02:58.892 So<00:02:54.555> from<00:02:54.732> my<00:02:54.957> perspective,<00:02:56.081> AI<00:02:56.740> is<00:02:56.900> broken<00:02:57.221> up<00:02:57.382> into<00:02:57.784> two<00:02:58.105> main<00:02:58.410> components. 00:02:59.872 --> 00:03:05.894 Productivity,<00:03:01.221> which<00:03:01.317> is<00:03:01.462> what<00:03:01.702> most<00:03:02.120> people<00:03:02.602> talk<00:03:02.987> about<00:03:03.260> today<00:03:04.112> and<00:03:04.208> is,<00:03:04.754> is<00:03:04.850> that<00:03:05.172> real<00:03:05.332> example. 00:03:06.360 --> 00:03:10.231 It<00:03:06.440> allows<00:03:07.019> our<00:03:07.179> teams<00:03:07.886> to<00:03:08.046> be<00:03:08.544> a<00:03:08.625> lot<00:03:08.849> more<00:03:09.026> effective<00:03:09.508> at<00:03:09.588> what<00:03:09.813> they<00:03:09.909> can<00:03:10.070> do. 00:03:11.194 --> 00:03:12.672 And<00:03:11.275> then<00:03:11.419> there's<00:03:11.741> actual<00:03:12.142> innovation. 00:03:13.202 --> 00:03:21.651 And<00:03:13.347> I,<00:03:13.620> I<00:03:13.748> actually<00:03:14.166> wish<00:03:14.487> that<00:03:14.712> that<00:03:14.889> was<00:03:15.595> thought<00:03:15.836> about<00:03:16.238> more<00:03:16.977> because<00:03:17.362> innovation<00:03:17.876> is<00:03:18.085> what<00:03:18.422> you<00:03:18.583> can<00:03:18.824> do<00:03:18.985> with<00:03:19.145> technology<00:03:20.270> that<00:03:20.414> you<00:03:20.591> just<00:03:20.832> couldn't<00:03:21.137> do<00:03:21.394> before. 00:03:22.117 --> 00:03:30.614 And<00:03:22.261> at<00:03:22.342> the<00:03:22.438> end<00:03:22.534> of<00:03:22.599> the<00:03:22.759> day,<00:03:24.108> the<00:03:24.205> compute<00:03:25.072> that<00:03:25.233> comes<00:03:25.634> out<00:03:25.747> of<00:03:25.875> machine<00:03:26.277> learning<00:03:27.257> and<00:03:27.401> what<00:03:27.803> actual<00:03:28.365> AI<00:03:28.702> can<00:03:28.927> do,<00:03:29.666> humans<00:03:30.148> can't<00:03:30.453> do. 00:03:31.208 --> 00:03:33.649 So<00:03:31.336> I<00:03:31.433> think<00:03:31.577> we<00:03:31.658> should<00:03:31.754> spend<00:03:31.979> a<00:03:31.995> lot<00:03:32.396> more<00:03:32.557> time<00:03:32.959> thinking<00:03:33.216> about<00:03:33.521> that. 00:03:33.697 --> 00:03:43.443 So<00:03:34.629> for<00:03:34.806> people,<00:03:35.368> for<00:03:35.512> example,<00:03:36.637> You,<00:03:37.279> you<00:03:37.439> look<00:03:37.616> at<00:03:37.696> self-driving<00:03:38.258> cars<00:03:39.060> that<00:03:39.221> can<00:03:39.526> only<00:03:39.863> be<00:03:40.024> made<00:03:40.248> possible<00:03:41.147> because<00:03:41.533> of<00:03:41.854> innovations<00:03:42.592> in<00:03:42.672> machine<00:03:43.138> learning. 00:03:44.117 --> 00:03:51.180 Whereas<00:03:44.598> most<00:03:44.984> of<00:03:45.080> what<00:03:45.321> we're<00:03:45.481> talking<00:03:45.883> about<00:03:46.107> with<00:03:46.348> AI<00:03:47.151> is<00:03:47.985> I<00:03:48.002> don't<00:03:48.130> need<00:03:48.371> people<00:03:48.676> anymore<00:03:49.398> because<00:03:49.880> I<00:03:49.976> can<00:03:50.088> now<00:03:50.297> automate<00:03:50.714> their<00:03:50.923> job. 00:03:51.597 --> 00:04:05.912 So<00:03:52.207> I<00:03:52.304> really<00:03:52.609> think<00:03:52.865> it'd<00:03:53.010> be<00:03:53.604> a<00:03:53.732> lot<00:03:54.133> easier<00:03:54.455> for<00:03:54.535> most<00:03:55.193> professionals<00:03:55.979> to<00:03:56.076> be<00:03:56.172> able<00:03:56.301> to<00:03:56.397> conceptualize<00:03:57.842> if<00:03:58.002> instead<00:03:58.227> of<00:03:58.307> using<00:03:58.548> the<00:03:58.628> word<00:03:58.949> AI,<00:04:00.009> use<00:04:00.169> the<00:04:00.314> word<00:04:00.554> automation<00:04:01.678> because<00:04:01.855> we've<00:04:01.999> been<00:04:02.240> automating<00:04:03.123> workflows<00:04:04.022> and<00:04:04.182> processes<00:04:05.047> for<00:04:05.464> decades. 00:04:06.425 --> 00:04:08.364 And<00:04:06.569> that's<00:04:06.745> just<00:04:06.970> an<00:04:07.130> easier<00:04:07.450> pill<00:04:07.691> to<00:04:07.771> swallow. 00:04:08.892 --> 00:04:11.520 And<00:04:08.956> I<00:04:08.972> think<00:04:09.069> where<00:04:09.165> there's<00:04:09.469> more<00:04:09.629> opportunity<00:04:10.591> is<00:04:11.071> innovation. 00:04:12.674 --> 00:04:14.644 We<00:04:12.834> have<00:04:13.058> our<00:04:13.234> Deep<00:04:13.427> Detect<00:04:13.939> AI<00:04:14.196> solution. 00:04:15.141 --> 00:04:20.733 The<00:04:15.301> easiest<00:04:15.622> way<00:04:15.878> to<00:04:16.375> break<00:04:17.064> it<00:04:17.160> down<00:04:18.025> is<00:04:18.121> you<00:04:18.346> probably<00:04:18.746> use<00:04:18.938> a<00:04:19.002> credit<00:04:19.307> card<00:04:19.563> today<00:04:19.964> to<00:04:20.108> purchase<00:04:20.525> things. 00:04:21.470 --> 00:04:32.445 You've<00:04:21.646> probably<00:04:22.127> never<00:04:22.527> gone<00:04:22.912> to<00:04:23.008> your<00:04:23.168> credit<00:04:23.425> card,<00:04:23.569> whether<00:04:23.793> it's<00:04:23.905> an<00:04:24.194> Amex,<00:04:24.851> a<00:04:24.915> Chase,<00:04:25.636> whoever,<00:04:26.597> and<00:04:26.757> you've<00:04:26.934> said,<00:04:27.831> tell<00:04:28.071> me<00:04:28.616> if<00:04:28.696> someone<00:04:29.097> is<00:04:29.321> in,<00:04:29.801> you<00:04:29.850> know,<00:04:30.122> Nebraska<00:04:31.019> spending<00:04:31.420> a<00:04:31.516> dollar<00:04:31.900> at<00:04:32.045> Target. 00:04:33.006 --> 00:04:33.968 You<00:04:33.182> didn't<00:04:33.663> need<00:04:33.888> to. 00:04:34.769 --> 00:04:42.398 Your<00:04:34.945> credit<00:04:35.266> card<00:04:35.506> company<00:04:36.067> continues<00:04:36.708> to<00:04:36.789> learn<00:04:37.414> you,<00:04:38.311> and<00:04:38.472> when<00:04:38.632> something<00:04:38.936> happens<00:04:39.273> that's<00:04:39.577> atypical<00:04:40.251> to<00:04:40.619> Clint,<00:04:41.292> it's<00:04:41.517> making<00:04:41.901> you<00:04:42.014> aware. 00:04:43.039 --> 00:04:46.004 That<00:04:43.264> is<00:04:43.424> how<00:04:43.825> our<00:04:44.546> DeepTech<00:04:44.867> AI<00:04:45.123> solution<00:04:45.668> works. 00:04:46.806 --> 00:04:50.220 Supply<00:04:47.271> chain<00:04:47.848> is<00:04:47.944> incredibly<00:04:48.473> complex,<00:04:48.986> especially<00:04:49.595> in<00:04:49.675> today's<00:04:50.011> world. 00:04:50.717 --> 00:04:55.541 There's<00:04:50.973> tariffs,<00:04:51.582> there's<00:04:51.774> not<00:04:52.079> tariffs,<00:04:52.400> there's<00:04:52.656> new<00:04:52.880> tariffs,<00:04:53.618> there's<00:04:54.002> a<00:04:54.179> war,<00:04:54.579> there's<00:04:54.820> a<00:04:54.980> new<00:04:55.301> war. 00:04:56.246 --> 00:05:01.439 All<00:04:56.422> of<00:04:56.583> this,<00:04:56.823> if<00:04:56.983> you<00:04:57.208> are<00:04:57.544> a<00:04:57.625> supply<00:04:58.266> chain<00:04:59.067> employee,<00:05:00.029> means<00:05:00.253> that<00:05:00.413> you<00:05:00.509> have<00:05:00.750> to<00:05:00.894> be<00:05:01.070> nimble. 00:05:01.792 --> 00:05:02.722 You<00:05:01.856> have<00:05:01.952> to<00:05:02.032> make<00:05:02.257> changes. 00:05:03.155 --> 00:05:06.492 And<00:05:03.236> as<00:05:03.396> you're<00:05:03.540> making<00:05:03.958> those<00:05:04.262> changes,<00:05:05.080> you're<00:05:05.161> working<00:05:05.482> with<00:05:05.786> new<00:05:05.963> providers. 00:05:07.743 --> 00:05:09.492 Shipping<00:05:08.209> characteristics<00:05:08.850> look<00:05:09.075> different. 00:05:09.893 --> 00:05:14.305 Maybe<00:05:10.198> before<00:05:10.551> you<00:05:10.695> could<00:05:10.936> ship<00:05:11.241> something<00:05:11.417> with<00:05:11.562> an<00:05:11.658> airplane,<00:05:12.604> right,<00:05:12.861> from<00:05:13.326> anywhere<00:05:13.727> to<00:05:13.824> the<00:05:13.968> US. 00:05:14.626 --> 00:05:17.000 Now<00:05:14.866> maybe<00:05:15.011> you<00:05:15.171> have<00:05:15.283> to<00:05:15.412> break<00:05:15.668> it<00:05:15.749> up<00:05:15.909> into<00:05:16.214> ocean<00:05:16.454> containers. 00:05:17.208 --> 00:05:19.246 So<00:05:17.658> you<00:05:17.818> have<00:05:18.155> to<00:05:18.315> be<00:05:18.396> able<00:05:18.636> to<00:05:18.781> be<00:05:18.877> nimble. 00:05:20.385 --> 00:05:31.247 How<00:05:20.625> our<00:05:20.946> AI<00:05:21.299> solution<00:05:21.925> works<00:05:22.342> is<00:05:22.486> as<00:05:23.128> you<00:05:23.288> continue<00:05:24.171> to<00:05:24.315> ship<00:05:24.636> anything,<00:05:25.518> if<00:05:25.695> we<00:05:25.855> see<00:05:26.192> something<00:05:26.802> that<00:05:26.978> we<00:05:27.139> couldn't<00:05:27.524> predict,<00:05:28.583> Just<00:05:28.727> like<00:05:28.904> your<00:05:29.032> credit<00:05:29.224> card<00:05:29.465> fraud<00:05:29.610> detection<00:05:29.947> does,<00:05:30.428> we're<00:05:30.540> making<00:05:30.829> you<00:05:30.990> aware. 00:05:31.776 --> 00:05:33.606 So<00:05:31.872> that<00:05:32.113> is<00:05:32.258> the<00:05:32.498> innovation<00:05:33.140> aspect. 00:05:33.798 --> 00:05:39.800 From<00:05:34.296> an<00:05:34.504> actual<00:05:35.788> optimization<00:05:36.767> perspective,<00:05:37.794> it<00:05:37.874> is<00:05:38.131> now<00:05:38.468> a<00:05:38.597> core<00:05:38.934> lever<00:05:39.319> everywhere. 00:05:40.137 --> 00:05:41.983 So<00:05:40.298> we<00:05:40.458> don't<00:05:40.699> do<00:05:40.924> anything<00:05:41.261> that's<00:05:41.485> not<00:05:41.646> AI. 00:05:42.224 --> 00:05:48.980 We<00:05:42.384> just<00:05:42.544> had<00:05:42.689> our<00:05:42.849> executive<00:05:43.267> team<00:05:43.491> meeting<00:05:43.668> this<00:05:43.909> week<00:05:44.390> and<00:05:44.936> every<00:05:45.192> conversation<00:05:46.075> was,<00:05:47.038> how<00:05:47.102> are<00:05:47.263> we<00:05:47.343> using<00:05:47.664> AI<00:05:47.905> to<00:05:47.985> make<00:05:48.145> that<00:05:48.322> more<00:05:48.418> impactful? 00:05:49.766 --> 00:05:54.677 But<00:05:49.911> the<00:05:50.472> tricky<00:05:50.793> part<00:05:50.954> here<00:05:51.194> that<00:05:51.291> I<00:05:51.371> would<00:05:51.676> kind<00:05:51.836> of<00:05:51.997> warn<00:05:52.157> everyone<00:05:52.430> is<00:05:53.217> AI<00:05:53.521> is<00:05:53.762> moving<00:05:53.955> so<00:05:54.179> fast. 00:05:54.982 --> 00:05:59.555 Where<00:05:55.142> it<00:05:55.367> is<00:05:55.608> today<00:05:55.945> versus<00:05:56.747> 3<00:05:56.972> weeks<00:05:57.228> ago<00:05:57.549> versus<00:05:57.934> 3<00:05:58.047> months<00:05:58.287> ago<00:05:58.528> is<00:05:58.737> vastly<00:05:59.218> different. 00:06:00.197 --> 00:06:06.262 And<00:06:00.341> it's—<00:06:00.919> you<00:06:01.176> have<00:06:01.336> to<00:06:01.481> just<00:06:01.641> start<00:06:02.106> implementing<00:06:02.748> it<00:06:02.925> and<00:06:03.069> moving<00:06:03.406> it<00:06:03.567> forward<00:06:04.289> and<00:06:04.449> be<00:06:04.754> ready<00:06:05.091> to<00:06:05.235> make<00:06:05.412> changes<00:06:05.797> afterwards. 00:06:06.696 --> 00:06:12.841 But<00:06:06.856> if<00:06:07.000> you're<00:06:07.161> just<00:06:07.482> always<00:06:07.979> paralyzed<00:06:08.605> because<00:06:09.744> there's<00:06:09.905> something<00:06:10.306> new<00:06:10.611> and<00:06:10.787> flashy,<00:06:11.830> you'll<00:06:11.991> never<00:06:12.231> make<00:06:12.456> progress. 00:06:13.274 --> 00:06:15.826 So<00:06:13.355> you<00:06:13.515> got<00:06:13.708> to<00:06:13.836> just<00:06:14.558> put<00:06:14.703> things<00:06:15.184> into<00:06:15.585> flight. 00:06:16.849 --> 00:06:20.335 I<00:06:16.869> think<00:06:17.045> some<00:06:17.206> of<00:06:17.270> the<00:06:17.430> angst<00:06:17.687> too<00:06:17.848> around<00:06:18.233> AI<00:06:18.489> is<00:06:18.634> like,<00:06:18.810> is<00:06:18.955> it<00:06:18.987> going<00:06:19.131> to<00:06:19.195> take<00:06:19.436> my<00:06:19.613> job? 00:06:20.479 --> 00:06:22.469 And,<00:06:21.041> you<00:06:21.121> know,<00:06:21.298> kind<00:06:21.474> of<00:06:21.779> those<00:06:22.020> types<00:06:22.196> of<00:06:22.324> things. 00:06:22.565 --> 00:06:27.242 How<00:06:22.661> have<00:06:22.902> you<00:06:23.528> managed<00:06:24.009> those<00:06:24.266> expectations<00:06:24.892> with<00:06:25.036> your<00:06:25.133> employees<00:06:25.951> and<00:06:26.362> and<00:06:26.532> talked<00:06:26.870> about<00:06:27.123> that? 00:06:29.100 --> 00:06:35.346 Automation<00:06:30.084> has<00:06:30.342> been<00:06:30.584> something<00:06:30.907> that<00:06:31.052> as<00:06:31.295> a<00:06:31.375> corporation,<00:06:32.102> because<00:06:32.424> we're<00:06:32.521> a<00:06:32.602> technology<00:06:33.248> company<00:06:33.651> first,<00:06:34.458> that's<00:06:34.765> always<00:06:35.007> been<00:06:35.184> there. 00:06:35.507 --> 00:06:39.861 So<00:06:36.072> we<00:06:36.250> exist<00:06:36.718> to<00:06:36.879> be<00:06:37.057> able<00:06:37.202> to<00:06:38.073> find<00:06:38.300> inefficiencies<00:06:38.992> and<00:06:39.281> automate<00:06:39.700> them. 00:06:40.263 --> 00:06:42.049 And<00:06:40.343> that<00:06:40.504> is<00:06:40.665> exactly<00:06:41.132> what<00:06:41.229> we're<00:06:41.309> doing<00:06:41.550> with<00:06:41.711> AI. 00:06:42.596 --> 00:06:54.299 The<00:06:42.983> opportunity<00:06:43.723> is,<00:06:43.820> and<00:06:43.948> I<00:06:44.029> hope<00:06:44.206> that<00:06:44.431> really<00:06:44.753> everyone<00:06:45.316> kind<00:06:45.493> of<00:06:45.735> flips<00:06:46.040> the<00:06:46.073> script<00:06:46.459> here,<00:06:47.557> I<00:06:47.638> have<00:06:47.831> never<00:06:48.201> met<00:06:48.764> and<00:06:48.812> talked<00:06:49.102> to<00:06:49.327> any<00:06:49.649> executive<00:06:50.389> at<00:06:50.454> any<00:06:50.631> company<00:06:51.515> where<00:06:51.918> their<00:06:52.143> first<00:06:52.561> constraint<00:06:53.285> is<00:06:53.446> not<00:06:54.009> bandwidth. 00:06:54.952 --> 00:06:55.641 Prioritization. 00:06:56.219 --> 00:06:57.421 It's<00:06:56.315> like,<00:06:56.459> yeah,<00:06:56.667> no,<00:06:56.732> that<00:06:56.956> sounds<00:06:57.261> great. 00:06:57.501 --> 00:06:59.777 I<00:06:57.597> just,<00:06:57.918> I<00:06:57.998> can't<00:06:58.206> because<00:06:58.479> I<00:06:58.559> got<00:06:58.671> to<00:06:58.719> focus<00:06:59.104> on<00:06:59.264> this<00:06:59.393> stuff<00:06:59.601> first. 00:06:59.857 --> 00:07:19.719 So<00:07:00.947> I<00:07:01.044> don't<00:07:01.300> see<00:07:02.070> a<00:07:02.102> near-term<00:07:02.887> world<00:07:03.288> in<00:07:03.368> the<00:07:03.448> next<00:07:03.833> 1<00:07:04.009> to<00:07:04.153> 2<00:07:04.330> years<00:07:04.955> where<00:07:05.292> most<00:07:05.837> companies<00:07:07.199> don't<00:07:07.440> have<00:07:08.177> a<00:07:08.321> ton<00:07:08.594> more<00:07:09.123> opportunities<00:07:09.940> to<00:07:10.101> be<00:07:10.197> able<00:07:10.421> to<00:07:10.758> invest<00:07:11.223> their<00:07:11.463> time<00:07:11.800> and<00:07:11.880> their<00:07:12.104> people<00:07:12.489> in<00:07:13.467> and<00:07:13.547> not,<00:07:13.707> and<00:07:13.852> it's<00:07:13.948> going<00:07:14.044> to<00:07:14.092> have<00:07:14.252> to<00:07:14.413> fire<00:07:14.669> them<00:07:15.214> because<00:07:15.535> really<00:07:15.872> what<00:07:16.032> it<00:07:16.192> means<00:07:16.449> is<00:07:16.897> because<00:07:17.218> AI<00:07:17.555> will<00:07:17.651> replace<00:07:18.052> a<00:07:18.116> lot<00:07:18.276> of<00:07:18.581> the<00:07:18.677> jobs<00:07:19.013> that<00:07:19.142> exist<00:07:19.462> today. 00:07:20.023 --> 00:07:20.937 It<00:07:20.103> just,<00:07:20.344> how<00:07:20.440> could<00:07:20.665> you<00:07:20.761> not? 00:07:21.242 --> 00:07:21.386 Yeah. 00:07:21.626 --> 00:07:21.723 Yeah. 00:07:21.883 --> 00:07:26.371 At<00:07:21.963> the<00:07:22.059> same<00:07:22.364> time,<00:07:23.149> you<00:07:23.326> still<00:07:23.726> as<00:07:23.887> a<00:07:23.967> company<00:07:24.592> have<00:07:24.993> so<00:07:25.121> many<00:07:25.409> more<00:07:25.634> problems<00:07:26.195> to<00:07:26.291> solve. 00:07:26.500 --> 00:07:26.580 Solve. 00:07:27.094 --> 00:07:29.068 So<00:07:27.238> just<00:07:27.977> focus<00:07:28.298> on<00:07:28.442> those<00:07:28.619> problems. 00:07:29.566 --> 00:07:31.573 And<00:07:29.887> by<00:07:30.064> doing<00:07:30.305> that,<00:07:30.690> you're<00:07:30.851> winning,<00:07:31.348> right? 00:07:31.670 --> 00:07:38.124 You<00:07:32.232> can<00:07:32.376> make<00:07:32.697> more<00:07:32.874> revenue,<00:07:33.757> you<00:07:33.853> can<00:07:34.222> increase<00:07:34.881> your<00:07:34.977> margins,<00:07:36.005> and<00:07:36.085> you<00:07:36.229> can<00:07:36.390> keep<00:07:36.631> your<00:07:36.808> team<00:07:37.048> and<00:07:37.193> uplevel<00:07:37.675> everyone. 00:07:39.296 --> 00:07:40.709 Do<00:07:39.521> I<00:07:39.617> think<00:07:39.794> it's<00:07:39.938> going<00:07:40.099> to<00:07:40.163> take<00:07:40.324> jobs? 00:07:40.902 --> 00:07:41.111 Yes. 00:07:41.785 --> 00:07:42.716 Will<00:07:41.865> it<00:07:41.945> take<00:07:42.170> opportunities? 00:07:43.053 --> 00:07:43.118 No. 00:07:43.471 --> 00:07:49.990 That's<00:07:43.776> where,<00:07:44.017> as<00:07:44.113> an<00:07:44.209> executive<00:07:44.836> team,<00:07:45.462> you<00:07:45.558> have<00:07:45.719> to<00:07:45.879> really<00:07:46.200> paint<00:07:46.505> the<00:07:46.602> picture<00:07:47.308> of<00:07:48.432> the<00:07:48.528> pizza<00:07:48.866> pie<00:07:49.090> just<00:07:49.315> got<00:07:49.476> a<00:07:49.492> lot<00:07:49.652> bigger. 00:07:50.519 --> 00:07:56.378 And<00:07:50.857> now<00:07:51.097> we<00:07:51.178> have<00:07:51.338> to<00:07:51.499> figure<00:07:51.804> out<00:07:52.270> How<00:07:52.382> are<00:07:52.446> we<00:07:52.542> going<00:07:52.639> to<00:07:52.767> continue<00:07:53.184> feeding<00:07:53.569> everyone<00:07:54.452> and<00:07:54.532> then<00:07:54.629> also<00:07:54.950> making<00:07:55.271> more<00:07:55.415> money<00:07:55.736> off<00:07:55.848> of<00:07:55.913> the<00:07:55.993> pizza? 00:07:56.940 --> 00:07:59.812 Yeah,<00:07:57.903> no,<00:07:58.063> that<00:07:58.240> makes,<00:07:58.480> that<00:07:58.577> makes<00:07:58.817> a<00:07:59.042> lot<00:07:59.267> of<00:07:59.363> sense. 00:08:00.390 --> 00:08:01.802 Uh,<00:08:00.888> tell<00:08:01.048> me<00:08:01.209> about<00:08:01.433> tariffs. 00:08:01.931 --> 00:08:03.102 How<00:08:02.091> did<00:08:02.172> that<00:08:02.332> affect<00:08:02.637> your<00:08:02.733> business? 00:08:03.199 --> 00:08:04.627 How<00:08:03.375> is<00:08:03.455> it<00:08:03.536> still<00:08:03.792> affecting<00:08:04.178> your<00:08:04.322> business? 00:08:05.943 --> 00:08:18.509 Disruptions<00:08:06.970> in<00:08:07.066> supply<00:08:07.532> chain<00:08:08.254> generally<00:08:08.896> are<00:08:08.992> selfishly<00:08:09.714> good<00:08:09.875> to<00:08:10.035> us<00:08:10.581> because<00:08:10.774> if<00:08:10.902> you<00:08:10.998> think<00:08:11.239> about<00:08:11.720> what<00:08:11.865> it<00:08:12.025> means<00:08:12.362> is,<00:08:13.004> you<00:08:13.069> know,<00:08:13.470> our,<00:08:13.871> our<00:08:14.128> customers<00:08:14.754> today,<00:08:15.652> they<00:08:15.957> probably<00:08:16.615> manufacture<00:08:17.739> around<00:08:18.124> the<00:08:18.284> world. 00:08:18.782 --> 00:08:20.435 And<00:08:18.862> they<00:08:19.023> have<00:08:19.344> set<00:08:19.745> supply<00:08:20.226> chains. 00:08:20.563 --> 00:08:22.168 I<00:08:20.628> mean,<00:08:20.772> that's<00:08:21.013> what<00:08:21.446> a<00:08:21.510> supply<00:08:21.896> chain<00:08:22.072> is. 00:08:22.233 --> 00:08:25.844 You<00:08:22.313> have<00:08:22.794> literally<00:08:23.099> a<00:08:23.180> chain<00:08:23.517> where<00:08:23.741> everyone<00:08:24.078> depends<00:08:24.399> on<00:08:24.496> each<00:08:24.704> other<00:08:25.025> to<00:08:25.122> move<00:08:25.362> products. 00:08:26.390 --> 00:08:33.307 When<00:08:26.486> there's<00:08:26.807> any<00:08:27.112> kind<00:08:27.288> of<00:08:27.449> disruption,<00:08:28.091> whether<00:08:28.332> it's<00:08:28.572> tariffs<00:08:29.054> or<00:08:29.134> a<00:08:29.279> war,<00:08:29.937> what<00:08:30.081> that<00:08:30.258> means<00:08:30.643> is<00:08:31.365> they<00:08:31.477> now<00:08:31.702> have<00:08:31.927> to<00:08:32.023> go<00:08:32.184> solve<00:08:32.665> a<00:08:32.681> new<00:08:32.986> problem. 00:08:34.094 --> 00:08:40.610 And<00:08:34.575> if<00:08:34.671> before,<00:08:35.217> for<00:08:35.378> example,<00:08:36.020> they<00:08:36.180> were<00:08:36.517> sole<00:08:36.854> 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carriers,<00:08:54.005> location<00:08:54.567> they're<00:08:54.711> shipping<00:08:55.048> from<00:08:55.433> and<00:08:55.529> to. 00:08:56.234 --> 00:09:02.632 And<00:08:56.331> complexity<00:08:56.908> is<00:08:57.052> good<00:08:57.212> for<00:08:57.453> us<00:08:58.094> because,<00:08:58.896> you<00:08:58.928> know,<00:08:59.602> when<00:08:59.762> things<00:09:00.019> are<00:09:00.243> easy<00:09:00.724> and<00:09:01.061> anyone<00:09:01.381> can<00:09:01.526> do<00:09:01.702> it,<00:09:02.023> anyone<00:09:02.263> can<00:09:02.424> do<00:09:02.568> it. 00:09:02.969 --> 00:09:14.979 But<00:09:03.065> where<00:09:03.306> we<00:09:03.450> exist<00:09:03.883> as<00:09:04.091> being<00:09:04.268> that<00:09:04.749> sole<00:09:05.246> source<00:09:05.711> of<00:09:05.855> truth,<00:09:06.256> where<00:09:06.352> we<00:09:06.513> take<00:09:07.218> our<00:09:07.459> customers'<00:09:08.036> data<00:09:08.501> from<00:09:08.822> everywhere,<00:09:09.720> which<00:09:09.800> is<00:09:10.024> really<00:09:10.281> hard<00:09:10.521> to<00:09:10.666> consume,<00:09:11.644> and<00:09:11.724> then<00:09:11.884> we<00:09:12.029> make<00:09:12.285> it<00:09:12.670> easy<00:09:13.087> for<00:09:13.392> them<00:09:13.792> to<00:09:13.889> understand<00:09:14.354> what<00:09:14.450> to<00:09:14.546> be<00:09:14.690> doing. 00:09:15.877 --> 00:09:25.972 The<00:09:15.958> other<00:09:16.198> thing<00:09:16.391> about<00:09:17.274> tariffs,<00:09:17.884> war,<00:09:18.124> anything<00:09:18.606> is<00:09:19.424> most<00:09:19.890> people<00:09:20.323> solve<00:09:20.628> the<00:09:20.788> problems<00:09:21.414> quickly<00:09:22.554> in<00:09:22.634> the<00:09:22.778> way<00:09:22.955> that<00:09:23.099> is<00:09:23.982> easiest<00:09:24.544> and<00:09:24.640> just<00:09:25.105> makes<00:09:25.362> the<00:09:25.459> most<00:09:25.683> sense. 00:09:26.887 --> 00:09:28.652 Almost<00:09:27.224> never<00:09:27.529> the<00:09:27.625> most<00:09:27.930> cost-effective. 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were<00:22:23.891> willing<00:22:24.212> to<00:22:24.373> teach<00:22:24.694> me,<00:22:25.337> and<00:22:25.481> I<00:22:25.658> love<00:22:25.899> to<00:22:26.043> learn. 00:22:27.409 --> 00:22:28.116 Hannah,<00:22:27.650> you're<00:22:27.746> amazing. 00:22:28.164 --> 00:22:30.237 Seriously,<00:22:28.791> this—<00:22:28.935> your<00:22:29.032> insights<00:22:29.417> were<00:22:29.739> unbelievable. 00:22:30.317 --> 00:22:31.843 Thank<00:22:30.542> you<00:22:30.622> so<00:22:30.815> much<00:22:31.185> for<00:22:31.281> coming<00:22:31.522> on<00:22:31.602> the<00:22:31.683> show. 00:22:32.470 --> 00:22:33.064 Thank<00:22:32.663> you,<00:22:32.807> Clint. 00:22:33.112 --> 00:22:33.787 It's<00:22:33.209> been<00:22:33.353> an<00:22:33.434> honor. 00:22:33.948 --> 00:22:35.233 So<00:22:34.076> I<00:22:34.108> really<00:22:34.317> appreciate<00:22:34.639> you<00:22:34.719> having<00:22:34.976> me. ``` ### The cost of assuming the world stays still: Toyota and the 2011 Tohoku earthquake URL: https://www.ceo.com/blog/the-cost-of-assuming-the-world-stays-still-toyota-and-the-2011-tohoku-earthquake/ Last updated: 2026-08-19T03:21:44.000Z For decades, Toyota was held up as the gold standard of manufacturing. Its production system was studied in business schools, copied by competitors, and written about in books. The core idea was elegant: eliminate waste, keep inventory lean, trust your suppliers to deliver exactly what you need exactly when you need it. It was called Just-In-Time, and it worked brilliantly. Then the ground moved. On March 11, 2011, a magnitude 9.0 earthquake struck the northeast coast of Japan, followed immediately by a tsunami that swept through the Tohoku region. The disaster was the [most powerful natural disaster in Japan's modern history](https://www.everycrsreport.com/reports/R41831.html?ref=ceo.com). The destruction of several nuclear reactors compounded the damage, cutting electricity across the region. A large area was evacuated, making rapid reopening of affected industries impossible. --- ### **78 Percent** Toyota produced 45 percent of its vehicles in Japan at the time, almost twice as much as Honda and Nissan. When the earthquake hit, the exposure was immediate and total. Plants closed. Suppliers went dark. The parts stopped moving. Global output declined 78 percent in April 2011 compared to the same month the previous year. Some [tier-1 and tier-2 suppliers were wiped out entirely](https://supplychainnuggets.com/lessons-from-toyotas-just-in-time-revamp/?ref=ceo.com), halting the production of critical microcontrollers and other essential components. With almost no stock on hand, assembly lines went dark. Net income for the quarter fell 77 percent. The disaster affected the production of over 150,000 vehicles. It took three months to recover to pre-earthquake production levels. Toyota's Executive VP Shinichi Sasaki did not search for euphemisms. He called it a big shock to Toyota's just-in-time system. The financial damage was severe. The strategic damage was worse. Toyota had spent years positioning itself as the most disciplined, most reliable manufacturer in the world. The earthquake did not just disrupt production. It revealed that the entire system was built on an assumption nobody had thought to question: that the world would stay still. --- ### **The Factory Nobody Knew About** Just-In-Time was not a bad idea. It was a brilliant idea that worked exactly as designed, right up until the moment the design met reality. The logic is seductive. Inventory is waste. Time your deliveries precisely, and you do not need to hold stock. Save on storage, reduce the risk of obsolescence, keep your operation lean. For three decades, this logic held. Toyota refined it. The rest of the industry copied it. The average manufacturing firm at the time of the earthquake held [just over three weeks' worth of materials inventory](https://www.federalreserve.gov/econresdata/notes/feds-notes/2016/role-of-global-supply-chains-in-the-transmission-of-shocks-20160502.html). Because this is an average across all inputs, there were likely many individual parts with much shorter supplies. Three weeks sounds reasonable. It is not when the parts stop coming entirely. But the inventory problem was only part of the story. The deeper problem was that Toyota did not actually know what its supply chain looked like. It knew its direct suppliers well. What it did not know was what existed behind those suppliers. The tier-2 and tier-3 vendors. The small factories in the Tohoku region produce a single component on which everything else in the chain depends. Renesas Electronics was one of the major global vehicle chip makers, producing as much as 40 percent of the world's automotive microcontroller supply. When its plant went down, it was not expected to return to even partial capacity for months. Renesas was not a name that appeared in Toyota's strategic planning documents. But when its plant went down, Toyota's assembly lines followed. This is the nature of modern supply chains. The risk is rarely where you are looking. It lives in the layers you cannot see. Toyota had one of the most sophisticated manufacturing operations in the world, yet it had no idea that a single semiconductor factory in Tohoku was the linchpin holding it all together. It found out the way most companies find out. When it was too late. --- ### **What Getting Serious Actually Looks Like** Toyota did not respond to the earthquake by patching the holes and moving on. It responded by rebuilding the system from a different set of assumptions. Before 2011, Toyota's line of sight effectively ended at its tier-1 suppliers. That was no longer acceptable. Toyota built a database covering suppliers across multiple tiers, linking parts to exact factory locations. The process of identifying which parts were at risk in a crisis took two weeks in 2011\. By 2021, it was cut to half a day. Toyota formalized this through a system called RESCUE, which stores supply chain information for around 6,800 items. The goal was not just to recover faster when something went wrong. It was to know, before a disaster arrived, exactly which nodes in the network were exposed and what the alternatives were. On inventory, Toyota made a deliberate choice to accept inefficiency in exchange for resilience. Around 500 priority parts most likely to cause production paralysis were identified, and suppliers were mandated to maintain a stock of two to six months for each. Semiconductors received special focus, with Toyota securing one to four months of chip inventory as part of its business continuity plan. Holding six months of semiconductor inventory is not lean. It is expensive. Toyota did it anyway because the cost of holding inventory is fixed, while the cost of a production shutdown is not. The change that received the least attention and mattered the most was what happened to Toyota's supplier relationships. Toyota began sharing three-year production forecasts with suppliers to help them plan capacity. During crises, purchasing teams maintained constant communication, connecting with some suppliers ten times a day during the 2020 to 2021 semiconductor crunch. It provided financial and technical assistance to help smaller suppliers build their own contingency plans. The supplier was no longer a vendor that the purchasing team called when something went wrong. It was a partner whose stability Toyota had a direct interest in protecting, because Toyota had finally understood something it should have known all along: a supply chain is only as strong as its least visible node. --- ### **Still Running** The real test of these reforms did not come from another earthquake. It came from the global semiconductor shortage that hit the automotive industry starting in 2020. The shortage was brutal. Plants closed. Production targets were slashed. Companies that had spent years squeezing cost out of their supply chains found themselves without the components they needed to build cars. General Motors idled plants. Volkswagen cut output. The losses across the industry ran into the billions. Toyota kept running. During the semiconductor shortage, Toyota's one to four-month chip inventory kept its lines running while rivals shut down their plants. The supplier database, the forecasting relationships, and the business continuity planning built after 2011 gave Toyota a different set of options than anyone else in the industry had. When Toyota's CFO Kenta Kon was asked directly whether the company foresaw any major impact from the shortage, his answer was no. The lessons learned following the 2011 earthquake, he said, had contributed to Toyota's ability to mitigate the impact of semiconductor supply disruption. The buffers eventually ran dry. By August 2021, Toyota cut production by 40 percent. But it had bought months of uninterrupted output that its competitors had not. Those months were not an abstraction. They were units sold, customers retained, and market share gained while everyone else was trying to figure out what went wrong. --- ### **The Same Mistake, Still Being Made** The Federal Reserve's analysis of the Tohoku earthquake found that the disaster shaved nearly half a percentage point from U.S. second-quarter GDP in 2011\. U.S. manufacturing output fell by about one percent in April and remained significantly below prior levels for roughly six months. One earthquake in Japan. Six months of depressed manufacturing output in the United States. The connections inside a modern supply chain are that tight, and the consequences of a single failure travel that far. Toyota's mistake in 2011 was not that it built an efficient system. It was built on the assumption that the environment that made efficiency possible would never change. That assumption lived invisibly inside every decision Toyota made for thirty years. Nobody questioned it because it had never been wrong. Until it was. Most companies operating today are making the same assumption. Not about earthquakes. About whatever their version of stability happens to be. A supplier relationship that has worked for a decade. A shipping route that has always been reliable. A cost structure built on conditions that existed last year. The disruptions hitting global supply chains right now, tariffs, rerouted ships, labor shortages, and demand swings, are not asking companies to do something different in kind from what Toyota faced in 2011\. They are asking the same question Toyota had to answer: how much of what you think you know about your supply chain is actually true, and what happens to your business when the part you did not know about stops working? [Hannah Testani built Intelligent Audit around exactly that question](https://www.ceo.com/c/podcast/why-every-disruption-is-a-hidden-opportunity-hannah-testani-ceo-of-intelligent-audit). Most companies, she argues, are sitting on the data that would answer it. The shipping records exist. The carrier data exists. The cost structures are documented somewhere. What is usually missing is the visibility to see it all in one place and the willingness to act on what it shows. Toyota built that visibility after the earthquake because it had no choice. The companies that build it now, before the next disruption, rather than because of it, are the ones that will still be running when everyone else is trying to understand what they missed. ### Ethos CEO Andrew Powell: How AI is training the U.S. military for the next war URL: https://www.ceo.com/episodes/are-your-people-ready-inside-ethos-the-ai-platform-training-the-u-s-military/ Last updated: 2026-08-24T19:58:52.000Z # The business of being ready The military and professional sports share a strange arithmetic. Both spend 90 to 95 percent of their time training and about five percent performing. If deterrence works, a soldier's performance time rounds to zero. Most jobs run the opposite way. Andrew Powell built a company for the inverted ones. Powell is the co-founder and CEO of [Ethos](https://www.ethossystems.com/?ref=ceo.com), a Redwood City, California company whose AI helps the Department of Defense and other high-stakes organizations answer what he calls the pivotal question: are our people ready for what they need to do? Readiness is the military's own word, the ability of forces to fight and achieve the goals of assigned missions, and on the CEO.com Podcast, Powell described the Pentagon as probably the world's largest educational bureaucracy, training millions of people. It is also an organization that cannot hire its way out of a talent problem. "You can't go poach a competitive fighter squadron leader from China," Powell said. "You have to develop people from an early age." Every CEO says people are their greatest asset, then pours effort into recruiting. The military has no such option. It grows everything at home. Powell came to this world without a uniform. He was Coursera's first non-software-engineering intern, then spent years building a startup university system in Africa. At Stanford's business school, he met Sasha Seymore, a [Naval Reserve Intelligence Officer](https://www.ethossystems.com/company?ref=ceo.com), and the two took Hacking for Defense, a course that applies Stanford's entrepreneurial method to military problems. Their assignment was pilot training, specifically how the Air Force could produce combat-ready aviators faster. Their project [beat more than 200 teams](https://news.stanford.edu/stories/2019/07/stanford-grad-students-develop-award-winning-app-streamlines-u-s-air-force-training?ref=ceo.com) to reach the final round of the 2019 Hacking4Defense competition, then took the top prize, and the company that grew out of it became, by Powell's account, the first from the program to land a recurring subscription contract with the government. The company launched as Learn to Win, took a $4 million seed from Norwest, and closed an [oversubscribed $30 million Series A](https://www.prnewswire.com/news-releases/enterprise-saas-training-platform-learn-to-win-closes-30-million-series-a-funding-round-302169853.html?ref=ceo.com) led by the Westly Group in 2024, capital Powell says the business genuinely needed given the cost of accreditation to run on classified networks. A [rebrand to Ethos](https://www.prnewswire.com/news-releases/learn-to-win-announces-rebrand-to-ethos-the-human-readiness-platform-302459673.html?ref=ceo.com) followed in 2025\. The customer list now runs from the Navy, Air Force, and Space Force to Novartis, AbbVie, and the Seattle Seahawks. Headcount is about 60. The product's newest layer, launched in August, is the [Readiness Engine](https://www.prnewswire.com/news-releases/ethos-launches-the-readiness-engine-a-living-map-of-workforce-capability-302848506.html?ref=ceo.com), built on a knowledge graph of everything a role requires a person to know and do. Powell finds that the graph serves two audiences. It shows leaders which people need training on which skill. And it turns out to be exactly what AI agents need too. "The same things that make people better at their jobs, the context, the direction, the effective onboarding, the right tools, a lot of that's the same things that make AI agents really effective," he said. The work is already recursive: Ethos is helping the Army retrain pilots of manned aircraft to lead mixed teams of manned and unmanned systems, training humans for jobs that AI is redefining while it trains them. Then there is the question that follows every defense tech founder into every interview now. [Anthropic's dispute with the Pentagon](https://www.congress.gov/crs-product/IN12669?ref=ceo.com) over restrictions on military use of its AI models was in the news, and Powell answered at length. "I am pretty fiercely in the camp that I believe in democracy, freedom, capitalism, and a rules-based international order," he said. "I've chosen the side of the US and our allies, and I want to strongly be on that team." His position is that elected leaders and their military counterparts, not vendors, should be entrusted with those tools, with courts and elections as checks. "I'm fiercely of the view that our government leaders are the ones who should be entrusted with deciding the law, not unelected tech companies." He also called Anthropic's models some of the best in the world and said he hopes the company and the Pentagon resolve their differences. The conviction has a boundary, and Powell polices it. He will talk to anyone, at any length, about measuring military readiness. Beyond that, he asks what he actually has credibility to speak on. "There was probably a period when CEOs were putting out statements on so many different issues that they had no direct influence over. It felt like moral grandstanding," he said. "Sometimes people in Silicon Valley believe that just because they're extremely good at technology, they're the wisest on a whole bunch of completely unrelated issues." He does worry publicly about one thing adjacent to his sphere: AI losing its social contract. Companies can use the technology to cut headcount and pad margins, or to retrain people into the jobs the technology is creating. Ethos sells the second option, and Powell wants it to win on the merits. "If you can prove that upskilling people with AI creates greater growth and greater opportunity, and that's better than laying off large numbers of people, hopefully that becomes the playbook others follow." Asked the question that closes every CEO.com interview, who gave you a chance, Powell named Jeff Crowe of Norwest. Powell had spent about a year pursuing the idea, and some of the nos landed personally. "To then have someone say, we believe in this too, and we want to back you and make this happen, was just a very impactful moment." ```chapters 00:00:00 Introduction to Ethos and Workforce Readiness 00:00:46 The Origins of Ethos in National Security 00:02:48 Working with the United States Military 00:05:14 Applying Readiness Tech to Commercial Insurance 00:06:06 How AI Is Transforming Workforce Training 00:08:14 The Ethics of Building Defense Technology 00:12:13 Should CEOs Speak Out on Political Issues 00:15:06 Public Perception and the Future of AI 00:18:58 Daily Routine of a Tech CEO 00:19:46 Venture Funding and Scaling the Business 00:20:51 The Macroeconomic Environment and Defense Budgets 00:23:25 Advice for Aspiring Defense Tech Founders 00:25:20 Reading Recommendations for Founders and Leaders 00:26:22 Who Gave Andrew Powell His First Big Chance ``` ```vtt WEBVTT 00:00:05.600 --> 00:00:07.520 Andrew,<00:00:06.160> thank<00:00:06.319> you<00:00:06.400> so<00:00:06.560> 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the<00:02:50.959> military. 00:02:51.920 --> 00:02:56.879 What<00:02:52.160> kind<00:02:52.319> of<00:02:52.480> challenges<00:02:52.959> come<00:02:53.120> with<00:02:53.280> that?<00:02:53.760> What,<00:02:54.319> um,<00:02:55.200> benefits<00:02:55.760> come<00:02:55.920> from<00:02:56.160> that? 00:02:56.879 --> 00:03:01.360 Uh,<00:02:57.200> I'm<00:02:57.440> sure<00:02:57.599> you<00:02:57.760> have<00:02:57.840> to<00:02:58.000> find<00:02:58.160> the<00:02:58.319> right<00:02:58.480> investors,<00:02:59.120> find<00:02:59.360> the<00:02:59.519> right<00:03:00.000> team,<00:03:00.239> and<00:03:00.480> all<00:03:00.640> of<00:03:00.720> that<00:03:00.879> type<00:03:01.040> of<00:03:01.120> stuff. 00:03:01.360 --> 00:03:04.720 What,<00:03:01.580> what<00:03:01.800> has<00:03:02.020> that<00:03:02.240> been<00:03:02.460> like?<00:03:02.680> <00:03:02.900> Yeah,<00:03:03.120> it's<00:03:03.340> been<00:03:03.560> a<00:03:03.780> fascinating<00:03:04.000> experience. 00:03:04.720 --> 00:03:11.280 I<00:03:05.120> didn't<00:03:05.440> have<00:03:05.519> a<00:03:05.760> military<00:03:06.159> background<00:03:06.480> before<00:03:06.879> starting<00:03:07.120> the<00:03:07.360> company,<00:03:07.680> but<00:03:08.319> fortunately,<00:03:08.879> the<00:03:09.120> program<00:03:09.440> I<00:03:09.599> mentioned<00:03:09.840> at<00:03:10.000> Stanford,<00:03:10.400> Hacking<00:03:10.640> for<00:03:10.800> Defense,<00:03:11.120> is 00:03:11.280 --> 00:03:14.080 a<00:03:11.440> great<00:03:11.760> crash<00:03:12.080> course<00:03:12.480> in<00:03:12.879> a<00:03:13.120> lot<00:03:13.200> of<00:03:13.360> this. 00:03:14.080 --> 00:03:20.159 And<00:03:14.400> I<00:03:14.640> really<00:03:14.800> got<00:03:15.040> inspired<00:03:15.840> by<00:03:16.239> the<00:03:16.560> opportunity<00:03:17.040> to<00:03:17.599> solve<00:03:17.920> problems<00:03:18.319> I<00:03:18.480> think<00:03:18.640> are<00:03:18.879> super<00:03:19.280> meaningful. 00:03:20.159 --> 00:03:25.680 Um,<00:03:20.720> the<00:03:21.599> Department<00:03:21.840> of<00:03:22.000> Defense<00:03:22.239> is<00:03:22.480> probably<00:03:22.640> the<00:03:22.800> world's<00:03:23.120> largest,<00:03:23.760> like,<00:03:24.080> educational<00:03:24.640> bureaucracy. 00:03:25.680 --> 00:03:30.000 Uh,<00:03:26.064> they're<00:03:26.448> training<00:03:26.832> millions<00:03:27.216> of<00:03:27.600> people<00:03:27.983> to<00:03:28.367> do<00:03:28.751> very<00:03:29.135> high-stakes<00:03:29.519> jobs. 00:03:30.000 --> 00:03:37.920 And<00:03:30.239> so,<00:03:31.040> um,<00:03:31.200> I<00:03:31.440> had<00:03:31.599> some<00:03:31.840> ideas<00:03:32.080> of<00:03:32.239> what<00:03:32.400> might<00:03:32.640> work<00:03:32.879> coming<00:03:33.120> from<00:03:33.280> the<00:03:33.680> kind<00:03:33.840> of<00:03:34.000> education<00:03:34.480> tech<00:03:34.799> background,<00:03:35.200> but<00:03:35.440> it's<00:03:35.599> a<00:03:36.080> totally<00:03:36.480> different<00:03:36.799> organization. 00:03:37.920 --> 00:03:42.080 Um,<00:03:38.480> and<00:03:38.720> there's<00:03:38.959> two<00:03:39.200> things<00:03:39.280> that<00:03:39.440> I<00:03:39.599> think<00:03:39.680> are<00:03:39.920> really<00:03:40.080> fascinating<00:03:40.480> about<00:03:40.640> it<00:03:40.879> from<00:03:41.040> a<00:03:41.200> training<00:03:41.519> perspective. 00:03:42.080 --> 00:03:49.680 One,<00:03:42.959> um,<00:03:43.360> probably<00:03:43.599> every<00:03:43.840> CEO<00:03:44.239> in<00:03:44.400> the<00:03:44.560> world<00:03:44.720> says,<00:03:45.200> you<00:03:45.280> know,<00:03:45.440> people<00:03:45.680> are<00:03:45.840> your<00:03:46.080> greatest<00:03:46.319> asset,<00:03:46.879> and<00:03:47.040> a<00:03:47.200> lot<00:03:47.280> of<00:03:47.440> times<00:03:47.599> what<00:03:47.760> that<00:03:48.000> means<00:03:48.239> is<00:03:48.799> put<00:03:49.040> a<00:03:49.200> ton<00:03:49.360> of<00:03:49.440> effort 00:03:49.680 --> 00:03:58.959 into<00:03:50.000> hiring,<00:03:51.200> um,<00:03:51.440> the<00:03:51.599> DoD<00:03:52.000> is<00:03:52.239> interesting<00:03:52.480> because<00:03:52.720> you<00:03:52.879> have<00:03:53.040> to<00:03:53.200> develop<00:03:53.599> all<00:03:53.840> of<00:03:53.920> your<00:03:54.080> talent<00:03:54.480> internally.<00:03:55.280> Like,<00:03:55.519> you<00:03:55.680> can't<00:03:55.920> just<00:03:56.080> go<00:03:56.319> and<00:03:56.560> coach<00:03:56.959> a,<00:03:57.360> you<00:03:57.519> know,<00:03:57.760> competitive 00:03:58.959 --> 00:04:05.439 fighter<00:03:59.599> squadron<00:04:00.080> leader<00:04:00.400> from<00:04:00.799> China.<00:04:01.200> Like,<00:04:01.360> it<00:04:01.599> doesn't<00:04:01.680> work<00:04:01.840> that<00:04:02.000> way<00:04:02.080> where<00:04:02.319> you<00:04:02.480> can<00:04:02.560> just,<00:04:02.799> you<00:04:02.959> know,<00:04:03.120> bring<00:04:03.280> in<00:04:03.519> the<00:04:03.680> talent<00:04:04.000> externally.<00:04:04.640> 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you<00:04:18.079> develop 00:04:18.400 --> 00:04:25.440 your<00:04:18.639> people<00:04:18.959> into<00:04:19.280> great<00:04:19.600> leaders<00:04:19.919> who<00:04:20.160> can<00:04:20.320> effectively,<00:04:21.359> uh,<00:04:21.519> run<00:04:21.680> the<00:04:21.919> organization<00:04:22.400> because<00:04:22.639> it's<00:04:22.880> all<00:04:23.199> homegrown<00:04:23.759> talent<00:04:24.080> with<00:04:24.240> some<00:04:24.479> exceptions<00:04:24.880> of<00:04:25.040> civilians 00:04:25.440 --> 00:04:28.960 or<00:04:25.680> contractors,<00:04:26.240> whatever<00:04:26.479> else,<00:04:26.639> but<00:04:26.960> majority<00:04:27.440> it's,<00:04:27.680> it's<00:04:28.000> homegrown. 00:04:28.960 --> 00:04:34.400 Um,<00:04:29.280> the<00:04:29.520> other<00:04:29.680> piece<00:04:29.919> is,<00:04:30.560> uh,<00:04:30.800> the<00:04:31.040> military<00:04:31.600> and<00:04:32.080> sports,<00:04:32.479> which<00:04:32.720> is<00:04:32.800> one<00:04:32.960> of<00:04:33.040> our<00:04:33.199> other<00:04:33.360> big<00:04:33.600> markets. 00:04:34.400 --> 00:04:42.479 Um,<00:04:35.280> they<00:04:35.680> spend<00:04:36.080> like<00:04:36.400> 90,<00:04:36.800> 90,<00:04:37.600> 95%<00:04:38.240> of<00:04:38.320> their<00:04:38.479> time<00:04:38.720> training<00:04:39.520> and<00:04:39.759> only<00:04:40.080> typically<00:04:40.400> like<00:04:40.639> 5%<00:04:41.120> really<00:04:41.440> doing<00:04:41.680> the<00:04:41.919> thing<00:04:42.000> that<00:04:42.240> they<00:04:42.400> need 00:04:42.479 --> 00:04:47.520 to<00:04:42.639> do.<00:04:43.040> Um,<00:04:43.360> hopefully<00:04:43.840> if<00:04:44.080> we<00:04:44.240> deter<00:04:44.639> wars,<00:04:44.880> then<00:04:45.040> they<00:04:45.199> don't<00:04:45.280> have<00:04:45.360> to<00:04:45.440> spend,<00:04:45.759> you<00:04:45.840> know,<00:04:46.000> any<00:04:46.160> time<00:04:46.320> actually<00:04:46.560> in<00:04:46.800> combat. 00:04:47.520 --> 00:04:54.080 Uh,<00:04:47.759> but<00:04:47.919> it's<00:04:48.080> an<00:04:48.320> interesting<00:04:48.560> space<00:04:48.720> where<00:04:48.880> you're<00:04:49.120> spending<00:04:49.440> almost<00:04:49.680> all<00:04:49.840> of<00:04:50.000> your<00:04:50.160> time<00:04:50.400> preparing<00:04:50.880> for<00:04:51.120> something<00:04:51.759> and<00:04:51.919> a<00:04:52.080> very<00:04:52.320> small<00:04:52.479> percentage<00:04:53.040> doing<00:04:53.280> it, 00:04:54.080 --> 00:04:59.440 uh,<00:04:54.160> which<00:04:54.320> is<00:04:54.479> inverse<00:04:54.880> of<00:04:54.960> a<00:04:55.120> lot<00:04:55.199> of<00:04:55.360> jobs<00:04:55.520> where,<00:04:55.759> like,<00:04:55.919> you're<00:04:56.160> almost<00:04:56.400> always<00:04:56.800> doing<00:04:57.040> the<00:04:57.280> job<00:04:57.520> and<00:04:57.759> you<00:04:57.919> spend<00:04:58.160> a<00:04:58.320> little<00:04:58.400> bit<00:04:58.560> of<00:04:58.639> time<00:04:58.800> in<00:04:58.960> training. 00:04:59.440 --> 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in<00:05:25.919> that<00:05:26.160> space. 00:05:26.479 --> 00:05:34.880 Um,<00:05:27.120> and<00:05:27.360> we've<00:05:27.600> got<00:05:27.680> some<00:05:27.919> customers<00:05:28.320> that<00:05:28.639> are<00:05:29.199> training<00:05:29.520> their<00:05:29.759> people<00:05:30.080> through<00:05:30.400> Ethos,<00:05:31.520> um,<00:05:32.000> on<00:05:32.560> essentially<00:05:32.960> everything<00:05:33.280> that<00:05:33.600> they,<00:05:34.639> uh, 00:05:34.880 --> 00:05:43.199 need<00:05:35.039> to<00:05:35.199> know<00:05:35.520> for<00:05:35.840> their<00:05:36.160> job.<00:05:36.560> Um,<00:05:36.880> it's<00:05:37.039> a<00:05:37.199> kind<00:05:37.360> of<00:05:37.440> fast-moving<00:05:38.000> space<00:05:38.320> where<00:05:38.639> you<00:05:38.800> want<00:05:38.880> to<00:05:39.039> make<00:05:39.120> sure<00:05:39.280> that<00:05:39.520> your<00:05:40.080> line<00:05:40.400> manager<00:05:40.800> or<00:05:41.039> sales<00:05:41.360> rep<00:05:41.600> is<00:05:42.240> on<00:05:42.560> message 00:05:43.199 --> 00:05:45.759 uh,<00:05:43.360> kind<00:05:43.520> of<00:05:43.600> saying<00:05:43.840> the<00:05:44.000> right<00:05:44.160> things,<00:05:44.400> doing<00:05:44.639> the<00:05:44.800> right<00:05:44.960> things. 00:05:45.759 --> 00:05:49.280 Um,<00:05:46.240> and,<00:05:46.720> uh,<00:05:46.800> that's<00:05:47.120> quickly<00:05:47.440> evolving<00:05:47.840> and<00:05:48.080> it<00:05:48.320> varies<00:05:48.720> state-by-state. 00:05:49.280 --> 00:05:51.680 So,<00:05:49.440> it's<00:05:49.600> kind<00:05:49.680> of<00:05:49.759> a<00:05:50.000> complex<00:05:50.400> training<00:05:50.720> problem<00:05:50.960> to<00:05:51.280> solve. 00:05:51.680 --> 00:05:58.400 And<00:05:51.840> so,<00:05:51.919> that's<00:05:52.080> a<00:05:52.240> place<00:05:52.320> where<00:05:52.560> AI<00:05:52.880> has<00:05:53.120> been<00:05:53.280> really<00:05:53.520> helpful<00:05:53.840> to<00:05:54.080> synthesize<00:05:54.720> all<00:05:54.880> of<00:05:54.960> that<00:05:55.199> information<00:05:55.520> and<00:05:55.759> then<00:05:55.919> equip<00:05:56.240> people,<00:05:57.120> um,<00:05:57.199> to<00:05:57.520> be<00:05:57.680> most<00:05:57.919> effective<00:05:58.240> in 00:05:58.400 --> 00:06:02.400 their<00:05:58.560> roles,<00:05:59.520> um,<00:05:59.919> in,<00:06:00.479> uh,<00:06:00.720> in<00:06:01.039> a<00:06:01.600> realm<00:06:01.840> like<00:06:02.080> insurance. 00:06:02.400 --> 00:06:08.560 <00:06:02.634> Give<00:06:02.867> me<00:06:03.101> a<00:06:03.334> sense<00:06:03.568> for<00:06:03.802> how<00:06:04.035> AI<00:06:04.269> is<00:06:04.502> changing<00:06:04.736> your<00:06:04.970> business,<00:06:05.203> how<00:06:05.437> you've<00:06:05.670> thought<00:06:05.904> about<00:06:06.138> it,<00:06:06.371> how<00:06:06.605> you're<00:06:06.838> integrating<00:06:07.072> it<00:06:07.306> internally,<00:06:07.539> and<00:06:07.773> how<00:06:08.006> you're<00:06:08.240> putting 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uh,<00:06:24.560> in,<00:06:24.720> in<00:06:25.120> their<00:06:25.360> work. 00:06:26.000 --> 00:06:33.120 Um,<00:06:26.479> it<00:06:26.800> also<00:06:27.199> changes<00:06:27.600> for<00:06:27.840> our<00:06:28.080> customers,<00:06:29.360> uh,<00:06:29.520> what<00:06:30.000> really<00:06:30.479> is<00:06:31.280> necessary<00:06:31.840> in<00:06:32.160> training<00:06:32.560> people. 00:06:33.120 --> 00:06:41.520 Um,<00:06:33.446> so<00:06:33.773> if<00:06:34.099> we're<00:06:34.426> kind<00:06:34.752> of<00:06:35.078> in<00:06:35.405> the<00:06:35.731> business<00:06:36.058> of<00:06:36.384> equipping<00:06:36.710> warfighters<00:06:37.037> to<00:06:37.363> be<00:06:37.690> prepared<00:06:38.016> for<00:06:38.342> a<00:06:38.669> future,<00:06:38.995> um,<00:06:39.322> what<00:06:39.648> does<00:06:39.974> that<00:06:40.301> look<00:06:40.627> like<00:06:40.954> when<00:06:41.280> a 00:06:41.520 --> 00:06:44.720 lot<00:06:41.680> of<00:06:41.759> the<00:06:42.080> systems<00:06:42.479> they're<00:06:42.720> operating<00:06:43.199> are<00:06:43.520> autonomous<00:06:44.240> systems? 00:06:44.720 --> 00:06:53.520 So,<00:06:44.880> one<00:06:45.039> example<00:06:45.199> is<00:06:45.440> we're<00:06:45.600> working<00:06:45.840> with,<00:06:46.639> um,<00:06:46.720> the<00:06:46.960> Army<00:06:47.440> to<00:06:48.240> retrain<00:06:48.800> a<00:06:48.960> bunch<00:06:49.120> of<00:06:49.280> their<00:06:49.440> pilots,<00:06:50.319> uh,<00:06:50.880> from<00:06:51.520> just<00:06:52.080> piloting<00:06:52.639> manned<00:06:53.039> aircraft 00:06:53.520 --> 00:07:00.319 to<00:06:53.840> being<00:06:54.240> essentially<00:06:54.720> a,<00:06:55.440> a<00:06:55.759> leader<00:06:56.160> of<00:06:56.400> a<00:06:56.639> combined<00:06:57.120> team<00:06:57.440> of<00:06:57.759> manned<00:06:58.080> and<00:06:58.400> unmanned<00:06:59.520> assets. 00:07:00.319 --> 00:07:08.800 Um,<00:07:00.800> and<00:07:01.039> so<00:07:01.199> that,<00:07:01.919> 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look<00:07:17.360> like<00:07:17.520> in<00:07:17.759> a<00:07:17.919> future<00:07:18.240> where<00:07:18.639> AI<00:07:19.039> is<00:07:19.199> rapidly<00:07:19.680> progressing. 00:07:20.639 --> 00:07:23.280 Um,<00:07:21.440> so<00:07:21.680> there's<00:07:22.000> some<00:07:22.240> really<00:07:22.479> interesting<00:07:22.800> stuff<00:07:22.960> there. 00:07:23.280 --> 00:07:30.479 One<00:07:23.440> of<00:07:23.520> the<00:07:23.680> things<00:07:23.759> that<00:07:23.919> we're<00:07:24.319> experimenting<00:07:24.880> with<00:07:25.120> is,<00:07:25.840> uh,<00:07:25.919> we<00:07:26.080> use<00:07:26.240> an<00:07:26.479> interesting<00:07:26.800> approach<00:07:27.680> called<00:07:27.840> a<00:07:28.080> knowledge<00:07:28.479> graph<00:07:28.880> to<00:07:29.199> essentially<00:07:29.599> structure<00:07:30.160> all<00:07:30.400> of 00:07:30.479 --> 00:07:33.919 the<00:07:30.639> knowledge,<00:07:30.960> skills,<00:07:31.120> and<00:07:31.360> abilities<00:07:31.599> 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to<00:12:34.079> that? 00:12:34.560 --> 00:12:43.120 Yeah,<00:12:34.880> I<00:12:35.120> think<00:12:35.279> that<00:12:35.519> I<00:12:36.399> got<00:12:36.639> into<00:12:36.959> this<00:12:37.200> because<00:12:37.440> I<00:12:37.600> definitely,<00:12:38.639> um,<00:12:39.120> am<00:12:39.279> very<00:12:39.519> mission-driven<00:12:40.160> and<00:12:40.399> care<00:12:40.560> a<00:12:40.800> lot<00:12:40.880> about,<00:12:41.680> uh,<00:12:42.000> essentially<00:12:42.399> the<00:12:42.720> potential 00:12:43.120 --> 00:12:51.279 of<00:12:43.360> people<00:12:43.600> and<00:12:43.920> how<00:12:44.079> can<00:12:44.240> you<00:12:44.959> equip<00:12:45.360> them<00:12:45.600> with<00:12:46.000> learning<00:12:46.399> and<00:12:46.720> tools<00:12:47.440> and,<00:12:48.639> um,<00:12:49.120> direction<00:12:49.519> that<00:12:49.839> helps<00:12:50.000> them<00:12:50.160> perform<00:12:50.560> really<00:12:50.800> well<00:12:50.959> on<00:12:51.120> the 00:12:51.279 --> 00:12:57.839 job.<00:12:51.532> Whether<00:12:51.785> it's<00:12:52.038> a<00:12:52.290> fighter<00:12:52.543> pilot<00:12:52.796> that's<00:12:53.049> trying<00:12:53.302> to<00:12:53.555> get<00:12:53.807> home<00:12:54.060> safely,<00:12:54.313> or<00:12:54.566> it's<00:12:54.819> a—we<00:12:55.072> worked<00:12:55.324> with<00:12:55.577> the<00:12:55.830> Seattle<00:12:56.083> Seahawks<00:12:56.336> this<00:12:56.589> year,<00:12:56.841> and<00:12:57.094> you<00:12:57.347> know,<00:12:57.600> them 00:12:57.839 --> 00:13:01.440 training<00:12:58.079> to<00:12:58.320> win<00:12:58.399> the<00:12:58.560> Super<00:12:58.720> Bowl.<00:12:58.959> Like,<00:12:59.120> that<00:12:59.360> was<00:12:59.440> really<00:12:59.680> cool<00:12:59.760> to<00:13:00.000> be<00:13:00.079> part<00:13:00.240> of<00:13:00.320> that<00:13:00.480> journey. 00:13:01.440 --> 00:13:04.800 Um,<00:13:01.600> or<00:13:01.839> just<00:13:02.000> a<00:13:02.240> person<00:13:02.399> who's,<00:13:02.720> 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you<00:27:34.080> built. 00:27:34.320 --> 00:27:39.120 It's<00:27:34.559> really<00:27:34.720> impressive,<00:27:35.279> and<00:27:35.840> let's<00:27:36.159> have<00:27:36.240> you<00:27:36.400> on<00:27:36.559> again<00:27:37.039> as<00:27:37.279> you<00:27:37.440> continue<00:27:37.679> to<00:27:37.840> grow<00:27:38.080> this<00:27:38.320> thing. 00:27:39.120 --> 00:27:42.320 Thanks,<00:27:39.440> Clay.<00:27:39.840> Appreciate<00:27:40.320> it. ``` ### The machine and the system: IBM, apartheid, and the question of corporate complicity URL: https://www.ceo.com/blog/the-machine-and-the-system-ibm-apartheid-and-the-question-of-corporate-complicity/ Last updated: 2026-08-19T03:18:35.000Z By 1952, IBM was selling electronic tabulators to the apartheid government of South Africa. By the 1960s, it was actively bidding on contracts to build population registration systems that would track millions of people by race. By 1982, it acknowledged in a letter to the U.S. State Department that its computers were being used for South Africa's national identity system. By 1987, it had earned hundreds of millions of dollars from a government the international community had formally sanctioned for crimes against humanity. Throughout it all, IBM maintained that it could not control how its products were used. That position ultimately prevailed in court. In 2015, the Second Circuit Court of Appeals dismissed the claims of apartheid survivors who had sued IBM under the Alien Tort Statute, finding insufficient evidence that IBM had acted with the purpose of facilitating apartheid. In 2016, the Supreme Court declined to hear the case. IBM was legally free. What IBM was not, and has never been, is historically free. The case study it left behind is the most instructive precedent in existence for technology companies navigating the question of what they owe when a powerful government wants to use their tools in ways that harm people. That question has never been more urgent than it is today. ### **The Pattern Before the Pattern** IBM's relationship with the apartheid government did not emerge in a vacuum. In the 1930s and early 1940s, IBM provided Hollerith punch card systems to its German subsidiary for use by the Third Reich. Historian Edwin Black documented the arrangement exhaustively in [IBM and the Holocaust](https://www.amazon.com/IBM-Holocaust-Strategic-Alliance-Nazi/dp/0914153277?ref=ceo.com). The systems were custom-designed to track and sort groups targeted for persecution. The identification numbers tattooed on Auschwitz inmates began as IBM punch-card system numbers. IBM president Thomas J. Watson Sr. received the Merit Cross of the German Eagle from the Nazi government. When U.S. law prohibited dealing with Germany after the war began, IBM chose concealment over withdrawal. The systems IBM later built in South Africa shared the same structural DNA. In both cases, racial classification was the primary identifying characteristic. In both cases, the equipment was leased rather than sold, meaning IBM always knew which agencies were using the machines. In both cases, the technology required close, customized collaboration between IBM and the government. In both cases, IBM said it was not responsible for what governments did with its products. This was not a company that stumbled into complicity once and failed to recognize it. When confronted with a government seeking to identify, classify, and control a population by race, IBM made itself available. It had done it before. It did it again. ### **The Architecture** Apartheid required administration on an industrial scale. The South African state maintained two parallel population registration systems. The Department of the Interior managed the [Book of Life](https://scielo.org.za/scielo.php?script=sci%5Farttext&pid=S0259-01902014000100010&ref=ceo.com), a comprehensive identity document covering citizens classified as non-black. That system ran on IBM hardware. The Plural Affairs Department maintained a separate passbook system tracking more than 25 million Africans classified as black, recording racial classification, name, sex, date of birth, residence, photograph, fingerprints, marital status, and every movement in and out of the country. IBM had competed in 1965 for the passbook contract covering the Black population and lost. It won the Book of Life contract instead. The company was not a reluctant supplier caught up in something it had not sought. It was an active bidder for apartheid contracts. It won one and pursued others. In 1970, the South African government relaunched its population register on new IBM hardware, constructing a 30-story building in Pretoria called Civitas specifically to house it, with a dedicated IBM computer room in the basement. By 1982, the South African police were making 850,000 annual queries at display screens connected to the population registry, examining nearly 180,000 fingerprints and making more than 13,000 positive identifications. IBM equipment was present in the Department of Labor, the Treasury, the Reserve Bank, and the Department of Prisons. The South African Parliament passed legislation making it illegal for companies to report the use of their computers to outside parties. As one [analysis of the period](http://www-cs-students.stanford.edu/~cale/cs201/apartheid.comp.html?ref=ceo.com) concluded, "Computer technology did not merely support the system of oppression, rather the entire country was utterly dependent upon it." ### **The Defense** IBM's position throughout was consistent: it could not control how customers used its products. Annual South African sales reached approximately $300 million by 1982 and an estimated $450 million by 1986, much of it going directly to the South African government. IBM was the largest computer supplier in South Africa throughout the apartheid era. It signed the [Sullivan Principles](https://philadelphiaencyclopedia.org/essays/sullivan-principles/?ref=ceo.com) in 1977, a voluntary corporate code of conduct that committed American companies in South Africa to equal pay and integrated workplaces. IBM paid its Black employees equally. It invested in training and education programs. None of that had anything to do with what the technology was being used for. The Sullivan Principles addressed behavior inside the corporate workplace. They said nothing about what governments were permitted to do with a company's products once those products left the building. IBM met its workplace commitments and simultaneously provided the systems that helped the state classify, track, and control the people those employees went home to at night. IBM formally divested from South Africa in 1987, the same year Leon Sullivan abandoned his own principles, declaring that a decade of constructive engagement had accomplished nothing and calling for full corporate withdrawal. IBM's divestment was structured as a management buyout. The subsidiary continued to operate. IBM products remained. Licensing revenue continued. The machines stayed. ### **What the Courts Said** In 2002, survivors of apartheid-era violence, represented by the [Khulumani Support Group](https://www.business-humanrights.org/en/latest-news/apartheid-reparations-lawsuits-re-so-africa/?ref=ceo.com), filed suit against 23 corporations that had done business in South Africa during the apartheid era. IBM was among them. The plaintiffs included relatives of people tortured, raped, and killed in connection with passbook violations, violations made possible in part by the identification systems IBM's technology had helped build. The litigation lasted 14 years. In 2015, the [Second Circuit Court of Appeals](https://foleyhoag.com/news-and-insights/blogs/global-business-and-human-rights/2015/july/alien-tort-case-development-second-circuit-affirms-dismissal-of-claims-against-ford-and-ibm/?ref=ceo.com) affirmed the dismissal of claims against IBM. The court's reasoning is the part every technology executive should read. The court acknowledged that IBM had acted with knowledge that its technology might facilitate apartheid. It found that knowledge was not enough. To establish liability, the plaintiffs needed to show purposeful facilitation. The court held they had not. "Plaintiffs do not and cannot plausibly allege that by developing hardware and software to collect innocuous population data, IBM's purpose was to denationalize black South Africans and further the aims of a brutal regime." The Supreme Court declined to hear the appeal in 2016\. IBM was legally clear. The court had drawn the line on purpose. IBM knew. IBM did not intend. Under the law, that distinction was sufficient. Under any other framework, it is harder to sustain. ### **The Question That Remains** The subsidiary structure provided legal cover. IBM South Africa had signed the contracts. IBM South Africa had installed the machines. IBM South Africa had trained the operators. IBM New York had set a strategy, provided technology, collected revenue, and maintained the relationship across decades. The parent and the subsidiary were legally distinct. That distinction was large enough to defeat a lawsuit. It was not large enough to change what happened to the people the system was used against. IBM did not set out to administer apartheid. Its machines worked exactly as designed. Population data was collected. People were classified by race. The system identified them. The state controlled, arrested, and in many cases killed them. The technology was not the weapon. It was what made the weapon precise. The "we cannot control how our products are used" defense is now the default posture of the technology industry. It is invoked by social media companies when their platforms are used to incite violence. It is invoked by surveillance technology companies when their tools are used by authoritarian governments. It will be invoked by AI companies when their models are used in ways that harm people. IBM did not invent this defense. It perfected it over two decades and two continents and prevailed in court with it. But here is what the IBM case actually demonstrates: the defense works legally precisely because it is built on a distinction between knowledge and purpose that is morally incoherent. IBM knew what its technology was being used for. It knew who was using it. It had leased the machines, not sold them, which meant it maintained continuous relationships with the agencies operating them. The distance between knowing and intending, in that specific context, is not a distance any serious person should find meaningful. That distinction is where today's AI industry lives. The companies building the most powerful AI systems in history know, or can know, what their technology is capable of. They know which governments are buying it and what those governments have done with technology before. The question of whether they intended the specific harm that resulted is one that courts may ultimately find in their favor. It is not a question that history will. Anthropic drew a line. It said its technology would not be used for mass domestic surveillance or fully autonomous weapons. The government called that a supply chain risk. A federal judge called the government's response illegal retaliation. The argument about where the line belongs is genuinely difficult. The argument about whether there should be a line is not. IBM spent 35 years proving what happens to companies that decide there should not be one. The machines worked. The system functioned. Millions of people were classified, tracked, controlled, and harmed. IBM collected the revenue and said it was not responsible. The courts agreed. That is one way to run a technology company. It is not the only way. And it is not, whatever the legal outcome, a defense that holds. ### When the Pentagon comes knocking URL: https://www.ceo.com/blog/when-the-pentagon-comes-knocking-ai-ethics-and-the-fight-over-who-controls-america-s-most-powerful-technology/ Last updated: 2026-08-14T00:23:40.000Z On the evening of February 27, as the United States and Israel were preparing to launch airstrikes on Iran, President Trump took to Truth Social to order the federal government to stop using the AI technology of one of America's most prominent artificial intelligence companies. Defense Secretary Pete Hegseth followed within hours, designating Anthropic, the maker of the Claude AI model, a "supply chain risk to national security." It was a label previously reserved for foreign adversaries like China's Huawei. It had never before been applied to an American company. Within the same news cycle, OpenAI CEO Sam Altman announced that his company had reached a deal with the Pentagon. The episode that produced those two events is the most consequential confrontation yet between the AI industry and the federal government. It has drawn in federal courts, members of Congress, and nearly every major AI company. It has also forced a reckoning that defense tech CEOs have long known was coming: When the government asks you to remove the guardrails on your technology, what do you do? Andrew Powell has thought about that question carefully. Powell is the co-founder and CEO of [Ethos](https://www.ethossystems.com/?ref=ceo.com), which builds AI-powered readiness platforms for the U.S. Department of Defense, training military personnel across Air Force, Navy, and Army installations on the knowledge and skills they need to perform high-stakes missions. Ethos is embedded in the classified networks of the U.S. military. Its customers are war fighters. Powell knows this world from the inside. In a [recent interview with ](https://www.ceo.com/c/podcast/are-your-people-ready-inside-ethos-the-ai-platform-training-the-u-s-military)[CEO.com](http://ceo.com/?ref=ceo.com), he laid out his view before the Anthropic dispute reached its peak. It is a view worth understanding because it represents a serious answer to the question now consuming the industry. "Our government leaders are the ones who should be entrusted with deciding the law, not unelected tech companies," Powell said. He is skeptical that private technology companies should position themselves as the primary check on how the government uses the tools it purchases. That is the job of elected officials, courts, and the democratic system. At the same time, he expressed something that went beyond legal philosophy. "I would hope that we all think about the consequences of our actions here and try to steer things towards the world that we want to live in in the future." Both of those ideas, the limits of corporate authority over government decisions and the obligation to think about consequences, turned out to be exactly what the Anthropic crisis was about. ### **How it started** The relationship between Anthropic and the Pentagon began as a success story. In [July 2025](https://www.anthropic.com/news/anthropic-and-the-department-of-defense-to-advance-responsible-ai-in-defense-operations?ref=ceo.com), the two parties signed a $200 million contract, and Anthropic's Claude became the first frontier AI model approved for use on the DoD's classified networks. The company had earned that position through years of careful work building what it called Claude Gov models, custom-built for national security customers and deployed on infrastructure powered by Amazon Web Services. The contract included two restrictions that Anthropic had insisted on from the beginning. Its technology could not be used for mass domestic surveillance of American citizens. It could not power fully autonomous weapons systems, defined as those capable of selecting and engaging targets without direct human oversight. The Pentagon agreed to those terms. The trouble began in the fall of 2025, when the DoD, operating under the Trump administration's renaming of the department to the Department of War, began pushing for broader access. Defense Secretary Pete Hegseth issued a memorandum calling for all DoD AI contracts to incorporate standard "any lawful use" language within 180 days. Adding that phrase to the Anthropic contract would have effectively nullified both restrictions. Negotiations continued and were, by most accounts, initially cordial. Anthropic offered to help the DoD transition to another vendor if an agreement could not be reached. But the talks became public in January, and once they did, the temperature rose quickly. ### **The ultimatum** On February 24, Hegseth gave Anthropic co-founder and CEO Dario Amodei a deadline: agree by 5:01 p.m. on Friday, February 27, to allow unrestricted use of Claude for all legal purposes, or face consequences. Amodei did not agree. In a [public statement](https://www.anthropic.com/news/statement-department-of-war?ref=ceo.com), he explained in detail why. On autonomous weapons, he was direct: frontier AI systems are "simply not reliable enough to power fully autonomous weapons," and without proper oversight they "cannot be relied upon to exercise the critical judgment that our highly trained, professional troops exhibit every day." On surveillance, his argument was both more nuanced and, in some ways, more unsettling. Amodei told [Fortune](https://fortune.com/2026/02/28/anthropic-ceo-dario-amodei-patriotic-americans-trump-hegseth-mass-surveillance-autonomous-weapons/?ref=ceo.com) that Anthropic supports 98 to 99 percent of the military's use cases. His concern was specifically that AI has made certain forms of surveillance newly possible without those activities being newly illegal. "That actually isn't illegal. It was just never useful before the era of AI. So there's this way in which domestic mass surveillance is getting ahead of the law," he said. "The technology's advancing so fast that it's out of step with the law." Powell had made a strikingly similar observation in the CEO.com interview, without reference to any specific dispute. "If you do have completely unfettered pursuit of technology purely for the goal of the technological advancement with no regard for what the societal or economic impact would be, then you probably are going to run afoul of people who are more focused on, well, are we building a country that I want to live in?" The concern about technology outpacing accountability is one that serious people in the defense tech world share across the ideological spectrum. The Pentagon's response to Amodei's statement was immediate. On February 27, Trump ordered all federal agencies to cease using Anthropic's products, with a six-month phase-out period. Hegseth designated the company a supply chain risk, requiring defense contractors, including Amazon, Microsoft, and Palantir, to certify they were not using Claude in their military work. Pentagon official Emil Michael called Amodei "a liar" who "has a God-complex." Hegseth reposted both of Michael's messages. Amodei called the threats "inherently contradictory," noting that "one labels us a security risk; the other labels Claude as essential to national security." Powell watched all of this with frustration more than alarm. He had expressed hope in the CEO.com interview that Anthropic and the Pentagon would find a resolution. He considers Anthropic's models among the best in the world and has friends who work there. On the supply chain risk designation specifically, he did not hold back. "I thought that was kind of ridiculous to slap that on them when it's like, clearly they have been a tremendous asset so far in kind of the classified work." ### **The OpenAI question** The same evening Anthropic was blacklisted, Sam Altman posted on X announcing that OpenAI had reached its own deal with the Pentagon. The timing was immediately controversial. In a post on X, Altman said his company's new defense contract included protections addressing the same issues that had become a flashpoint for Anthropic. "Two of our most important safety principles are prohibitions on domestic mass surveillance and human responsibility for the use of force, including for autonomous weapon systems," he wrote. He also said OpenAI had asked the Pentagon to offer those same terms to all AI companies, including Anthropic, and that he disagreed with the supply chain risk designation. The reaction, both inside and outside the AI industry, was sharp. Critics accused OpenAI of opportunism. Consumers sent Claude surging past ChatGPT to the top of Apple's App Store. Chalk graffiti criticizing OpenAI appeared outside its San Francisco offices. More than 60 OpenAI employees signed an open letter supporting Anthropic's position. Over 300 Google employees sent a similar letter to their own leadership. The picture that emerged over the following days was more complicated than simple opportunism, though the optics were genuinely bad. Altman had told employees in an internal memo the day before the announcement that OpenAI shared Anthropic's red lines on surveillance and autonomous weapons. He had privately been trying to persuade the Pentagon to find an off-ramp for Anthropic. [Axios reporting](https://www.axios.com/2026/03/26/sam-altman-openai-anthropic-pentagon?ref=ceo.com) on internal Slack messages showed Altman characterizing his role as trying to "save" his competitor, while simultaneously acknowledging that the optics might not look good and privately venting that Amodei had spent years trying to undermine him. When the deal was announced, Altman said OpenAI had secured contractual protections against the same two issues that had become a flashpoint for Anthropic. He pushed the Pentagon to offer the same terms to all AI companies. He publicly stated he disagreed with the supply chain risk designation. He also admitted he had moved too fast. "We were genuinely trying to de-escalate things and avoid a much worse outcome," he said, "but I think it just looked opportunistic and sloppy." He then amended the contract, adding more explicit language restricting domestic surveillance. Amodei was not persuaded. In an internal memo that became public, he called Altman's messaging "straight up lies," writing that "the main reason they accepted the DoD's deal and we did not is that they cared about placating employees, and we actually cared about preventing abuses." He later apologized for the tone of the memo. Legal experts were divided on whether OpenAI's contract actually provided meaningful protections or merely repackaged the same "any lawful use" framework that Anthropic had refused. Senator Elizabeth Warren [opened an investigation](https://www.warren.senate.gov/newsroom/press-releases/warren-opens-investigation-into-pentagons-designation-of-anthropic-as-national-security-risk-new-openai-contract?ref=ceo.com) into both the Anthropic designation and the OpenAI contract, writing that she was concerned the DoD appeared to be "trying to strong-arm American companies into providing the Department with the tools to spy on American citizens and deploy fully autonomous weapons without adequate safeguards." ### **The courts decide** Anthropic filed suit on March 9 in a California federal court, arguing the government's actions had caused irreparable harm and requesting an injunction against the supply chain risk designation. On March 26, [Judge Rita Lin granted that injunction](https://www.cnbc.com/2026/03/26/anthropic-pentagon-dod-claude-court-ruling.html?ref=ceo.com). Her ruling ran 43 pages. The core finding was that the government had not acted out of genuine national security concern. It had punished a company for speaking publicly. An internal DoD memo had stated that Anthropic's risk level escalated because it was engaging in an "increasingly hostile manner through the press." That memo was, in the judge's reading, dispositive. Amodei had published an essay on AI safety. The company had issued a public statement explaining its position in the contract dispute. Those are constitutionally protected acts. "Punishing Anthropic for bringing public scrutiny to the government's contracting position is classic illegal First Amendment retaliation," Lin wrote. She also rejected the government's broader theory of what the supply chain risk designation allows. "Nothing in the governing statute supports the Orwellian notion that an American company may be branded a potential adversary and saboteur of the U.S. for expressing disagreement with the government," she wrote. That sentence matters beyond this case. It establishes, at least at the preliminary injunction stage, that the government cannot use the extraordinary power of a supply chain risk designation as leverage in a contract negotiation. It cannot threaten to functionally destroy a company because that company said something publicly that the government did not like. The government has indicated it will seek an emergency stay from the Ninth Circuit, and a separate case is already pending in the D.C. Circuit. The legal battle is far from over. ### **The real stakes** The Anthropic episode is not primarily a story about one company's contract dispute. It is a story about the terms on which the most powerful technology ever built will be integrated into the U.S. military's apparatus, and who gets to set them. Powell's answer, offered before the storm arrived, is that elected leaders and democratic institutions should make those calls, not private companies acting unilaterally. It is a coherent and genuinely held position. But Judge Lin's ruling suggests that the answer is not that simple. Democratic institutions include the courts. And the courts have now said, at least preliminarily, that even the government has limits on what it can do when a private company disagrees with it publicly. What the Anthropic case has demonstrated is that AI companies can no longer treat their government relationships as purely commercial arrangements, quietly managed and rarely examined. The decisions these companies make about what their technology will and will not do are consequential enough that the public, Congress, and federal judges are now paying close attention. That scrutiny is not going away. For every CEO in the defense tech world, including Powell, the question is no longer theoretical. It is immediate and personal: When the government asks you to move the line, where do you stand? ### The bill always comes due URL: https://www.ceo.com/blog/the-bill-always-comes-due/ Last updated: 2026-08-19T03:15:18.000Z On December 15, 1953, the heads of six major American tobacco companies sat down with the public relations firm Hill & Knowlton in a New York City hotel room. The immediate problem was a *Reader's Digest* article called "Cancer by the Carton." The piece had reached millions of Americans, summarized a growing body of research linking cigarettes to lung cancer, and caused a measurable drop in consumption and a fall in tobacco stock prices. The companies faced a choice. Investigate whether the science was right and act on what they found. Or organize to ensure the public never felt certain enough to act. Hill & Knowlton's president, John W. Hill, advised that a flat denial would backfire. What would work was manufacturing the appearance of scientific disagreement. If credible voices could be found to question the research, if the public could be made to feel that experts were divided, the industry could continue operating under the cover of uncertainty indefinitely. That meeting produced [the "Frank Statement to Cigarette Smokers,"](https://en.wikipedia.org/wiki/A%5FFrank%5FStatement?ref=ceo.com) published on January 4, 1954, in more than 400 newspapers, reaching an estimated 43 million Americans. It questioned the cancer research, expressed concern for customers' health, and promised to fund independent scientific inquiry. It was one of the most consequential acts of corporate deception in American history, and it worked for nearly 40 years. A federal judge later described it as the opening act of a conspiracy to make false and misleading public statements about cigarettes that continued without interruption until the industry finally settled in 1998. --- The tobacco case is not primarily a story about product harm. It is a story about the gap between what executives said publicly and what they wrote to each other. A 1963 internal memo by Brown & Williamson's general counsel, [cited in the Campaign for Tobacco-Free Kids document archive,](https://www.tobaccofreekids.org/press-releases/id%5F0082?ref=ceo.com) states it plainly: "Nicotine is addictive. We are, then, in the business of selling nicotine, an addictive drug." That memo was written 31 years before the company's CEO stood before Congress and said the opposite under oath. The concealment was not passive. [Tobacco companies genetically engineered their crops](https://truthinitiative.org/research-resources/harmful-effects-tobacco/how-big-tobacco-made-cigarettes-more-addictive?ref=ceo.com) to contain twice the natural level of nicotine and altered cigarette designs to increase nicotine delivery by 14.5 percent. Ammonia was added to tobacco blends to convert nicotine into a form that reaches the brain faster. All of it was documented internally. None of it was disclosed. The [Minnesota Tobacco Trial,](https://pubmed.ncbi.nlm.nih.gov/9777818/?ref=ceo.com) concluded in 1998, confirmed what the documents showed: the industry had known for decades, and had actively engineered its products to be more addictive while publicly denying that addiction was possible. --- Alongside the concealment of addiction science, the industry was executing a parallel strategy: reach children before they were old enough to evaluate the risks. The internal logic was financially rational. Most lifetime smokers started before 18\. An [internal R.J. Reynolds memo](https://pmc.ncbi.nlm.nih.gov/articles/PMC3413965/?ref=ceo.com) stated the objective plainly: "To ensure increased and longer-term growth for Camel Filter, the brand must increase its share penetration among the 14-24 age group." A Florida attorney involved in that state's tobacco litigation later [summarized the strategy](https://www.tortmuseum.org/the-tobacco-cases/?ref=ceo.com) in plain language: "Hook kids at 12 years of age, and they'd be hooked for life." The most visible execution was Joe Camel. R.J. Reynolds introduced the cartoon character in 1988 to revive the flagging Camel brand. [A 1991 study in the Journal of the American Medical Association](https://en.wikipedia.org/wiki/Joe%5FCamel?ref=ceo.com) found that children aged three to six recognized Joe Camel and the Disney Channel logo with equal frequency. Camel's market share among youth smokers rose sharply. The [Federal Trade Commission eventually charged R.J. Reynolds](https://en.wikipedia.org/wiki/Joe%5FCamel?ref=ceo.com) with violating federal law for targeting underage smokers. Joe Camel was retired in 1997 after nearly a decade. --- The defining public moment came on [April 14, 1994,](https://senate.ucsf.edu/tobacco-ceo-statement-to-congress?ref=ceo.com) when the chief executives of the major American tobacco companies appeared together before Congress for the first time. Rep. Ron Wyden of Oregon asked each CEO a direct question: Do you believe nicotine is not addictive? They answered in sequence. [All seven said no.](https://www.tobaccofreekids.org/press-releases/id%5F0082?ref=ceo.com) William Campbell of Philip Morris. James Johnston of R.J. Reynolds. Joseph Taddeo of U.S. Tobacco. Edward Horrigan of Liggett Group. Andrew Tisch of Lorillard. Thomas Sandefur of Brown & Williamson. Donald Johnston of American Tobacco. Under oath. Before a national television audience. While internal documents dating back 31 years confirmed they had known the opposite to be true. [Within two years, all seven were under federal investigation](https://www.c-span.org/program/american-history-tv/congress-investigates-tobacco-industry/638858?ref=ceo.com) for potentially lying under oath. Not one remained in their position. The image of those seven men in a row, right hands raised, became one of the most enduring symbols of institutional dishonesty in American business history. --- Documents can be contested. What broke the industry's hold on the public narrative was a person who had been inside and could confirm the gap from firsthand knowledge. Jeffrey Wigand was the Vice President of Research and Development at Brown & Williamson. He was hired to develop safer cigarettes, clashed with executives over nicotine manipulation and the addition of known carcinogens, and was fired in 1993\. He had signed a non-disclosure agreement. [On February 4, 1996, he appeared on *60 Minutes*](https://www.cbsnews.com/news/60-minutes-most-famous-whistleblower/?ref=ceo.com) and told Mike Wallace that the company had deliberately engineered its tobacco blend to accelerate nicotine absorption, that executives knew they were selling an addictive product, and that internal safety concerns had been treated as threats to be managed. Brown & Williamson [hired a private investigation firm](https://en.wikipedia.org/wiki/Jeffrey%5FWigand?ref=ceo.com) to produce a 500-page dossier on Wigand and distributed it to media organizations. They sued him for breach of his non-disclosure agreement. He received death threats. None of it worked. His testimony became a pivotal factor in the state attorneys general litigation. He remains the highest-ranking tobacco industry executive to have come forward publicly. What Wigand established, beyond any specific revelation, was the existence of the gap itself. Once an insider confirmed from the inside that executives knew things they were not saying, the legal structure built around denial had no foundation left. --- [On November 23, 1998,](https://en.wikipedia.org/wiki/Tobacco%5FMaster%5FSettlement%5FAgreement?ref=ceo.com) the four largest tobacco companies reached the Master Settlement Agreement with the attorneys general of 46 states. They committed to paying [at least $206 billion over the first 25 years,](https://www.naag.org/our-work/naag-center-for-tobacco-and-public-health/the-master-settlement-agreement/?ref=ceo.com) with payments continuing in perpetuity, along with sweeping restrictions on youth marketing and the mandatory public release of tens of millions of internal documents. [Between 1998 and 2019, U.S. cigarette consumption dropped by more than 50 percent.](https://www.naag.org/our-work/naag-center-for-tobacco-and-public-health/the-master-settlement-agreement/?ref=ceo.com) Regular smoking among high schoolers fell from a near-peak of 36.4 percent in 1997 to 6 percent in 2019\. The [14-million-document archive](https://www.tortmuseum.org/98-tobacco-settlement/?ref=ceo.com) of internal industry files, now permanently public, transformed how regulators, researchers, and litigants approached corporate concealment for the next generation. --- The tobacco companies believed the internal documents would never see daylight. They had non-disclosure agreements, legal teams, and four decades of precedent protecting their internal communications. None of it held. The strategy worked, in the narrow sense, for a long time. The companies grew, generated enormous profits, and retained market share for decades while the documents accumulated. What ended it was not a regulatory breakthrough or a crisis of conscience. It was the documents themselves. When the gap between what the executives said publicly and what they wrote to each other became part of the permanent public record, the consequences arrived quickly and did not stop. The question for any executive is not whether this pattern belongs only to tobacco. It does not. The question is whether your organization has built a version of that gap: between what internal research shows, what safety teams have flagged, what employees have raised in writing, and what you say publicly. That gap, if it exists, is documented somewhere. The bill came due in 1998\. It took 40 years to arrive. When it did, it arrived all at once. ### The bill comes due URL: https://www.ceo.com/blog/the-bill-comes-due/ Last updated: 2026-08-14T00:17:16.000Z In 1762, a French philosopher named Jean-Jacques Rousseau published a book that got him banned from Paris and Geneva simultaneously. The book was called [*Émile, or On Education*](https://www.gutenberg.org/files/5427/5427-h/5427-h.htm?ref=ceo.com). Authorities [burned it in the streets](https://en.wikipedia.org/wiki/Emile,%5For%5FOn%5FEducation?ref=ceo.com). It went on to change how the Western world thinks about childhood. Rousseau's argument was simple and radical. Children are born good. Society corrupts them. The job of a parent or teacher is not to fill a child with knowledge. It is to protect them from harm long enough for their own reason to develop. He called this Negative Education. Not negative as in harmful. Negative as in protective. As in clearing the space around a child rather than cramming it full. He wrote: "The first education, then, ought to be purely negative. It consists not at all in teaching virtue or truth, but in shielding the heart from vice and the mind from error." His fictional student, Émile, is raised in the French countryside. No books until age 12\. No formal lessons. No exposure to the vanity and competition of Paris. The child learns through his senses, through physical experience, through direct contact with the natural world. If he breaks a window, Rousseau does not lecture him on property rights. He lets him feel the cold wind come through the broken pane. The environment teaches. The adult protects. The thing Rousseau feared most was what he called social contagion. He believed that exposing a child too early to the machinery of adult society, its competitions, its vanity, its relentless pressure to perform and compare, would corrupt the child before they had the inner resources to resist it. The harm was not dramatic. It was cumulative. A slow, invisible pressure applied before the child's heart and mind were ready to process it. He was not describing a technology that existed. He was describing one that would be invented 262 years later, refined over roughly a decade, and placed into the hands of children as young as six. What Rousseau feared was a system specifically engineered to maximize the time a child spent inside it. A system that replaced the countryside with a feed. That replaced physical sensation with a notification. That replaced a child's developing sense of self with an infinite scroll of other people's curated lives. That discovered through its own internal research that 11-year-old girls were its most reliable returning users and treated it as a product milestone rather than a warning sign. He believed that any adult who understood this and allowed it to happen anyway was not making a passive omission. It was an active harm. On March 25, 2026, a jury in Los Angeles agreed. --- The verdict itself was straightforward. A jury of twelve people [found Meta and YouTube liable](https://www.npr.org/2026/03/25/nx-s1-5746125/meta-youtube-social-media-trial-verdict?ref=ceo.com) on all counts in a case accusing the companies of deliberately designing their platforms to addict a child and damage her mental health. [Total damages came to $6 million.](https://www.cnn.com/2026/03/25/tech/social-media-addiction-trial-jury-decision?ref=ceo.com) That number will not register on any earnings call either company has ever held. What will register is the legal theory the verdict validated. For the first time in history, a jury held that the architecture of a social media platform, not the content on it, constitutes a defective product. The plaintiff's lawyers argued that it was not what Kaley saw on Instagram that harmed her. It was the way Instagram was built. Infinite scroll. Autoplay. Notification systems calibrated to create urgency. Beauty filters that, according to 18 external experts Meta had consulted, raised serious concerns about harm to young girls. Features the company understood, evaluated, and kept. That is a different kind of ruling. It does not ask what a child was exposed to. It asks who designed the exposure mechanism and whether they knew what it would do. The case centered on a 20-year-old woman from Chico, California, known in court as Kaley. She started using YouTube at age 6\. Instagram at age 9\. By the time she was a teenager, she spent more than 16 hours on Instagram in a single day. She developed anxiety, body dysmorphia, and suicidal thoughts. Her mother tried to intervene. The algorithm was more persistent than her mother. Meta bears 70 percent of the liability. YouTube, 30\. Both companies said they will appeal. Both said they disagree with the verdict. Neither said they would change anything. This verdict did not arrive alone. One day earlier, [a New Mexico jury found Meta liable](https://www.npr.org/2026/03/24/g-s1-115019/new-mexico-meta-children-mental-health?ref=ceo.com) for knowingly harming children's mental health and concealing what it knew about child sexual exploitation on its platforms. That jury ordered Meta to pay $375 million. Two verdicts in two days. They are the first of what could be thousands. There are currently [2,407 pending lawsuits](https://www.robertkinglawfirm.com/personal-injury/social-media-addiction-lawsuit/?ref=ceo.com) in federal multi-district litigation against social media companies. More than 10,000 individual cases. Nearly 800 school district claims. Over 40 state attorneys general have sued Meta alone. The lawyers involved now compare this wave to the tobacco litigation of the 1990s. That comparison is not rhetoric. It is a timeline. --- The companies have long argued that the science does not support a link between their platforms and mental health harm in children. Mark Zuckerberg has said this in Congress, in interviews, and [under oath in Los Angeles](https://www.nbcnews.com/tech/tech-news/mark-zuckerberg-testifies-landmark-social-media-addiction-trial-rcna259422?ref=ceo.com). The existing body of scientific work, he has said repeatedly, has not proved that social media causes mental health harms. He is not entirely wrong. And that partial truth is precisely the problem. [Rates of depression among U.S. teenagers rose 106 percent between 2010 and 2020\. Anxiety rose 134 percent](https://hsph.harvard.edu/news/how-to-calm-the-anxious-generation/?ref=ceo.com) in the same period. Those numbers did not drift upward gradually over decades. They spiked. The inflection point was around 2012, when Instagram's user base exploded from 10 million to 90 million, the front-facing camera became standard, and the platforms that social psychologist Jonathan Haidt has studied exhaustively began their full penetration of adolescent life. [The same pattern showed up](https://jonathanhaidt.com/anxious-generation/?ref=ceo.com) in the UK, Canada, and across Western Europe. This was not a local phenomenon. The gender divide in the data is not subtle. [A 2024 Pew Research survey](https://www.pewresearch.org/internet/2025/04/22/teens-social-media-and-mental-health/?ref=ceo.com) found that 34 percent of teen girls say social media makes them feel worse about their own lives, compared with 20 percent of boys. Girls report more pressure to post, more exposure to content that triggers comparison, more sleep disruption, and more anxiety about appearance. These are not mysterious findings. They describe what happens when you take a developing adolescent girl, place her inside a system that ranks her photographs and quantifies her social standing in real time, and then calibrate that system to keep her inside it as long as possible. [A 2024 systematic review](https://pmc.ncbi.nlm.nih.gov/articles/PMC12539155/?ref=ceo.com) drawing on nearly 15 years of research found that excessive social media use is associated with impaired attention, reduced working memory, and diminished executive functioning. [A separate review](https://pmc.ncbi.nlm.nih.gov/articles/PMC12165459/?ref=ceo.com) found that increased screen time correlates with altered neural development in areas governing social cognition. Rousseau believed the years before adolescence were the critical window for a child's reason to develop free from external pressure. Neuroscience now has a name for what he was describing. These reviews suggest the platforms may be reshaping that window from the inside. Not everyone agrees on how much of the causation runs directly from platform to harm. [Developmental psychologist Candice Odgers of UC Irvine](https://www.nature.com/articles/d41586-024-00902-2?ref=ceo.com), reviewing hundreds of studies, found a "mix of no, small and mixed associations" and argued that young people with existing mental health problems may simply be heavier users of platforms, not the other way around. That is a serious argument from a serious researcher, and it deserves to be taken seriously. But the scientific debate and the legal question are different questions. The legal question is not whether the science is settled. The legal question is what these companies knew, when they knew it, and what they chose to do with that knowledge. On that question, the internal documents introduced at trial are not ambiguous. [A 2022 internal document](https://www.cnn.com/2026/02/19/tech/takeaways-mark-zuckerberg-testifiessocial-media-child-mental-health?ref=ceo.com) projected that average time spent on Instagram would increase from 40 minutes per day to 46 minutes per day by 2026\. [Another showed that 11-year-olds](https://www.npr.org/2026/03/25/nx-s1-5746125/meta-youtube-social-media-trial-verdict?ref=ceo.com) were four times more likely to return to Instagram than to competing apps, despite the platform requiring users to be 13 or older. [One internal review](https://www.nbcnews.com/tech/tech-news/mark-zuckerberg-testifies-landmark-social-media-addiction-trial-rcna259422?ref=ceo.com) estimated that more than 4 million children under 13 were using Instagram in 2015\. One document stated the company's ambition plainly: "If we wanna win big with teens, we must bring them in as tweens." An internal email cited in the New Mexico trial showed a Meta employee writing that informing parents about what their children were viewing on the platform would "ruin the product from the start." This is not a company wrestling with uncertainty. This is a company that understood exactly what it had built, who was using it, and how young they were; received warnings from its own safety teams; and chose growth. Rousseau's fear was not abstract. It was this. An adult institution, with full knowledge of a child's vulnerability, deciding that vulnerability was a feature. --- Mark Zuckerberg has now stood before a U.S. Senate committee and a Los Angeles jury and said essentially the same thing both times. The platforms are not addictive by design. The science is inconclusive. Meta has invested more in child safety than any company in the world. And, when pressed, he is sorry for what these families have been through. [The moment at the 2024 Senate hearing](https://www.nbcnews.com/tech/social-media/mark-zuckerberg-apologizes-parents-online-child-safety-hearing-rcna136578?ref=ceo.com) has been replayed many times. Sen. Josh Hawley challenged Zuckerberg to face the parents in the gallery, parents who believed their children had been harmed or killed because of his platforms. Zuckerberg stood, turned away from the microphone, and addressed them directly. "I'm sorry for everything you've all gone through. No one should have to go through the things that your families have suffered. This is why we invest so much and are going to continue doing industry-leading efforts to make sure that no one has to go through the types of things that your families have had to suffer." He apologized for their suffering. He did not accept responsibility for its cause. That is a precise and deliberate distinction, and he has maintained it in every forum since. [In the Los Angeles courtroom, under oath](https://www.npr.org/2026/02/18/nx-s1-5717117/zuckerberg-testimony-social-media-addiction-trial?ref=ceo.com), he said: "I'm focused on building a community that is sustainable. If you do something that's not good for people, maybe they'll spend more time short term, but if they're not happy with it, they're not going to use it over time." That is a reasonable-sounding sentence. It is also directly contradicted by a decade of internal documents showing the company tracked, measured, and optimized for the time spent by users who were not old enough to be on the platform at all. The jury deliberated for 43 hours. They found him liable. Neal Mohan, who became YouTube's CEO in 2023 and was named [TIME's CEO of the Year for 2025](https://time.com/7337793/ceo-of-the-year-neal-mohan-youtube-politics-creators-kids-future/?ref=ceo.com), has been quieter on this subject. YouTube's defense throughout the trial rested on a single argument: YouTube is a streaming platform, not a social media site, and the case misunderstands the product. YouTube's CEO was not called to testify. In his [2024 annual letter](https://blog.youtube/inside-youtube/2024-letter-from-neal/?ref=ceo.com), Mohan wrote that creating a healthy online experience for kids is important and that YouTube supports the growth of kids and teens "thoughtfully and in coordination with parenting and mental health experts." That is a corporate sentence. It does not say much. What says more is what both men do at home. In December 2025, just weeks before the Los Angeles trial began, Mohan [told TIME Magazine](https://www.cnbc.com/2025/12/13/youtubes-ceo-is-latest-tech-boss-limiting-his-kids-social-media-use.html?ref=ceo.com) that he limits his own children's access to YouTube and other social media platforms. "We do limit their time on YouTube and other platforms and other forms of social media," he said. "We're not perfect by any stretch." He is not alone. YouTube's former CEO, Susan Wojcicki, barred her children from browsing YouTube unless they were using the app's children's version. Steve Jobs limited his children's iPad use. Evan Spiegel of Snapchat restricts his children's screen time. Tim Cook has expressed public concerns about overuse. These are the people who built the products, who know the research, who sit in the rooms where the engagement metrics are reviewed. And when they go home, they impose exactly the kind of protective boundaries on their own children that Rousseau prescribed in 1762. Think about what that means. These executives have access to the most complete picture of what these platforms do to developing minds. They have the internal data, the safety reports, the engagement research, the neurological studies. They have more information than any parent in America about the effects of these products on children. And their conclusion, for their own families, is: limit it. Control it. Keep them away from it until they are old enough to handle it. They have decided their children deserve the protection they are not offering to yours. Rousseau would have called that a betrayal of the fundamental adult obligation. He did not think protecting children was optional. He thought it was the whole job. --- The liability question will work its way through the courts for years. Appeals will be filed. Some verdicts will be reversed. Others will stick. The settlements that eventually come will likely dwarf what was awarded in Los Angeles. That process has its own logic, and it will proceed whether or not Silicon Valley cooperates. But there is a question here that applies to every executive reading this, not just those running social media companies. These companies knew things. The documents confirm it. They knew about the harm to teen girls. They knew minors under 13 were using their platforms at scale. They knew their design features were driving compulsive use. They received warnings from their own safety teams. They had employees who raised alarms and were pushed aside. And through all of it, they said publicly that the science was uncertain, that causation was unproven, that they were investing in safety, that they took this seriously. That is a specific behavior. It has a name. It is using the legitimate ambiguity in public research as cover to continue a practice that your private research has already clarified. It is commissioning studies and not publishing the results. It is acknowledging "problematic use" in internal emails while denying addiction in courtrooms. It is the careful management of what you admit to knowing and when. The tobacco companies did this for decades. The opioid manufacturers did it. The social media companies have done it, and the documents that will eventually surface in 2,407 pending lawsuits will show exactly how they did it. The question for every CEO reading this is not an exotic one. It is: what does your internal data tell you that your public statements do not reflect? What has your safety team, your research team, or your legal team told you about your product that has not made it into a press release? What are you using scientific uncertainty to avoid doing? That is not a hypothetical. It is a pattern, and it does not stay private forever. Rousseau believed that the deepest responsibility of any adult is to protect a child from the world until the child is ready to meet it. He spent his career arguing that this responsibility could not be delegated, deferred, or dissolved by institutional convenience. The adults knew. That was enough. Knowing and not acting was the harm. The bill comes due eventually. It always does. The only question is who pays it, and when. Kaley is 20 years old. She started using YouTube at 6 and Instagram at 9\. For roughly a decade, the most sophisticated engagement systems ever built were pointed at a child. When she told a jury what that did to her, twelve people believed her. So did the verdict. ### Alan Mulally and the Ford turnaround URL: https://www.ceo.com/blog/alan-mulally-and-the-ford-turnaround/ Last updated: 2026-08-19T03:11:24.000Z When Alan Mulally arrived at Ford in September 2006, the company [anticipated a loss of $17 billion](https://www.hbs.edu/faculty/Pages/item.aspx?num=59955&ref=ceo.com). He had never built a car. He had been recruited from Boeing by Bill Ford, great-grandson of the founder, who had tried to run the company himself and could not fix it. Ford had not hired an outsider as CEO in its 103-year history. The culture Mulally inherited had been decades in the making. Bryce G. Hoffman, who was granted unprecedented access to Ford's leadership for his book [*American Icon*](https://brycehoffman.com/books/american-icon/?ref=ceo.com), described it in three words: infighting, backstabbing, and excuses. Regional divisions operated as [warring fiefdoms](https://www.penguinrandomhouse.com/books/208637/american-icon-by-bryce-g-hoffman/?ref=ceo.com). Executives who surfaced problems were [punished for it](https://blionline.org/news/2152-want-to-save-your-company-follow-fords-two-step-blueprint-2018-04-14?ref=ceo.com). Everyone had learned the same lesson: protect yourself, perform competence, and let someone else deliver the bad news. Mulally's first move was a meeting. ## The Sea of Green He called it the Business Plan Review. Weekly. Mandatory. Every senior leader, in person, no surrogates. Each executive would present their division's status using a color system: green for on track, yellow for issues with a plan, red for off plan with no clear solution. At the first several BPRs, [every chart was green](https://globalcoachgroup.com/how-alan-mulally-turned-transparency-into-a-turnaround-strategy/?ref=ceo.com). Mulally looked at the room and said: ["You guys, you know we lost a few billion dollars last year. Is there anything that's not going well?"](https://www.conference-board.org/research/human-capital-briefs/blg-00-1-3201?ref=ceo.com) Nobody moved. The meeting ended. Mulally walked out. This happened week after week. Billions in losses. Green slides. Silence. The company was performing health while bleeding to death, and everyone in the room knew it, and no one was willing to be the person who said so. ## The Fork Then Mark Fields made a decision. Fields ran Ford's Americas division. He was not a junior executive. He was not expendable. He had spent years learning the same survival instincts as everyone else in that room: read the room, manage up, keep your slide green. But the Ford Edge, a new SUV scheduled for launch, had a [technical problem with its rear liftgate latch](https://www.conference-board.org/research/human-capital-briefs/blg-00-1-3201?ref=ceo.com). The vehicle was not ready. Fields could have coded it yellow, signaling concern while hedging his exposure. He could have framed the problem as contained, manageable, nearly solved. That is what the old Ford rewarded. Fields [coded his slide red](https://www.marshallgoldsmith.com/post/the-leader-as-the-facilitator?ref=ceo.com). The room went [deathly silent](https://www.conference-board.org/research/human-capital-briefs/blg-00-1-3201?ref=ceo.com). In the culture they all knew, showing red was not transparency. It was a resignation letter. Mulally stood up and [started clapping](https://www.marshallgoldsmith.com/post/the-leader-as-the-facilitator?ref=ceo.com). He thanked Fields for the transparency. He thanked him for the courage. Then, as [Marshall Goldsmith later recounted](https://www.marshallgoldsmith.com/post/the-leader-as-the-facilitator?ref=ceo.com), Mulally told the room: "Mark, you have a red. Above all else, sincere thanks for the transparency. Also, please recognize this: it's OK. Now, just to be clear, I don't have the answer to your problem either. But, good news, we have thousands of very smart people who work here at Ford. Let's get to work and find somebody who can help Mark solve this problem." The quality chief raised his hand. The purchasing chief followed. Within minutes, a problem that had been invisible was being solved by people who, days earlier, had been too busy performing to help each other. The following week, the BPR charts were [full of color](https://www.conference-board.org/research/human-capital-briefs/blg-00-1-3201?ref=ceo.com). Yellows and reds everywhere. The truth, finally, on the walls. ## What Followed The rest of the story is well documented. Mulally [mortgaged every asset Ford owned](https://business.time.com/2012/05/25/how-ford-earned-its-blue-oval-back/?ref=ceo.com), including the Blue Oval logo, to secure $23.5 billion in credit before the financial crisis hit. He sold Jaguar, Land Rover, Aston Martin, and Volvo to refocus on the core brand. He [testified before Congress on behalf of his bankrupt competitors](https://www.factcheck.org/2011/09/ford-motor-co-does-u-turn-on-bailouts/?ref=ceo.com), because Ford shared 80 percent of its supplier network with GM and Chrysler and saving the industry mattered more than winning the news cycle. Ford went from a $17 billion loss to [$8.6 billion in annual profit](https://globalcoachgroup.com/how-alan-mulally-turned-transparency-into-a-turnaround-strategy/?ref=ceo.com). It was the only American automaker that did not take a government bailout. In May 2012, Moody's upgraded its credit rating, and the [Blue Oval came home](https://www.autonews.com/article/20120522/OEM/120529973/ford-s-credit-rating-raised-to-investment-grade-by-moody-s?ref=ceo.com). Bill Ford announced it on the company PA system, which he noted was ["only ever used for fire drills."](https://www.autonews.com/article/20120522/OEM/120529973/ford-s-credit-rating-raised-to-investment-grade-by-moody-s?ref=ceo.com) Mark Fields [succeeded Mulally as CEO in 2014](https://en.wikipedia.org/wiki/Mark%5FFields%5F%28businessman%29?ref=ceo.com). Under his leadership, Ford reported its highest profits and margins in company history and distributed [$9,300 profit-sharing checks](https://en.wikipedia.org/wiki/Mark%5FFields%5F%28businessman%29?ref=ceo.com) to hourly employees. The man who showed red got the job. ## The Lesson The standard reading of this story is that Mulally was a brilliant strategist who made bold financial bets and streamlined a bloated company. That is true but incomplete. The financial turnaround was a result. The transformation was the moment an entire leadership culture stopped performing and started telling the truth. For years, Ford's executives had been doing exactly what the culture rewarded: reading the room, showing green, protecting themselves. Every decision ran through a question that had nothing to do with building better cars: Am I safe? The organization had become a hall of mirrors, every person reflecting what they thought the person above them wanted to see, until nobody in the building was saying what they actually believed. One clap broke the mirror. Fields was the protagonist, not Mulally. Mulally built the system. Fields was the one who had to decide, in real time, with his career on the line, whether to keep performing or start leading. He chose the work over the room. And the leader above him made sure that choice was rewarded instead of punished. That is the whole mechanism. Enacted leadership cannot survive in a culture that punishes it. Performed leadership cannot survive in a culture that stops rewarding it. Mulally did not give a speech about honesty. He built a weekly ritual that made honesty the only viable option, and then, when someone was brave enough to go first, he stood up and clapped. Mulally once told [*Korn Ferry Briefings*](https://www.kornferry.com/insights/briefings-magazine?ref=ceo.com) that when he arrived at Ford, the internal forecast was for a $17 billion loss, "and at the end of the year, we achieved that loss." Ford had always been good at achieving things. Mulally just changed what it aimed at. ### Performing vs. leading URL: https://www.ceo.com/blog/performing-vs-leading/ Last updated: 2026-08-14T00:23:22.000Z Boris Dubretskoi is a nobody. A second lieutenant. But within hours of arriving at military headquarters, he sees something most officers spend entire careers pretending doesn't exist: the real hierarchy has nothing to do with the one printed in the manual. A captain can make a general wait in the hallway. Rank is decoration. Proximity is power. Boris doesn't resist this discovery. He doesn't report it. He leans into it. He decides, right there, to be guided by the invisible system. The one where power actually lives. Tolstoy wrote that scene in *War and Peace*. C.S. Lewis loved it so much he opened one of his [most important essays](https://www.lewissociety.org/innerring/?ref=ceo.com) with it. He gave the invisible system a name: the Inner Ring. And then he made an argument that should unsettle every leader who encounters it. ## The pull The Inner Ring is not a conspiracy. It's a desire. The desire to be inside, to be one of the people who know, to hear someone use the word "we" and feel the warmth of inclusion. Lewis argued it is one of the most powerful forces in human behavior, and it operates most effectively when the person under its influence has no idea they're under its influence at all. The pull never arrives as obvious corruption. It comes over coffee. Between two jokes. From someone you admire, at precisely the moment when you most want their approval. They say "we," and something lights up. You don't cross a line. You just lean toward the warmth. This is how leaders stop leading and start performing. ## The performance The performed leader is oriented toward a Ring. Every decision comes down to a question that has nothing to do with the work: Am I in, or am I out? They learn the right language for the room. They learn which opinions are safe. They signal depth without committing to it. They look like they're making hard calls while deferring to whatever the Ring expects. Here is the part Lewis understood that most leadership thinking misses: the performance never stabilizes. The Ring cannot hold you. "By the very act of admitting you," he wrote, "it has lost its magic." The moment you're in, you're already scanning for the next Ring. The one inside the one you just entered. Performance is a sieve. You pour yourself through it, and nothing accumulates. And the cost doesn't stop with the leader. The team learns to perform back. They start reading the room instead of doing the work. They learn which truths are welcome and which aren't worth the risk. An entire organization can become a hall of mirrors, every person reflecting what they think the person above them wants to see, until no one in the building is saying what they actually believe. ## The fork The distance between performing and leading rarely announces itself. Consider: a CEO hears through a back channel that a board member is quietly building support to replace the CFO with someone from their own network. The CFO is good. Not perfect, but solid and trusted by the team. The board member is influential and connected, and sits at the center of a Ring the CEO has spent years building relationships with. The performed leader takes the meeting. Tests the water. Finds a way to frame the change as strategic rather than political. Tells the CFO it's about "fit" or "the next phase." Everyone in the room knows what actually happened, but the language is clean enough to maintain the fiction. The enacted leader picks up the phone and tells the board member no. That's the fork. It's not complicated. It's just expensive. Lewis warned that each time someone takes the performance fork, the next one comes at a cheaper price. "Next week it will be something a little further from the rules, and next year something further still, but all in the jolliest, friendliest spirit." Nobody becomes a hollow leader all at once. It happens by tiny increments of choosing the Ring over the work, until the work is barely a memory. ## The craftsmen Lewis offered an alternative so simple it's easy to dismiss. Make the work the point. "If in your working hours you make the work your end," he wrote, "you will presently find yourself all unawares inside the only circle in your profession that really matters." You will be among the sound craftsmen. And other sound craftsmen will know it. The sound craftsmen. Not the most visible leaders. Not the most connected. Not the ones collecting keynotes and board seats and magazine profiles. The ones who do the thing the role actually exists to do. The ones whose judgment is trusted not because of their title but because of a long, unglamorous track record of caring about getting it right. The leaders who last have all been inside Rings. Most of them walked out. Some were pushed. All of them, at some point, made the same quiet decision: the work matters more than the room. Lewis said this kind of belonging, the kind that forms around shared craft rather than shared exclusion, is the thing Aristotle called friendship. It causes "perhaps half of all the happiness in the world, and no Inner Ring can ever have it." That is the whole difference between performing leadership and enacting it. One is a sieve. The other is a craft. ### "I've heard from a lot of people" URL: https://www.ceo.com/blog/i-ve-heard-from-a-lot-of-people/ Last updated: 2026-08-14T01:21:04.000Z Five words. That's all it takes to destroy someone's reputation while protecting your own. "I've heard from a lot of people that the organization is struggling; they can't pay their bills." "I've heard from a lot of people that she's difficult to work with." "I've heard from a lot of people that he's not as nice as everyone thinks." No names. No sources. No accountability. Just a grenade tossed into a conversation, and you get to walk away clean. I've been in rooms where this happens. Business dinners, investor meetings, conferences, casual conversations that turn into character assassinations. Someone drops the phrase, everyone nods knowingly, and a person or company takes damage they'll never know about, from an attack they can never defend against. It comes across as cowardice dressed up as insight. ### The unattributed negative Journalists have a term for this: the unattributed negative. It's when an anonymous source makes a derogatory comment about someone's character, reputation, or conduct. Most credible news organizations have strict policies against it. NPR's ethics guidelines are clear: anonymous sources generally cannot make pejorative comments about an individual. The New York Times requires that anonymous sources only be used for information that is newsworthy, credible, and impossible to obtain any other way. Why? Because it's fundamentally unfair. The target has no idea who is attacking them or why. They can't respond. They can't defend themselves. They can't even know it's happening. But there's another reason, one that matters more for our purposes: it destroys credibility. The overuse of anonymous sources has been devastating to journalism. When readers see "according to sources familiar with the matter" or "people close to the situation say," they've learned to be skeptical. They wonder about agendas. They question motives. Trust erodes. The same thing is happening to business leaders who trade in anonymous negativity. They just don't realize it yet. ### Skin in the game Nassim Taleb wrote an [entire book](https://www.amazon.com/Skin-Game-Hidden-Asymmetries-Daily/dp/042528462X?ref=ceo.com) about this principle. His argument is simple: if you're going to make claims, you should bear the consequences of being wrong. Opinions without accountability are worthless. Criticism without exposure is cheap. Taleb reserves his sharpest contempt for those who cause harm without facing consequences. The bureaucrat who makes policy but never lives under it. The pundit who recommends war but never fights in one. The advisor who gives guidance but loses nothing when it fails. Add to that list: the business leader who spreads damaging information about competitors, colleagues, or community members while hiding behind "I've heard." When you say "I've heard from a lot of people," you're claiming the authority of consensus without the vulnerability of attribution. You get to inflict damage without taking any risk. You're placing a bet with someone else's chips. That's not insight. That's not leadership. That's gossip with a business card. ### Who it really hurts Here's what the people who do this don't understand: the person they damage most is themselves. They think they're hurting the target. And maybe they are, in the short term. Deals might fall through. Opportunities might close. Relationships might sour based on whispered warnings and vague concerns. But watch what happens over time. People start to notice patterns. They realize that this person always seems to have negative information about others. They wonder what's being said about them when they're not in the room. They stop sharing. They stop confiding. They stop trusting. Because here's the thing about spreading anonymous negativity: everyone who hears you do it learns something about you. Not about your target. About you. They learn that you'll talk about people behind their backs. They learn that you won't stand behind your words. They learn that relationships with you come with a hidden cost. The person who constantly tears others down starts to look petty. Small. Insecure. Like someone who can only feel tall by making others short. I've watched this play out over years. The people who built reputations on being "connected" and "in the know," who always had the inside scoop on who was struggling and who was failing, eventually find themselves on the outside. Not because anyone confronted them. Just because people quietly stopped including them in anything that mattered. ### What leaders actually do A leader's job is not to tear people down. It's to build them up. Not just the people who can help you. Not just the people who can make your bank account larger. Not just the people who are useful to your ambitions. All people. The competitor who's struggling doesn't need you spreading rumors about their runway. The founder who made the mistake doesn't need you to ensure everyone knows about it. The executive who's going through a hard time doesn't need you turning their difficulties into dinner conversation. If you have genuine concerns about someone's conduct that warrant warning others for their protection, please say it plainly and put your name on it. Stand behind your words. Accept the consequences of being wrong. Have skin in the game. But it's not important enough to say openly, with your name attached, or to say at all. The best leaders I know do something different. When someone's name comes up, they find something good to say. When gossip starts, they redirect or excuse themselves. When they have concerns, they go directly to the person involved. They build. They don't tear down. Here's what's interesting: people trust them more. People confide in them more. People want to work with them more. Because everyone knows that if this person won't tear others down behind their backs, they won't tear you down either. That's That's the kind of reputation that actually matters. ### A simple test Before you share something negative about someone, ask yourself: Would I say this if they were standing right here? Would I put my name on this? Am I willing to be wrong, publicly, if this turns out to be false or unfair? If the answer is no, then don't say it. If the answer is yes, then say it directly, to them, with your name attached: "I've " I've heard from a lot of people" is a sentence for cowards. It's a way to attack without accountability, to damage without risk, to tear down without ever having to build anything yourself. The business world has enough of that already. Be the person who builds. ### The friction economy is over URL: https://www.ceo.com/blog/the-friction-economy-is-over/ Last updated: 2026-08-14T00:29:31.000Z On Monday, the [Dow Jones Industrial Average fell 822 points](https://www.wsj.com/finance/stocks/global-stocks-markets-dow-news-02-23-2026-06a32080?mod=hp%5Flead%5Fpos1&ref=ceo.com). The Wall Street Journal tied the selloff in part to a single piece of writing that had gone viral over the weekend: a fictional macro memo from CitriniResearch, dated June 30, 2028, reconstructing the collapse of what they called the Global Intelligence Crisis. It is a scenario, not a prediction. The authors say so plainly. But the market did not treat it that way, and neither should you. The [piece](https://www.citriniresearch.com/p/2028gic?ref=ceo.com) deserves to be read in full. It is one of the most grounded, financially specific, and unsettling analyses of what AI actually does to an economy. Not in theory. In plumbing. In the real mechanics of how money moves through a system built entirely on the assumption that human intelligence is scarce. That assumption is now in question. And if you are a CEO, the only question worth asking this week is the one buried near the end of that memo: how much of your business model is built on friction, intermediation, or human cognitive tasks that are now exposed? ### **The moat that wasn't** For decades, the most durable competitive advantages in business were not the best products. They were the best friction. Insurance companies earned 15 to 20 percent of their premiums from policyholder inertia. People who simply did not get around to re-shopping their coverage every year. Travel booking platforms built billion-dollar businesses on the idea that assembling a complete itinerary was so tedious that consumers would pay someone else to approximate it. DoorDash's real moat was not logistics. It was because you were hungry and tired, and it was already on your home screen. The CitriniResearch piece calls this "habitual intermediation," and it describes its collapse with precision. AI agents do not have a home screen. They do not get tired. They do not default to the familiar option. They check every platform, every price, every alternative, every time, in milliseconds. The entire consumer subscription economy, built on the behavioral science of inertia, is now negotiating with a counterparty that has no inertia whatsoever. This is not a future risk. It is happening now. The piece notes that, in their scenario, by early 2027, the average American was consuming 400,000 tokens per day from AI systems. Those systems were renegotiating subscriptions, routing around interchange fees, re-shopping insurance, and dismantling every business model whose value proposition was ultimately "navigating complexity you find tedious." The agents found nothing tedious. ### **The ServiceNow lesson every CEO should internalize** The most instructive story in the memo is about ServiceNow. ServiceNow sold workflow automation. It was disrupted by better workflow automation. Its response was to cut headcount and use the savings to invest in the very technology disrupting it. The company that sold seats lost revenue when its customers cut 15 percent of their workforce and cancelled 15 percent of their licenses. The AI-driven headcount reductions that boosted margins for Fortune 500 clients were mechanically destroying ServiceNow's own revenue base. What makes this story important is not the outcome. It is the logic. Every company's individual response was rational. Cut costs, deploy AI, maintain output. The collective result was catastrophic. Every dollar saved on headcount flowed into AI capability that made the next round of cuts possible. The piece describes what happened to incumbents across all sectors: they did not resist because they could not afford to. Boards demanded answers. Stocks were down 40 to 60 percent. The historical disruption model said incumbents die slowly by resisting change. What happened instead was that incumbents accelerated their own disruption by adopting the technology aggressively, thereby validating and funding the very loop that was consuming them. Any CEO running a company today needs to ask whether the revenue model survives the aggressive AI adoption of their own customers. Not whether AI will disrupt the product. Whether the efficiency gains clients extract from AI will mechanically cancel the seats, licenses, or contracts they currently hold. ### **The cognitive task inventory** The piece draws a clear line. Blue-collar employment remained relatively stable through the scenario's initial disruption. White-collar employment collapsed. The jobs that disappeared were the ones that wrote memos, approved budgets, routed decisions, managed workflows, and lubricated the middle layers of the economy. This is not a statement about the relative worth of those workers. It is a statement about what AI can do right now, and what it cannot. Physical presence, dexterity, and in-person judgment remain genuinely hard problems. Cognitive intermediation, the process of taking information, applying learned pattern recognition, and producing a recommendation or deliverable, is increasingly being solved. Every CEO should conduct a cognitive task inventory of their organization. Ask two questions. First, what percentage of our labor costs is paying for human cognitive tasks that an AI agent could perform at a fraction of the price? Second, what percentage of our revenue is being paid to us by customers who are asking the same question about us? The first question reveals where the cost structure is exposed. The second reveals where the revenue is exposed. If the honest answer to either is "a large percentage," then the CitriniResearch scenario is not fiction. It is a roadmap. ### **The intelligence premium is unwinding** The most philosophically significant passage in the memo is near the end. The authors write that throughout modern economic history, human intelligence has been the scarce input. Capital was abundant or at least replicable. Natural resources were finite but substitutable. Technology improved slowly enough that humans could adapt. Intelligence was different. The ability to analyze, decide, create, persuade, and coordinate could not be replicated at scale. Every institution built over the last century, from labor markets to mortgage underwriting to the tax code, was designed for a world where that assumption held. That assumption is now unwinding. This is not doom. The authors are careful about that. The economy will find a new equilibrium. It always does. But the path to that equilibrium will be disorderly, and the businesses that fail to see it coming will not fail slowly, as Kodak or Blockbuster did. They will fail the way ServiceNow did in this scenario: rationally, quickly, and while trying their hardest to survive. The canary is still alive. The [S&P 500](https://finance.yahoo.com/quote/%5EGSPC/?ref=ceo.com) is still near all-time highs relative to any historical baseline. The loop has not started. But a piece of financial scenario writing going viral enough to move the Dow 822 points is itself a data point. The market is signaling that these questions are no longer academic. ### **What personal leadership demands right now** At [CEO.com](http://ceo.com/?ref=ceo.com), the core belief around personal leadership is straightforward: before you can lead an organization, you have to be able to lead yourself. That requires being honest with yourself. To be able to see clearly. Seeing clearly right now means resisting two temptations. The first temptation is dismissal. Calling this speculation, noting that scenarios are not predictions, pointing out that the doom-and-gloom crowd has been wrong before. Some of that is true. But the underlying mechanism is not speculative. AI agents that eliminate friction are not a 2028 hypothesis. They are a 2025 product. The question is not whether they exist. It is how fast they scale. The second temptation is paralysis. The piece is written with enough detail and conviction that it can feel deterministic. It is not. The authors close by noting that there is still time to be proactive. As investors, as executives, as a society. What personal leadership demands is a clear-eyed audit. Not of your AI strategy in the abstract, but of the specific assumptions underlying your business model. Where are you charging a premium for something that is no longer hard for humans but is still hard for machines? Where are your customers paying you to navigate complexity that agents will soon handle for free? Where is your moat made of friction? Answer those questions honestly, and the next step becomes clear. The piece ends with a line worth sitting with: "Getting there is one of the few tasks left that only humans can do. We need to do it correctly." That is still true. For now. ### The trust deficit is bigger than the budget deficit URL: https://www.ceo.com/blog/the-trust-deficit-is-bigger-than-the-budget-deficit/ Last updated: 2026-08-14T00:34:56.000Z The great Murray Rothbard believed all taxation is theft. Not some taxation. Not excessive taxation. All of it. His position was that the state has no legitimate claim to any portion of anyone's income or wealth because the relationship between citizen and government is not voluntary. It is compulsory. You never signed a social contract. You never consented to the arrangement. It was imposed on you at birth and enforced ever since. In Rothbard's ideal, government would play such a limited role in society that you'd rarely think about its existence or who was in charge of it. Taxes would be unnecessary because the institutions they fund would be private. The roads, the courts, the schools. All of it. The state wouldn't need your money because, as we understand it, the state wouldn't exist. It’s a beautiful idea. And we couldn’t be further from its existence. --- We live in a world where the government commands armies, operates prisons, and holds a monopoly on violence. It can seize your property. It can restrict your movement. It can compel you, under threat of imprisonment, to hand over a portion of everything you earn. No private citizen has this power, regardless of how many billions they have accumulated. You can choose not to buy a billionaire's products. You cannot opt out of the government. That is the world as it actually exists. And in that world, with that power structure already in place, the question is not whether taxation should exist. It does. The question is more fundamental. How’s that money being spent? --- There’s a growing, overwhelmingly popular movement to tax the rich. Tax them good; tax them hard. In California, the [2026 Billionaire Tax Act](https://lao.ca.gov/BallotAnalysis/Initiative/2025-024?ref=ceo.com) would impose a one-time 5 percent tax on the net worth of every California resident with $1 billion or more. It would apply retroactively to anyone residing in the state as of January 1, 2026\. It targets roughly [255 people](https://www.cbsnews.com/news/california-billionaire-tax-ballot-initiative-how-it-works/?ref=ceo.com). In Washington, [SB 6346](https://clarknuber.com/articles/wa-state-millionaires-tax-proposed-legislation/?ref=ceo.com) passed the state Senate on February 16, 2026\. It would impose a 9.9 percent tax on individual income above $1 million per year. Washington has no state income tax, so this is not an adjustment. It is a structural transformation. Both proposals poll well, of course. Rich people problems and all that. [Pew Research found](https://www.pewresearch.org/short-reads/2025/03/19/most-americans-continue-to-favor-raising-taxes-on-corporations-higher-income-households/?ref=ceo.com) in early 2025 that 58 percent of Americans believe tax rates on household income over $400,000 should be raised. An [Economist/YouGov poll](https://truthout.org/articles/poll-voters-say-billionaires-pay-too-little-in-taxes-back-action-on-inequality/?ref=ceo.com) found 61 percent think billionaires' tax rates are too low. Even among 2024 Trump voters, a plurality said billionaire taxes are too low. [Eight in ten Americans](https://truthout.org/articles/poll-voters-say-billionaires-pay-too-little-in-taxes-back-action-on-inequality/?ref=ceo.com) view the wealth gap as a problem. In Washington, [54 percent of Republicans](https://senatedemocrats.wa.gov/blog/2026/02/16/millionaires-tax-passes-the-senate/?ref=ceo.com) support taxing millionaires. The argument is powerful; one might call it convincing. If you built a fortune using a state's infrastructure, legal systems, universities, and workforce, you owe something back. [Washington families in the bottom 20 percent](https://governor.wa.gov/news/2025/governor-ferguson-announces-support-millionaires-tax?ref=ceo.com) of income pay 13.8 percent of their total income in state and local taxes. Those in the top 1 percent pay 4.1 percent. The public agrees. The votes are there. The logic is sound. So why are the politicians pushing it so unpopular? Why are they bumping into a single roadblock? Thank you, dear reader, for asking the right question. --- [Fewer than one in five](https://www.pewresearch.org/politics/2025/12/04/public-trust-in-government-1958-2025/?ref=ceo.com) Americans trust the government to do the right thing most of the time. That is among the lowest readings in nearly seven decades of measurement. [Congress's approval](https://news.gallup.com/poll/700241/americans-end-year-gloomy-mood.aspx?ref=ceo.com) hovers around 15-17 percent. [Only 14 percent](https://today.yougov.com/politics/articles/53277-new-second-term-low-donald-trump-job-approval-government-spending?ref=ceo.com) of Americans trust Congress "a great deal" or "quite a bit," making it the least trusted institution among the 15 measured. [Trust in politicians](https://news.gallup.com/poll/697421/trust-government-depends-upon-party-control.aspx?ref=ceo.com) has dropped 23 points since the 1970s. Billionaires are unpopular. [Eighty percent of Americans](https://truthout.org/articles/poll-voters-say-billionaires-pay-too-little-in-taxes-back-action-on-inequality/?ref=ceo.com) say the rich have too much political power. But politicians are far more unpopular. It’s not even close. Oh, and they’re the ones we elected. They work for us. If a CEO had a 15 percent approval rating among shareholders, the board would replace them by morning. Politicians with a 15 percent approval rating propose new taxes. Were I advising those politicians (a scary thought), I would explain, in an overly kind Utahn way, that the tax-the-rich argument cannot work in isolation. The public already agrees with the premise. They do not need to be convinced that billionaires should pay more. What they need to be convinced of is that the money will be properly allocated once it arrives. And the record makes that case almost impossible. --- California has [faced budget deficits for three consecutive years](https://lao.ca.gov/Publications/Report/5091?ref=ceo.com): $27 billion, then $55 billion, then $15 billion. The state now faces an estimated $18 billion shortfall for 2026-27\. Between 2022 and 2024, California [experienced a $175 billion swing](https://www.governing.com/finance/can-california-ever-escape-its-boom-and-bust-budget-woes?ref=ceo.com) from surplus to deficit, driven in part by what officials [acknowledged](https://calmatters.org/commentary/2025/10/california-chronic-deficit-budget/?ref=ceo.com) was a $165 billion error in revenue projections. Not a rounding error. A $165 billion miscalculation. The state's Legislative Analyst now [warns of "chronic" structural deficits](https://calmatters.org/commentary/2026/02/newsom-spending-california-chronic-deficit/?ref=ceo.com) of $20 billion to $35 billion annually for years to come. California already relies on the personal income tax for [nearly 70 percent](https://www.governing.com/finance/can-california-ever-escape-its-boom-and-bust-budget-woes?ref=ceo.com) of its general fund revenue. The national average is 38 percent. The state has papered over its deficits with rainy day fund withdrawals, payment deferrals, internal borrowing, and curious [accounting maneuvers](https://lao.ca.gov/Publications/Report/5079?ref=ceo.com). This state, the golden one, is now asking 200 billionaires for $100 billion to fund healthcare. It cannot balance its own books. Why should its citizens trust them to use this billionaire windfall appropriately and judiciously? At the federal level, the GAO [identified 38 programs](https://usafacts.org/articles/which-government-programs-are-considered-wasteful-or-inefficient/?ref=ceo.com) as highly susceptible to fraud, waste, and mismanagement in its 2025 review. Twenty-eight have been on the list for more than a decade. Five have been there since 1990\. Thirty-five years of identifying the problem. Thirty-five years of not fixing it. The federal government [made $236 billion in improper payments](https://www.gao.gov/blog/federal-government-made-236-billion-improper-payments-last-fiscal-year?ref=ceo.com) in fiscal year 2023 alone. Over 20 years, the total is an estimated $2.7 trillion. If you are a politician asking for more money, this is your resume. This is what you are presenting to the public when you say, "trust us to spend even more tax revenue the right way this time." --- Massachusetts passed a millionaire surtax in 2022, and millionaires didn't flee. The [number of millionaires](https://www.cbsnews.com/news/california-billionaire-tax-ballot-initiative-how-it-works/?ref=ceo.com) in the state rose by 39 percent in the two years that followed. Good. But that is an argument about migration, not stewardship. The question is not whether rich people will leave. The question is whether the money made a difference once it arrived. Did outcomes improve? Were the funds tracked? Almost nobody applies that standard. And that is the problem. A [February 2026 poll](https://www.foxbusiness.com/media/californias-billionaire-tax-disastrous-cause-wealthy-flee-economist-predicts?ref=ceo.com) found that 60 percent of California's likely voters support the billionaire tax. A majority of those same respondents said the measure would spark a business exodus and cost local jobs. People support the tax. They also believe it will backfire. That is not hypocrisy. That is a public that believes in fairness but has given up on competence. --- Rothbard would say none of this matters. He would say the institution collecting the money is illegitimate, regardless of how well it spends. He would say that the monopoly on force is the problem itself, not a reason to demand better performance from those who wield it. Maybe he's right (he is). But we are a long way from that world. In this one, the government exists. It taxes. It spends. It holds power that no private citizen holds. And because it holds that power, because it alone can compel payment under threat of imprisonment, it should be held to a higher standard than those it taxes. Not an equal standard. A higher one. So here is the advice offered to any politician in Sacramento, Olympia, or anywhere else making the case that the wealthy should pay more. The public agrees. The votes are there. You do not have a persuasion problem. You have a credibility problem. Get your house in order. Show the public you can track where the money goes. Stop papering over deficits with one-time fixes. Stop fighting over how to spend revenue that doesn't exist yet. Demonstrate that existing dollars are being spent in ways that justify asking for more. Then come ask for more. ### Satya Nadella and the cultural transformation of Microsoft URL: https://www.ceo.com/blog/satya-nadella-and-the-cultural-transformation-of-microsoft/ Last updated: 2026-08-19T03:07:58.000Z In the summer of 2012, Kurt Eichenwald published an article in *Vanity Fair* titled ["Microsoft's Lost Decade."](https://www.computerworld.com/article/1372393/microsoft-s-downfall-bureacuracy-over-reliance-on-windows-and-poor-hr-managemen.html?ref=ceo.com) Eichenwald had interviewed dozens of current and former Microsoft employees, and his conclusion was blunt: the company that had once defined the technology industry had turned inward, bureaucratic, and culturally toxic. At the center of the dysfunction was a management system called stack ranking, which forced every team to sort its members along a bell curve. A fixed percentage had to be rated top performers. A fixed percentage had to be rated poor. It did not matter how good the team was. Someone had to lose. The consequences were predictable. Employees hoarded information. Collaboration became a liability, because helping a teammate succeed could mean pushing yourself down the curve. A former software developer [told Eichenwald](https://abcnews.go.com/Business/microsoft-abolishes-stack-ranking-employees/story?id=20877556&ref=ceo.com) that the system led employees to focus on competing with each other rather than competing with other companies. Another described giving "the appearance of being courteous while withholding just enough information from colleagues" to protect his own ranking. Top engineers avoided joining teams with other top engineers, because the math of the bell curve meant that the better your colleagues were, the more likely you were to be ranked as average or below. The system created a culture of fear. Not the productive kind. The kind that makes people small. By 2012, Microsoft's stock price had been essentially flat for a decade. The company had missed mobile. It was late to cloud computing. It had the talent and the resources to compete in every major technology shift of the 2000s, and it lost ground in nearly all of them. Not because the engineers weren't capable. Because the culture made it irrational to take risks, to collaborate, to do the kind of work that produces breakthroughs. Microsoft's market capitalization when Eichenwald's article was published: roughly $257 billion. --- On February 4, 2014, [Satya Nadella sent his first email as CEO to every employee at Microsoft.](https://news.microsoft.com/source/2014/02/04/satya-nadella-email-to-employees-on-first-day-as-ceo/?ref=ceo.com) He was the company's third chief executive, following Bill Gates and Steve Ballmer. He had been at Microsoft for 22 years. He was not an outsider. He knew exactly what was broken. The email contained a line that would define his tenure: "Our industry does not respect tradition. It only respects innovation." But what Nadella did first was not a technology play. It was a people play. The stack ranking system had technically been [eliminated in November 2013](https://abcnews.go.com/Business/microsoft-abolishes-stack-ranking-employees/story?id=20877556&ref=ceo.com), shortly before Ballmer's departure, after the *Vanity Fair* piece had made the practice indefensible in public. But killing the system was not the same as killing what the system had created. A decade of forced ranking had produced a culture where self-protection was the default behavior, where showing vulnerability was dangerous, and where the phrase "not invented here" was the unofficial company policy. Nadella understood that changing the org chart or the performance review form would not be enough. He had to change how people felt about coming to work. --- The framework he chose came from an unlikely source. In early 2015, Nadella's wife Anu gave him a book by Stanford psychologist [Carol Dweck](https://news.microsoft.com/hitrefresh/?ref=ceo.com) called *Mindset: The New Psychology of Success*. Dweck's research distinguished between what she called a fixed mindset, the belief that abilities are innate and static, and a growth mindset, the belief that abilities can be developed through effort and learning. People with fixed mindsets avoid challenges because failure threatens their identity. People with growth mindsets seek challenges because failure is information. Nadella [made the book required reading](https://www.15minutebusinessbooks.com/blog/2022/06/01/satya-nadella-had-his-top-lieutenants-read-mindset-by-carol-dweck-and-then-he-did-this/?ref=ceo.com) for his senior leadership team. For the broader organization, he distilled the idea into a phrase designed to travel: Microsoft would shift from being a company of "know-it-alls" to a company of ["learn-it-alls."](https://www.gsb.stanford.edu/insights/microsoft-ceo-satya-nadella-be-bold-be-right?ref=ceo.com) Six words. But the behavioral implications were enormous. Under the old culture, admitting you didn't know something was weakness. Under the new one, it was the expectation. Under the old culture, asking for help meant you couldn't handle your job. Under the new one, leveraging other people's work was [an explicit criterion in your performance review](https://www.deel.com/blog/employee-performance-reviews-at-microsoft/?ref=ceo.com). Under the old culture, failure was career-threatening. Under the new one, it was supposed to be a data point. Nadella didn't just announce this. He modeled it. He [changed how the senior leadership team meetings ran](https://brighterstrategies.com/work-relationships/what-microsofts-transformation-teaches-us-about-network-leadership/?ref=ceo.com). Previously, these sessions were described by participants as gladiatorial combat, where executives competed to demonstrate they had the best numbers and the sharpest insights. Nadella turned them into collaborative sessions where leaders were expected to share what they had learned, not what they had accomplished. He asked questions instead of giving answers. He made vulnerability safe at the top of the organization, because he knew it would never be safe at the bottom if it wasn't safe at the top. The new performance system reflected this philosophy. Microsoft replaced stack ranking with a framework built around three dimensions: your individual impact, [how you contributed to others' success, and how you leveraged the work of others](https://www.deel.com/blog/employee-performance-reviews-at-microsoft/?ref=ceo.com). Two of the three criteria were explicitly about collaboration. The message was structural, not just rhetorical: you could no longer succeed at Microsoft by hoarding. --- The cultural work was not a parallel initiative to the technology strategy. It was the prerequisite for it. When Nadella took over, Microsoft's future depended on a massive pivot to cloud computing. Azure existed but was not yet a serious competitor to Amazon Web Services. The pivot required something that the old Microsoft was incapable of producing: cross-team collaboration at scale, willingness to cannibalize existing products, comfort with releasing imperfect software and iterating, and openness to building for platforms Microsoft did not control, including Linux, iOS, and Android. None of that was possible in a culture where teams were at war with each other and where admitting your product was imperfect was a career risk. One of Nadella's first major product decisions made this concrete. He [launched Microsoft Office on Apple's iPad](https://sapumalperera.medium.com/from-struggler-to-3-trillion-giant-how-microsofts-customer-driven-strategy-redefined-success-869592de4794?ref=ceo.com), a move that would have been unthinkable under Ballmer, who had insisted that everything revolve around Windows. The decision signaled something beyond product strategy. It told employees that the old sacred cows were gone. That the company would go where customers were, even if it meant abandoning positions that previous leadership had treated as non-negotiable. Azure grew. Microsoft Teams was built through the kind of cross-divisional collaboration that stack ranking had made impossible. The company acquired [LinkedIn, GitHub, Nuance, and Activision Blizzard](https://dailyfornex.com/satya-nadella-notable-achievements/?ref=ceo.com), each acquisition requiring the cultural capacity to integrate outside talent and ideas rather than rejecting them. When the OpenAI partnership emerged, Microsoft was positioned to act on it because the organization had spent years building the internal trust and cross-functional agility that a bet of that magnitude requires. The numbers tell the story. Microsoft's market capitalization when Nadella became CEO in February 2014: [approximately $300 billion](https://dailyfornex.com/satya-nadella-notable-achievements/?ref=ceo.com). By late 2024, it had [exceeded $3 trillion](https://sapumalperera.medium.com/from-struggler-to-3-trillion-giant-how-microsofts-customer-driven-strategy-redefined-success-869592de4794?ref=ceo.com). A tenfold increase. The largest value creation by a single CEO in corporate history. --- The conventional reading of this story is that Nadella was a brilliant technology strategist who made the right bets on cloud and AI. That is true. But it misses the causal chain. Nadella could not have made those bets work without first building a culture that could execute them. The strategy required collaboration. Collaboration required trust. Trust required dismantling a system that had made fear the organizing principle of the company for over a decade. The people strategy came first. The technology strategy was built on top of it. The market cap was a consequence of both. This distinction matters because it is precisely the distinction most companies are getting wrong right now. --- Microsoft stock is [down roughly 25% from its 52-week high](https://www.fool.com/investing/2026/02/09/down-25-from-its-high-is-now-the-time-to-buy-micro/?ref=ceo.com). In late January, the company lost [$357 billion in market value in a single day](https://www.fool.com/investing/2026/02/02/shares-down-10-earnings-call-microsoft-stock/?ref=ceo.com) after an earnings report that showed strong revenue growth but massive AI infrastructure spending that spooked investors. The broader [$2 trillion software selloff](https://fortune.com/2026/02/10/stocks-2-trillion-software-wipeout-ai-bull-market/?ref=ceo.com) has hit Microsoft along with the rest of the sector. The question is whether the culture Nadella built is resilient enough to navigate another period of massive uncertainty. The early evidence suggests it is, and for a specific reason: Microsoft has been through a version of this before. In 2014, the company faced an existential question about whether it could survive the shift from desktop software to cloud computing. The pivot required employees to accept that the work they had been doing might become less important, that the skills they had built might need to change, that the company they had joined was going to become a fundamentally different organization. Nadella's cultural work gave people a framework for processing that uncertainty without checking out or leaving. The growth mindset framework is not just corporate philosophy. It is infrastructure. It gives employees a language for talking about change that does not reduce them to cost lines. It makes learning and adaptation the expected response to disruption, not a threat to identity. It creates space for the question that every employee is asking right now, "Am I going to be replaced?", to be asked out loud, examined honestly, and addressed as a shared challenge rather than a private fear. Whether that infrastructure holds through the current AI transition is not guaranteed. But the contrast with companies that have no such infrastructure is stark. Microsoft employees have a decade of cultural evidence that their leadership sees them as people to be developed, not expenses to be optimized. That evidence is the kind of thing that keeps top performers from leaving when the market gets turbulent. It is the kind of thing that keeps people engaged when the ground is shifting under them. It is the kind of thing that makes the difference between an AI transformation that works and one that produces the illusion of efficiency while the actual quality of work quietly degrades. --- The lesson of the Nadella case is not that culture is more important than technology. It is that they are the same thing. You cannot execute a technology strategy without the people who will build it, maintain it, improve it, and catch it when it is wrong. And you cannot retain those people, much less earn their best work, if they are afraid. In Chekhov's story, Tchervyakov dies because no one in a position of authority engages with his fear honestly. The general dismisses him. Forget about it. It's nothing. Nadella did the opposite. He looked at a company full of people who were afraid of each other, afraid of their own performance reviews, afraid to collaborate and afraid to fail, and he named it. He said: this is what we are, and this is what we need to become. He didn't promise that the transition would be painless. He didn't guarantee anyone's job. He changed the conditions that had made fear the rational response. That is the work. It was the work in 2014, and it is the work right now. ### Am I Going to Be Replaced? URL: https://www.ceo.com/blog/am-i-going-to-be-replaced/ Last updated: 2026-08-14T00:39:21.000Z A minor bureaucrat named Tchervyakov is sitting in a theater when he accidentally sneezes on the back of a general's bald head. The general says it's fine. Don't worry about it. Tchervyakov apologizes. The general says forget it. But Tchervyakov cannot forget it. He goes home and tells his wife. The next day he shows up at the general's office to apologize again. The general waves him off. Tchervyakov comes back the following day. And the day after that. Each visit makes things worse. Each apology creates exactly the hostility he feared in the first place. Finally, the general, now genuinely furious, screams at him to get out. Tchervyakov walks home, lies down on his sofa in his uniform, and dies. That is the entire plot of Anton Chekhov's ["The Death of a Government Clerk."](https://www.livrosgratis.com.br/ler-livro-online-146860/the-death-of-a-government-clerk?ref=ceo.com) Two pages. A sneeze, a series of apologies, and a death. The story is absurd. It is also, if you lead people for a living, a useful read. What kills Tchervyakov is not the sneeze. It is not the general's anger, which only appears at the very end, manufactured entirely by Tchervyakov's relentless pursuit of forgiveness. What kills him is the gap between what is actually happening and what he believes is happening. The general says "never mind," and Tchervyakov sees a fiendish light in his eye. The general says, "I've forgotten it," and Tchervyakov reads it as barely concealed rage. He cannot receive reassurance because his fear is not about the sneeze. His fear is about his position in the world. He is a small man in a system that could crush him at any moment, and that knowledge has so thoroughly colonized his perception that he can no longer distinguish between reality and the story his anxiety is telling him. There is a version of this happening right now inside almost every company in the country. --- The $2 trillion software selloff made something concrete that had been abstract. J.P. Morgan called it the [largest non-recessionary drawdown](https://fortune.com/2026/02/10/stocks-2-trillion-software-wipeout-ai-bull-market/?ref=ceo.com) in software stocks in over 30 years. When markets began repricing entire companies built on software as potentially obsolete, the question stopped being theoretical. If the company itself might be worth dramatically less because of AI, what does that mean for the people inside it? For the engineer who spent a decade mastering a stack that a model can now approximate in seconds? For the marketing director whose team just got cut in half because a founder somewhere read a blog post about doing more with less? For the mid-level manager who has been hearing the word "efficiency" in every all-hands meeting for six months and knows, with the bone-deep certainty of someone who has survived previous rounds of corporate euphemism, that efficiency is what leaders say before they say layoffs? Every employee in your company has a question they are not asking out loud. Am I going to be replaced? Not by a competitor. Not by a restructuring. By a machine. They are not asking because they are afraid the answer is yes. They are also not asking because the culture has made it clear that this question is not welcome. You are supposed to be excited about AI. You are supposed to see it as a tool that will make you better at your job, not a tool that will make your job unnecessary. You are supposed to be an early adopter, a forward thinker, someone who embraces change. The anxiety you feel is a personal failing, a lack of vision, a resistance to the future. This is how organizations create Tchervyakovs. --- There is a pattern that keeps repeating in companies moving fast on AI adoption. Leadership announces a major initiative. The framing is relentlessly positive. Productivity. Efficiency. Competitive advantage. The technology is presented as purely additive. Everyone will be able to do more. Nobody talks about what "more" means when the headcount stays flat or shrinks. Nobody talks about what happens when a tool that lets one person do the work of three creates an obvious question about the other two. What happens next is predictable and invisible. The top performers leave first. This sounds counterintuitive. The best people should be the least threatened. But the best people are also the most mobile. They have options. When they sense that the ground is shifting under them, when they hear the language of optimization applied to human beings, when the all-hands meeting features a slide about "leveraging AI to do more with less," and nobody in leadership seems to notice that "less" means people, the best performers start taking calls from recruiters. They don't leave because they can't adapt. They leave because they don't trust the people in charge to value them through the transition. The people who stay begin to disengage. Not dramatically. Not in ways that show up immediately on a dashboard. They stop volunteering for new projects. They stop sharing ideas in meetings. They do their work competently and quietly and they stop doing the unseen work, the discretionary effort, the going above and beyond, the caring, that actually makes organizations function. Their bodies are at their desks, but their commitment has quietly migrated somewhere safe, somewhere that cannot be optimized away. The AI implementation then fails or underperforms. Because here is the thing that almost no one building the business case for AI wants to acknowledge: these systems depend on human beings. They depend on people who understand the work well enough to train the models, to check the outputs, to know when the machine is confidently wrong. They depend on institutional knowledge, on judgment, on the ten thousand small decisions that experienced people make every day without thinking. When those people check out emotionally, the AI does not magically fill the gap. It produces outputs that look right but aren't. It automates processes that needed human judgment at exactly the points where judgment was removed. It creates the illusion of efficiency while the actual quality of work quietly degrades. And leadership, having committed to the narrative, having built their board presentations around it, having tied their own compensation to the transformation, doubles down. The problem must be the technology. Or the implementation partner. Or the change management process. It is almost never recognized for what it actually is: a human problem created by the failure to treat it as such. --- None of this is an argument against speed. The technology is transformative. The companies that figure out how to use these tools well will outperform those that don't by enormous margins. Timidity is not the answer. But the technology question and the people question are the same question. You cannot answer one without answering the other. Right now, almost every leadership team is treating them as separate problems. The technology question gets the strategy decks, budget, and executive attention. The people question gets a vague reference to "change management" and maybe a lunch-and-learn about prompt engineering. Recall Tchervyakov. His tragedy is not just that he is afraid. It is that no one in a position of authority engages honestly with his fear. The general dismisses him. Forget about it. It's nothing. This is what most leaders do when employees express anxiety about AI. They wave it off. Your job is safe. AI is a tool, not a replacement. These reassurances are meant to be kind, but they function the same way the general's dismissals do in Chekhov's story. They tell the person that their perception of reality is wrong without ever addressing the conditions that gave rise to it. Tchervyakov is not afraid because he misread a social situation. He is afraid because he lives in a system in which his entire existence depends on the goodwill of those above him, where he has no real power, no real security, no real agency. His fear is rational even if his response to it is not. Telling him not to worry does not change the structure that produced the worry. It just tells him that his worry is not welcome. Your employees' fear of AI is also rational. They are watching the world change in real time. They are reading the same headlines you are. They see the layoffs framed as AI-driven efficiency. They hear the venture capitalists talking about how AI will let startups do the work of a hundred people with a team of ten. They know that "doing more with less" has a subject and an object, and they are pretty sure they are the object. Telling them not to worry is not reassurance. It is a signal that you either don't understand what they are going through or you don't want to talk about it. Either way, it breaks trust. --- What people need in a moment like this is not a guarantee that their jobs are safe. That guarantee would be a lie, and they are smart enough to know it. They need the truth. Not the catastrophic truth of "we're all going to be replaced." The real truth, which is harder: AI is going to change the nature of work in your company significantly; you don't know exactly how yet, and you are thinking about it seriously. Some roles will change. Some may be eliminated. New roles will be created. The specific shape of all this is still forming. They need transparency about how decisions will be made. When a leader says "we're investing in AI," what an employee hears is "we're investing in something that might replace me." The antidote is not reassurance. It is specificity. How will the company evaluate which roles are augmented by AI and which are displaced? What is the timeline? What does the company owe people whose roles are affected? Is the retraining real, with real resources behind it, or is it a token gesture designed to make the press release look better? Most importantly, they need leaders who stop treating them as a cost line item. The language of efficiency and optimization is the language of spreadsheets, and it is poison when applied to human beings. Every time a leader describes AI in terms of headcount reduction, doing more with less, or cost savings, they are telling their workforce exactly where they stand in the organization's hierarchy of values. They are telling them they are an expense to be minimized, not a capability to be developed. People hear this with extraordinary precision. They hear the thing you didn't say even louder than the thing you did. --- Chekhov's story ends with Tchervyakov dying on his sofa. Still in his uniform. That detail makes the story. He dies as the clerk. Not as a man. Not as a husband. Not as a human being with a life outside the hierarchy that consumed him. He dies in the costume of his function, because by the end, his function is all that's left. The fear ate everything else. Your people are not Tchervyakovs. Not yet. But they are sitting in the theater right now, watching you, trying to read the expression on your face, trying to determine whether the thing you said is what you meant, trying to figure out if the reassurance was real or if there was a fiendish light in your eye. What they see will determine everything that happens next. Not the technology. Not the implementation roadmap. Not the vendor you selected or the models you deployed. What your people see when they look at you. ### Disney and the "Don't Say Gay" bill URL: https://www.ceo.com/blog/disney-and-the-don-t-say-gay-bill/ Last updated: 2026-08-19T03:05:28.000Z On February 25, 2020, Bob Iger stepped down as CEO of the Walt Disney Company after fifteen years at the helm. His handpicked successor, Bob Chapek, assumed office immediately. Chapek had spent decades inside Disney, most recently running its theme parks and consumer products division. He was an operations executive inheriting a creative empire. The timing was terrible. Within weeks, a pandemic shut down Disney's theme parks, cruise ships, and film productions. Chapek spent his first two years managing crisis after crisis. By most financial measures, he did it well. Disney's fiscal first-quarter results in early 2022 [blew past analyst expectations](https://fortune.com/2022/03/21/disney-bob-chapek-bo-iger-ceo-feud-dont-say-gay-bill/?ref=ceo.com) on earnings per share, revenue, and Disney+ subscribers. But the crisis that would define and ultimately end Chapek's tenure had nothing to do with a balance sheet. --- ### The Bill In January 2022, Florida's legislature introduced the Parental Rights in Education Act, which opponents would come to call the ["Don't Say Gay" bill](https://en.wikipedia.org/wiki/Disney%5Fand%5FFlorida's%5FParental%5FRights%5Fin%5FEducation%5FAct?ref=ceo.com). The bill prohibited classroom instruction on sexual orientation or gender identity from kindergarten through third grade and restricted it in higher grades to what was deemed "age-appropriate." Critics argued the language was vague enough to extend the ban to all grade levels and would silence LGBTQ+ students and families. Florida is home to Walt Disney World, one of the company's most important properties. Disney employs over 75,000 workers in the state. It is among Florida's largest private employers. The [Orlando Sentinel reported](https://en.wikipedia.org/wiki/Disney%5Fand%5FFlorida's%5FParental%5FRights%5Fin%5FEducation%5FAct?ref=ceo.com) that Disney had donated money to every one of the bill's sponsors and co-sponsors, totaling roughly $200,000. Pressure was building. AIDS Healthcare Foundation launched a [TV ad campaign in Orlando](https://www.queerency.com/a-timeline-of-disneys-response-to-floridas-dont-say-gay-bill/?ref=ceo.com) urging Disney to speak out. LGBTQ+ employees began posting public statements and videos expressing frustration. The Hollywood Reporter published a piece citing insiders who said Chapek ["is less willing than predecessor Bob Iger to take public political stands."](https://www.hollywoodreporter.com/business/business-news/disney-florida-dont-say-gay-bill-1235103165/?ref=ceo.com) Meanwhile, Iger himself had already weighed in. On February 25, 2022, he [tweeted](https://fortune.com/2022/03/21/disney-bob-chapek-bo-iger-ceo-feud-dont-say-gay-bill/?ref=ceo.com): "I'm with the President on this! If passed, this bill will put vulnerable, young LGBTQ people in jeopardy." Disney heiress Abigail Disney piled on days later. ["When laws are being passed that are this hateful and dripping with prejudice, there is no neutrality,"](https://deadline.com/2022/03/disney-dont-say-gay-bill-florida-bob-chapek-lgbtq-ron-desantis-1234972655/?ref=ceo.com) she tweeted on March 3\. "Not saying anything is saying a lot." The current CEO's predecessor and his own family's descendants had taken public positions before the current CEO had said a word. --- ### The First Position: Silence On March 7, Chapek released an internal memo. Disney would not take a public stance on the bill. Corporate statements, he wrote, ["do very little to change outcomes or minds."](https://deadline.com/2022/03/disney-dont-say-gay-bill-florida-bob-chapek-lgbtq-ron-desantis-1234972655/?ref=ceo.com) Instead, they are "weaponized by one side or the other to further divide and inflame." He pointed to Disney's content as the real expression of its values, citing films like *Encanto*, *Black Panther*, and shows like *Modern Family* and *Pose*. "These and all of our diverse stories are our corporate statements," Chapek wrote, "and they are more powerful than any tweet or lobbying effort." Employees organized. A site called [WhereIsChapek.com](http://whereischapek.com/?ref=ceo.com) collected anonymous testimonials from Disney workers expressing disapproval. Pixar employees alleged in a public statement that Disney had been [actively censoring same-sex scenes](https://www.fatherly.com/news/disney-employees-wont-back-down-to-dont-say-gay-bs?ref=ceo.com) in their films. "Nearly every moment of overtly gay affection is cut at Disney's behest," the group wrote. Several longtime Disney employees told [Deadline](https://deadline.com/2022/03/disney-dont-say-gay-walk-out-lgbtq-staff-bob-chapek-florida-1234979311/?ref=ceo.com) it was "the worst week they've ever had working at the company." --- ### The Reversal Two days later, on March 9, at Disney's annual shareholder meeting, Chapek changed course. He told shareholders he had [called Florida Governor Ron DeSantis](https://www.cnn.com/2022/03/09/media/dont-say-gay-bill-disney-chapek-desantis/index.html?ref=ceo.com) that morning to express the company's "disappointment and concern." He acknowledged that Disney's behind-the-scenes approach had failed. "I understand our original approach, no matter how well intended, didn't quite get the job done," he said. By March 11, in another company-wide letter, Chapek went further. ["You needed me to be a stronger ally in the fight for equal rights and I let you down,"](https://deadline.com/2022/03/disney-dont-say-gay-response-sorry-bob-chapek-ron-desantis-1234976280/?ref=ceo.com) he wrote. "I am sorry." Disney pledged $5 million to organizations working to protect LGBTQ+ rights and signed the Human Rights Campaign's statement opposing the legislation. The Human Rights Campaign [refused the donation](https://www.npr.org/2022/03/08/1085130633/disney-response-florida-bill-dont-say-gay?ref=ceo.com), saying it wouldn't accept Disney's money "until we see them build on their public commitment." On March 22, Disney employees [staged a full-day walkout](https://www.fatherly.com/news/disney-employees-wont-back-down-to-dont-say-gay-bs?ref=ceo.com) at properties in Florida and California, including subsidiaries like Marvel, Pixar, and Lucasfilm. DeSantis signed the bill into law on March 28. --- ### The Retaliation According to DeSantis's own account in his book, published the following year, Chapek had called the governor as pressure mounted. "We get pressured all the time," Chapek told him. ["But this time is different. I haven't seen anything like this before."](https://www.cnbc.com/2023/02/27/disney-ex-ceo-chapek-called-desantis-over-dont-say-gay-book.html?ref=ceo.com) DeSantis says he replied: "Do not get involved with this legislation. You will end up putting yourself in an untenable position." He warned Chapek that critics would ask why Disney had never spoken out about China, where the company generates significant revenue. Chapek got involved anyway. Or, more precisely, his employees forced him to. Within weeks, DeSantis [called a special legislative session](https://commercialobserver.com/2022/04/desantis-ends-disneys-special-status-in-reedy-creek/?ref=ceo.com). In 72 hours, the Florida legislature introduced, passed, and sent to the governor's desk a bill stripping Disney of its self-governing status through the [Reedy Creek Improvement District](https://www.factcheck.org/2022/05/desantis-vs-disney-qa/?ref=ceo.com), a special tax district that had allowed Disney to manage its own zoning, sewage, transportation, and security on 25,000 acres since 1967. DeSantis signed it. "You're a corporation based in Burbank, California," he [said](https://www.factcheck.org/2022/05/desantis-vs-disney-qa/?ref=ceo.com), "and you're going to marshal your economic might to attack the parents of my state? We view that as a provocation, and we're going to fight back against that." The district was renamed the [Central Florida Tourism Oversight District](https://www.cnn.com/2023/02/27/politics/desantis-disney-reedy-creek/index.html?ref=ceo.com). DeSantis appointed a new five-member board to replace Disney's hand-picked supervisors, stacking it with conservative allies and campaign donors. "Today, the corporate kingdom finally comes to an end," [DeSantis said](https://www.cnn.com/2023/02/27/politics/desantis-disney-reedy-creek/index.html?ref=ceo.com) at the signing ceremony, held at a fire station inside the district itself. "There's a new sheriff in town." The move carried real consequences. Reedy Creek held an estimated [$1 billion in outstanding bond debt](https://commercialobserver.com/2022/04/desantis-ends-disneys-special-status-in-reedy-creek/?ref=ceo.com). The district operated at a loss of $5 to $10 million annually, which Disney had absorbed internally. Local taxpayers in Orange and Osceola counties suddenly faced the prospect of inheriting those obligations. Residents [sued DeSantis](https://www.hollywoodreporter.com/business/business-news/florida-taxpayers-sue-gov-ron-desantis-for-eliminating-disneys-special-district-1235140609/?ref=ceo.com) in federal court, arguing the law violated Disney's First Amendment rights and would burden taxpayers. Some of DeSantis's own party balked. Former Vice President Mike Pence [said](https://www.cnn.com/2023/02/27/politics/desantis-disney-reedy-creek/index.html?ref=ceo.com) the conflict was "beyond the scope of what I as a conservative, limited government Republican would be prepared to do." New Hampshire Governor Chris Sununu called it "the worst precedent in the world." --- ### The Firing On November 20, 2022, Disney's board fired Bob Chapek. [Bob Iger came out of retirement](https://www.hollywoodreporter.com/business/business-news/disney-bob-iger-returning-ceo-bob-chapek-exits-1235266823/?ref=ceo.com) to replace him. The "Don't Say Gay" episode was not the sole reason for Chapek's firing. Disney's stock had dropped 40% that year. The company's streaming division had posted [$1.5 billion in quarterly losses](https://fortune.com/2022/11/21/bob-chapek-disney-ceo-bob-iger-tenure-replacement/?ref=ceo.com). Chapek had mishandled a public dispute with Scarlett Johansson over *Black Widow* compensation. His relationship with Iger had deteriorated badly, with Iger privately telling associates, as the New York Times reported, that [Disney "seemed to be losing its soul."](https://www.cnbc.com/2023/09/06/disney-succession-mess-iger-chapek.html?ref=ceo.com) But the "Don't Say Gay" crisis crystallized the broader critique: Chapek lacked the political instincts, creative relationships, and communication skills that the role demanded. He had tried silence. He had tried reversal. Both positions cost him. Within days of returning, [Iger fired Chapek's closest advisors](https://www.cnbc.com/2023/09/06/disney-succession-mess-iger-chapek.html?ref=ceo.com), including his former chief of staff, his assistant, and his de facto second-in-command. --- ### The Aftermath In April 2023, Disney [sued DeSantis in federal court](https://www.nbcnews.com/business/business-news/disney-sues-ron-desantis-over-reedy-creek-control-rcna81587?ref=ceo.com), alleging a "targeted campaign of government retaliation" that violated the company's First Amendment rights. The DeSantis-appointed board countersued. The legal battle stretched for over a year. In March 2024, with DeSantis's presidential bid behind him, [both sides settled](https://www.cnn.com/2024/03/27/business/desantis-disney-fight-reaches-settlement?ref=ceo.com). Disney agreed to drop its lawsuits and accept that the development agreements it had rushed through before the state takeover were null and void. In return, the two sides would negotiate a new development agreement. Neither party admitted fault. By June 2024, Disney [dropped its federal appeal entirely](https://variety.com/2024/biz/news/disney-drops-appeal-desantis-florida-1236036533/?ref=ceo.com) after a new 15-year development agreement was approved, allowing Disney to invest up to $17 billion in expanding its Orlando parks. The fight was over. But the ruling that dismissed Disney's First Amendment claim still stands. The court found that Florida had the power to revoke the district, and that its motives for doing so were irrelevant. --- ### What This Case Reveals Bob Chapek faced a version of the problem that confronts every CEO who leads a large workforce during a period of cultural and political tension. The question is not whether leaders should take positions on social issues. The question is whether they can avoid it. Chapek tried. His initial instinct was the same as Brian Armstrong's at Coinbase and Jason Fried's at Basecamp: stay out of it. Let the work speak. Avoid the trap of making corporate statements that get "weaponized." The logic is defensible. But it assumes two things that turned out to be wrong. First, that a CEO's silence will be read as neutral. Abigail Disney called it immediately: "Not saying anything is saying a lot." Second, that the internal culture of a company can be separated from external political events. Chapek's employees didn't experience the bill as an abstract policy debate. They experienced it as a threat to colleagues and their families. For LGBTQ+ employees at Disney's Florida properties, this wasn't a "societal issue." It was their commute, their children's schools, their daily reality. But Chapek's reversal proved equally costly. Once Disney publicly opposed the bill, DeSantis treated it as an act of political aggression and responded with the full force of the state. A 55-year-old governing arrangement was demolished in 72 hours. A billion dollars in bond obligations were put at risk. A company that had been one of the state's most important economic engines found itself in a legal fight with the state itself. The case is sometimes framed as evidence that CEOs should stay out of politics. But the evidence points in the opposite direction: Chapek tried both positions, and both failed. His silence emboldened critics internally and let Iger claim the moral high ground publicly. His reversal was read as weakness rather than courage, since it came only after sustained pressure rather than from conviction. And the reversal triggered political retaliation that silence might have avoided. DeSantis himself described the trap perfectly when he warned Chapek: "You will end up putting yourself in an untenable position." The word was untenable. Not "wrong." The position was untenable regardless of which direction it faced. This is the [fragility](https://www.amazon.com/Antifragile-Things-That-Disorder-Incerto/dp/0812979680?ref=ceo.com) that Nassim Taleb describes: a system structured so that the leader absorbs all the risk. Speak up, and you alienate one constituency. Stay silent, and you alienate another. Either way, something breaks. The question is not whether to take a position. The question is whether you understand which breaks you can survive. Chapek didn't survive either one. ### Whose politics count? URL: https://www.ceo.com/blog/whose-politics-count/ Last updated: 2026-08-14T00:44:30.000Z In 1978, a Czech playwright named Václav Havel sat in his summer home outside Prague and wrote an essay while police watched his house from an observation tower across the road. They followed him to the store. They followed him while he walked his dog. They stopped and fined anyone who tried to visit him. The essay was titled [*The Power of the Powerless*](https://www.nonviolent-conflict.org/resource/the-power-of-the-powerless/?ref=ceo.com). It was smuggled out by hand, copied on typewriters, and passed from person to person across Eastern Europe. It became one of the most important political documents of the twentieth century. A decade later, the regimes it described collapsed, and Havel became president. The essay opens with a greengrocer. Every morning, this man places a sign in his shop window: "Workers of the world, unite!" He doesn't believe it. He doesn't think about it. He puts it up the same way he arranges his onions, as part of the ordinary routine of getting through the day without being noticed. The sign is the price of being left alone. Havel's insight is that the greengrocer's compliance isn't neutral. By hanging the sign, he helps sustain a system he privately disagrees with. And the moment he takes it down, the moment he stops performing a belief he doesn't hold, he becomes a threat. Not because he's done anything radical. Because he's stopped participating in a fiction. Havel wrote this about totalitarian Czechoslovakia. But the underlying observation extends beyond any single political system. Participation is never neutral. Silence is never empty. Every public act, including the act of saying nothing, is read by the people watching. --- In September 2020, Coinbase CEO Brian Armstrong published [a blog post](https://www.coinbase.com/blog/coinbase-is-a-mission-focused-company?ref=ceo.com). The company would be "mission-focused," he wrote. It would not engage in broader social activism unrelated to its crypto mission. It would not take public positions on societal issues. Employees were discouraged from debating political causes internally. He framed it as protecting focus. Those who couldn't accept the new direction were offered [severance packages to leave](https://www.cnbc.com/2020/09/30/coinbase-ceo-offers-severance-to-employees-leaving-over-politics.html?ref=ceo.com). About 60 people took them. Twitter co-founder Jack Dorsey [responded the same day](https://twitter.com/jack/status/1311423420274372608?ref=ceo.com). "Bitcoin is direct activism against an unverifiable and exclusionary financial system which negatively affects so much of our society," he tweeted. "This leaves people behind." Translation: You can't build a company on disruption and then tell your employees disruption is a distraction. The backstory is the story. Armstrong's policy came after black employees spoke at an all-hands meeting about their pain following the murder of George Floyd. It came after employees [staged a walkout](https://thehill.com/policy/technology/519133-cryptocurrency-company-coinbase-defends-rule/?ref=ceo.com) because Armstrong initially refused to voice support for Black Lives Matter. He eventually [tweeted his support](https://www.cnbc.com/2020/09/30/coinbase-ceo-offers-severance-to-employees-leaving-over-politics.html?ref=ceo.com). Then, weeks later, he announced the policy. Many within the company didn't see it as an abstract philosophical position. They saw a response. John Russ, the highest-ranking black executive at Coinbase, was among those who left. Seven months later, Basecamp CEO Jason Fried made a similar move. ["Societal and political discussions"](https://techcrunch.com/2021/04/30/basecamp-employees-quit-ceo-letter/?ref=ceo.com) would no longer be permitted on the company's internal communication platform. Every discussion remotely related to politics, he wrote, was spinning away from pleasant. Again, the backstory is the story. According to [reporting by Casey Newton](https://www.npr.org/2021/05/07/994812274/basecamp-blowup-banning-politics-at-work-prompts-over-a-dozen-employees-to-quit?ref=ceo.com), the real catalyst was an internal reckoning over a long-maintained list of "funny" customer names, many of which were ethnic names of Asian or African descent. When employees began to examine why the list existed and to advocate for diversity initiatives, tensions escalated. Fried's ban came alongside the disbanding of a newly formed employee-led diversity committee. Approximately one-third of the company's 57 employees resigned. The head of design. Head of marketing. Head of customer support. Nearly the entire iOS team. Fried [later apologized](https://www.theregister.com/2021/05/05/basecamp%5Fpolitical%5Fdiscussion%5Fapology/?ref=ceo.com), calling the week "terrible." [Stanford's Graduate School of Business](https://www.gsb.stanford.edu/faculty-research/case-studies/politics-workplace-aligning-or-alienating?ref=ceo.com) turned both situations into a case study. The central question: does political neutrality promote organizational cohesion, or does it silence marginalized voices? Both CEOs said they were drawing a clean line between the work and the world. Both discovered that the line isn’t perfectly straight. --- A [2025 Bentley University-Gallup survey](https://news.gallup.com/poll/692981/support-businesses-taking-public-stance-rebounds.aspx?ref=ceo.com) found that 51% of Americans now believe companies should take public stances on current events. That's up from 38% one year earlier. A 13-point jump. But buried in the same data is a contradiction: most employed Americans say their own employers shouldn't communicate those stances to workers internally. We want CEOs to speak for us. We don't want to hear about it at work. Rock. Hard place. Nassim Nicholas Taleb would recognize this as a kind of [fragility](https://www.amazon.com/Antifragile-Things-That-Disorder-Incerto/dp/0812979680?ref=ceo.com). The expectation is structured so that leaders absorb all the risk. Speak up, and you alienate half your stakeholders. Stay silent, and the other half fills the void with their own interpretation. Every position is punished. Every silence is interpreted. The system is designed so that someone always breaks. Taleb spent his career studying what he calls [Black Swans](https://www.amazon.com/Black-Swan-Impact-Improbable-Incerto/dp/1400063515?ref=ceo.com), the highly improbable events that carry massive consequences. COVID was one. But so is every cultural and political flashpoint that arrives without warning and demands a response from people who never claimed expertise on the subject. George Floyd. January 6th. Roe v. Wade. The war in Ukraine. These events don't fit into quarterly objectives. They don't come with briefing papers. And they carry enormous consequences for anyone who leads people through them. Taleb's deeper idea, though, is about what happens after the disruption. He distinguishes between the fragile, which breaks under stress, the robust, which endures it, and the antifragile, which gets stronger because of it. --- In March 2020, the organization I was running went from holding an in-person event nearly every day to holding none. Overnight. We weren't built for pandemic response. We were built for community. For bringing people together in rooms. That was the whole point. But the crisis didn't care what we were built for. We got pulled into government affairs, public health logistics, and federal lending programs. We helped coordinate COVID testing. We tracked down PPE. We became a clearinghouse for PPP loan information so small businesses in our community could survive long enough to reopen. None of it was why we started the organization. What stayed with me after it was all over wasn't the work itself. It was the shift in expectation that followed. Before COVID, leading a tech community meant leading a tech community. After COVID, it meant something broader and more difficult to define. The crisis forced us into unfamiliar territory, and once we operated there, the expectation stuck. Leaders were now supposed to have a position on things far beyond their expertise, their industry, their training. Something changed during the pandemic. Maybe it was that people saw what leaders could do when they mobilized outside their lane. Maybe it was that trust in other institutions was already eroding, and people needed someone to look to. Maybe it was just that the world got loud enough that silence started to feel like a choice. Whatever it was, we didn't go back. No one wants to go backward. --- Havel spent his life arguing that the most powerful act is simply refusing to participate in a fiction. For the greengrocer, the fiction was a Party slogan he didn't believe. For leaders today, I'm not sure which fiction is more dangerous: that you can run a company without acknowledging the world your people live in, or that every CEO owes the public a position on every issue of the day. Both are signs in the window. And the people watching are always reading. ### Kodak, Blockbuster, and the leaders who saw it coming URL: https://www.ceo.com/blog/kodak-blockbuster-and-the-leaders-who-saw-it-coming/ Last updated: 2026-08-19T03:02:24.000Z The common narrative about Kodak and Blockbuster is that their leaders were blindsided by digital disruption. The truth is more instructive and more painful. Kodak invented the digital camera in 1975\. Blockbuster had an opportunity to buy Netflix for $50 million in 2000 and passed. In both cases, the leaders saw the disruption coming and chose not to act. This case study examines the psychology of inaction in the face of disruption, drawing parallels to the current AI moment. The pattern is remarkably consistent: leaders see the threat, commission reports confirming the threat, hold strategy sessions about the threat, and then continue doing what they've always done because the core business is still generating revenue. The revenue becomes the enemy of adaptation. --- ## The Invention That Couldn't Be Told In 1974, a young electrical engineer named Steve Sasson was given what his supervisors at Eastman Kodak considered a throwaway assignment: investigate whether a recently developed device called a charge-coupled device could be used to capture images. [Sasson had joined Kodak](https://www.invent.org/inductees/steven-sasson?ref=ceo.com) the year before, fresh out of Rensselaer Polytechnic Institute. He was given complete autonomy and minimal expectations. His persistence produced something extraordinary. By December 1975, Sasson had built a device that combined a Super 8 movie camera lens, 16 nickel cadmium batteries, an analog-to-digital converter, and several dozen circuits wired together on six circuit boards. It weighed eight pounds. It captured black-and-white images at 100 by 100 pixels and stored them on a cassette tape. It was [the world's first self-contained digital camera](https://spectrum.ieee.org/first-digital-camera-history?ref=ceo.com). What happened next would define the next four decades of Kodak's trajectory. Sasson demoed the camera for executives. He would walk into a room, take pictures of the people present before saying anything, then pop the tape into a playback unit and display the image on a television. According to Sasson's account to [PetaPixel](https://petapixel.com/how-steve-sasson-invented-the-digital-camera/?ref=ceo.com), the executives didn't ask how it worked. They asked why anyone would want to take a picture this way when there was nothing wrong with conventional photography. When Sasson estimated the technology would need 15 to 20 years to match film quality, the response was effectively: we have time. The [World Economic Forum](https://www.weforum.org/stories/2016/06/leading-innovation-through-the-chicanes/?ref=ceo.com) later reported that management's reaction to Sasson's filmless photography was dismissive, treating the invention as a curiosity rather than a signal. Kodak patented the technology in 1978 but did not develop it for sale. Sasson continued working on digital imaging for the rest of his career at Kodak, developing the first prototype megapixel digital camera in 1989 alongside colleague Robert Hills. Kodak [declined to sell that product too](https://www.invent.org/blog/inventors/Legacy-Steve-Sasson?ref=ceo.com), in order to protect film sales. This is the detail that transforms the Kodak story from a case of corporate blindness into something far more troubling. The leaders were not blind. They could see. They chose not to look. --- ## The Revenue Trap At its peak in the mid-1990s, Kodak controlled [90 percent of the U.S. film market and 85 percent of camera sales](https://businesshistory.domain-b.com/focus/kodak-a-journey-from-creating-memories-to-bankruptcy?ref=ceo.com). In 1996, the company reported $15.9 billion in revenue, employed more than 140,000 people, and held a market capitalization exceeding [$28 billion](https://quartr.com/insights/edge/the-dilemma-that-brought-down-kodak?ref=ceo.com). The Kodak brand was among the most recognized in the world. The yellow box showed up in photo studios, corner stores, and family vacations on every continent. This is where the psychology becomes relevant. Daniel Kahneman, Amos Tversky, and Richard Thaler published a [landmark paper in 1991](https://www.aeaweb.org/articles?id=10.1257/jep.5.1.193&ref=ceo.com) documenting what they called the endowment effect and its relationship to loss aversion and status quo bias. Their central finding: people weigh potential losses from changing the status quo far more heavily than potential gains. The pain of losing what you have is roughly two and a half times more powerful than the pleasure of gaining something equivalent. Apply this to Kodak's leadership and the calculus becomes clear. Digital photography promised uncertain future gains. Film photography was generating $15.9 billion in certain present revenue. Every rational incentive, every quarterly earnings call, every bonus structure, every organizational habit pointed in one direction: protect the film business. Kodak did eventually enter the digital camera market. By 2005, the company was actually the [leading seller of digital cameras in the United States](https://businesshistory.domain-b.com/focus/kodak-a-journey-from-creating-memories-to-bankruptcy?ref=ceo.com). But the margins on digital cameras were nothing like the margins on film. Kodak had built its empire on a razor-and-blade model, selling cameras cheaply and profiting from film and processing. Digital photography eliminated the blade. There was nothing recurring to sell. Each camera was a one-time transaction. In January 2012, Kodak filed for [Chapter 11 bankruptcy protection](https://en.wikipedia.org/wiki/Kodak?ref=ceo.com). Court filings showed $5.1 billion in assets against $6.8 billion in liabilities. Among the patents sold during bankruptcy proceedings were seminal digital imaging patents, the very technology Kodak had pioneered. The company that invented the future sold the future to survive the present. --- ## The Meeting in Dallas The Blockbuster story follows the same architecture, but with its own instructive details. In September 2000, Netflix co-founders Reed Hastings and Marc Randolph flew to Dallas on a chartered plane to meet with Blockbuster CEO John Antioco. Netflix had been requesting this meeting for months. When Blockbuster finally agreed, it gave the Netflix team less than 12 hours notice, requiring them to be at the Renaissance Tower headquarters by 11:30 the following morning. As Randolph later described it, the scheduling itself communicated something about how seriously Blockbuster took the conversation. Hastings and Randolph arrived at Blockbuster's 27th-floor conference room. Blockbuster was then a $6 billion company with nearly 9,000 stores and 84,000 employees. Netflix was unprofitable and losing money on its DVD-by-mail service. As Hastings later recalled in his book [*No Rules Rules*](https://www.marketplace.org/story/2020/09/08/ceo-reed-hastings-on-how-netflix-beat-blockbuster?ref=ceo.com), he whispered to Randolph as they entered that Blockbuster was a thousand times their size. The proposal was straightforward. Netflix would handle Blockbuster's online operations, essentially becoming [Blockbuster.com](http://blockbuster.com/?ref=ceo.com). The price: $50 million. According to Randolph's account in [*That Will Never Work*](https://www.inc.com/minda-zetlin/netflix-blockbuster-meeting-marc-randolph-reed-hastings-john-antioco.html?ref=ceo.com), Antioco listened carefully throughout the pitch, nodding and making eye contact. But when the number was revealed, the room shifted. Randolph described Antioco as struggling to suppress a reaction. The answer was no. What makes the Blockbuster story more complex than the simple version is what happened afterward. Antioco was not a passive leader content to ride the status quo into the ground. According to his own [account in Harvard Business Review](https://hbr.org/2011/04/how-i-did-it-blockbusters-former-ceo-on-sparring-with-an-activist-shareholder?ref=ceo.com), once he became convinced that Netflix posed a genuine threat, he acted. He launched Blockbuster Online in 2004\. He eliminated the late fees that customers hated, at a cost of roughly $200 million in annual revenue. In 2006, he introduced [Total Access](https://www.inc.com/greg-satell/blockbuster-had-a-brilliant-strategy-to-beat-netflix-but-then-failed-to-survive-victory.html?ref=ceo.com), a program that let customers return online rentals at physical stores for a free additional rental. Within weeks, Blockbuster was winning the majority of new subscribers and outpacing Netflix's growth. It was working. And then it was stopped. The investments cost roughly $400 million to implement. Profitability dropped. The stock price fell. Activist investor Carl Icahn began acquiring shares and [challenged Antioco's leadership](https://www.kornferry.com/insights/briefings-magazine/issue-35/how-blockbuster-became-house-of-cards?ref=ceo.com). A proxy fight followed. Antioco left the company in 2007 over a compensation dispute and strategic disagreements with the board. His successor, Jim Keyes, immediately reversed the online strategy to improve short-term profitability. Blockbuster filed for bankruptcy in 2010\. Today, one privately owned franchise location remains open, in Bend, Oregon. Antioco later wrote that he firmly believed the online strategy would have succeeded if it had not been abandoned. The disruption was not that leadership failed to see the threat. The disruption was that the organization could not tolerate the cost of responding to it. --- ## The Dilemma Behind the Dilemma In 1997, a year before Antioco began his tenure at Blockbuster, Harvard Business School professor Clayton Christensen published [*The Innovator's Dilemma*](https://www.hbs.edu/faculty/Pages/item.aspx?num=46&ref=ceo.com). The book's central argument has become one of the most cited ideas in business: successful companies fail not because they make bad decisions, but because they make good ones. Christensen's framework explains why the Kodak and Blockbuster failures are not aberrations but patterns. Disruptive technologies initially appear inferior to existing products. They serve niche markets that established companies don't care about. The established company's best customers don't want the new technology. Its most reliable revenue streams don't depend on it. Every signal the organization trusts, from customer feedback to financial projections to competitive analysis, says to stay the course. The dilemma is that the same practices that made these companies dominant, listening to customers, investing in proven technologies, maximizing returns on existing assets, become the mechanisms of their decline. Steve Jobs reportedly said the book deeply influenced his thinking. Andy Grove, CEO of Intel, called it the most important book of the decade. Marc Benioff, CEO of Salesforce, wrote the foreword to a later edition. What Christensen described structurally, Kahneman and Tversky described psychologically. The bias toward inaction is not a character flaw. It is a feature of how the human mind evaluates risk. [Samuelson and Zeckhauser's 1988 research](https://link.springer.com/article/10.1007/s11301-022-00283-8?ref=ceo.com) on status quo bias found that the preference for maintaining the current state grows stronger as the number of alternatives increases and as uncertainty rises. The more complex the disruption, the more powerful the gravitational pull of doing nothing. Kahneman and Tversky's own research demonstrated that people feel greater regret for bad outcomes resulting from action than for equivalent bad outcomes resulting from inaction. Losing money because you made a trade feels worse than losing money because you didn't. Failing because you tried a new strategy feels worse than failing because you stuck with the old one. The asymmetry is not rational, but it is real, and it operates at the level of individuals, teams, and entire organizations. --- ## The Self-Destruct Pattern There is a specific sequence that repeats across these stories, and it is worth naming explicitly because it is happening again right now. It begins with invention. Someone inside the organization, or just adjacent to it, demonstrates a technology that could fundamentally alter the business. The technology is crude. It does not yet threaten the core product. Leadership acknowledges it as interesting. Next comes assessment. Reports are commissioned. Strategy sessions are held. Consultants are hired. The conclusion is always some version of the same finding: this technology will eventually matter, but not yet. The core business is still growing. There is time. Then comes the revenue defense. The organization begins making decisions designed to protect existing revenue rather than capture future revenue. Digital cameras are priced to protect film margins. Online rental services are underfunded to protect store profitability. AI features are bolted onto existing software to preserve per-seat licensing. The logic is always the same. The existing business is real. The future business is theoretical. Finally comes the point of no return. The technology improves faster than predicted. New entrants who have no legacy revenue to protect move aggressively. The established company attempts to pivot, but the organizational muscle memory, the incentive structures, the customer relationships, the board expectations, and the sheer weight of quarterly earnings all resist the turn. By the time the pivot is fully committed, the window has closed. Kodak had a 37-year head start on digital photography and still filed for bankruptcy. Blockbuster had a working online strategy that was outpacing Netflix and still filed for bankruptcy. The technology was not the problem. The pattern was. --- ## The AI Parallel This case study accompanies the essay [**AI Was the Opportunity. Now It's Also the Threat**](https://www.ceo.com/c/magazine/ai-was-the-opportunity-now-it-s-also-the-threat)**”** on CEO.com, which examines the current SaaS selloff and the AI disruption facing the software industry. The parallels are not subtle. In February 2026, the S&P 500 Software Index dropped 13 percent in five trading sessions. Salesforce lost 29 percent of its value year to date. ServiceNow shed $115 billion in market capitalization. The trigger was the same thing that triggered every prior disruption: a demonstration that a new technology could do what the old model did, faster, cheaper, and without the constraints that made the old model profitable. The SaaS companies seeing their valuations collapse are not blind to AI. They are investing billions in it. They are building copilots, integrating large language models, and hiring AI researchers. But they are doing so within the constraints of their existing business models, just as Kodak launched digital cameras designed to protect film margins, and just as Blockbuster funded online rentals only until the cost threatened quarterly earnings. The leaders can see the disruption coming. That has never been the hard part. --- ## The Question Christensen died in January 2020, three years before generative AI reached the mainstream. But the framework he spent his career building was designed for precisely this moment. The question is not whether AI will disrupt existing business models. The question is whether the leaders who see it coming will act on what they see, or whether they will follow the pattern and protect the revenue until the revenue can no longer be protected. Kodak's Steve Sasson kept working on digital photography from the day he invented it in 1975 until the day he retired. Blockbuster's John Antioco built an online strategy that was beating Netflix and then watched someone else dismantle it. In both cases, the knowledge was there. The courage to absorb the short-term cost of acting on that knowledge was not. The psychology of inaction is not about intelligence. It is not about vision. It is about the willingness to endure the pain of transition while the existing business is still generating revenue. It is about choosing the uncertain future over the certain present. It is about leading through the valley where the old model is dying and the new model has not yet proven itself. That valley is where most leaders lose their nerve. And that valley is where we are right now. ### AI was the opportunity; now it's also the threat URL: https://www.ceo.com/blog/ai-was-the-opportunity-now-it-s-also-the-threat/ Last updated: 2026-08-14T00:52:10.000Z For three years, AI was the stock market's golden child. Every earnings call featured some version of the same pitch: we're integrating AI, we're deploying AI, we're building the future with AI. The message to investors was simple. AI is the opportunity. Adopt it or get left behind. In the past two weeks, that story has inverted completely. [Anthropic's launch of Claude Cowork](https://www.bloomberg.com/news/articles/2026-02-04/what-s-behind-the-saaspocalypse-plunge-in-software-stocks?ref=ceo.com) and its agentic plugins triggered what traders at Jefferies are now calling the "[SaaSpocalypse](https://finance.yahoo.com/news/traders-dump-software-stocks-ai-115502147.html?ref=ceo.com)," an indiscriminate selloff that has erased more than [$800 billion in market value](https://www.investing.com/news/stock-market-news/us-software-stocks-stabilize-after-bruising-selloff-on-ai-disruption-fears-4487518?ref=ceo.com) from the software sector in six trading sessions. The S&P 500 Software Index dropped 13% in five trading sessions. The iShares Expanded Tech Software Sector ETF is [down nearly 30% from its September high](https://www.theregister.com/2026/02/04/ai%5Freplace%5Fsaas?ref=ceo.com). Salesforce is down 29% year-to-date. ServiceNow has lost $115 billion in market cap since late January. Adobe, Microsoft, SAP, and Oracle have collectively shed hundreds of billions more. The IPO window has [frozen shut](https://markets.financialcontent.com/stocks/article/marketminute-2026-2-11-the-saaspocalypse-software-sector-plunge-freezes-ipos-and-reshapes-the-digital-economy?ref=ceo.com). Private equity firms are hiring consultants to stress-test their portfolios for AI vulnerability. Hedge funds have piled into short positions. The question for CEOs is no longer "How do we adopt AI?" It is "Is AI about to eat our business?" ## The screwdriver vs. the newspaper Two competing narratives are fighting for control of the conversation right now, and which one you believe will shape how you lead through the next several years. The first comes from Jensen Huang, who called the panic "[the most illogical thing in the world](https://www.cnbc.com/2026/02/06/ai-anthropic-tools-saas-software-stocks-selloff.html?ref=ceo.com)." His argument is that AI will use and enhance existing software, not replace it. Software is a screwdriver. AI is the hand that picks it up. You don't throw away the screwdriver because the hand got stronger. Arm Holdings CEO Rene Haas echoed the sentiment, calling the market reaction "micro-hysteria." Bank of America published a note arguing the selloff is [built on two mutually exclusive premises](https://fortune.com/2026/02/04/why-saas-stocks-tech-selloff-freefall-like-deepseek-2025-overblown-paradox-irrational/?ref=ceo.com): that AI spending will collapse because it's not delivering returns, and simultaneously, that AI will be so effective it renders all existing software obsolete. You can believe one of those things. You cannot logically believe both. The second narrative is darker and more structural. Goldman Sachs analysts have compared the software sector's trajectory to that of newspapers in the early 2000s, when disruption began as a slow leak and then became a flood. Microsoft CEO Satya Nadella himself laid the groundwork for this argument [over a year ago](https://www.theregister.com/2026/02/04/ai%5Freplace%5Fsaas?ref=ceo.com), saying that business applications would "all collapse in the agent era" because AI agents won't discriminate between backends. They'll just update multiple databases, and all the logic will live in the AI layer. When the CEO of the world's largest software company tells you that traditional business applications are structurally vulnerable, it is worth taking seriously. The math behind this second narrative is straightforward and unforgiving. If 10 AI agents can do the work of 100 sales reps, you don't need 100 Salesforce seats anymore. You need 10\. That is a [90% reduction in seat revenue](https://www.tradingkey.com/analysis/stocks/us-stocks/261581475-ai-saas-selloff-who-really-wins-and-loses?ref=ceo.com) for the same work output. The per-seat licensing model, which generated predictable, recurring revenue for a generation of software companies, suddenly appears to have a structural ceiling. And it is not just the pricing model. IT budgets are being actively redirected. [CIO surveys show budget growth decelerating](https://markets.financialcontent.com/stocks/article/marketminute-2026-2-11-saaspocalypse-2026-why-wall-street-is-slashing-software-valuations-and-turning-cautious-on-debt?ref=ceo.com), with funds moving away from application software and toward the massive compute costs of AI infrastructure. ## The self-destruct paradox Here is the part that should keep every software CEO up at night: the companies trying hardest to survive are accelerating their own disruption. Salesforce is aggressively pushing its Agentforce platform. Adobe is embedding generative AI across its creative suite. ServiceNow is building AI into its workflow automation. But the more successful those AI features become at automating work, the fewer human users need the software, and the fewer seats those companies sell. It is a [self-destruct paradox](https://www.tradingkey.com/analysis/stocks/us-stocks/261581475-ai-saas-selloff-who-really-wins-and-loses?ref=ceo.com). Success in AI undermines the business model that pays the bills. This is not theoretical. It is already showing up in the numbers. The narrative through 2024 and early 2025 was that AI would augment incumbents and make their products stickier. By late 2025, the reality on the ground was that the pace at which incumbents were adding AI lagged the pace at which native AI tools were beginning to replace them. Jason Lemkin, whose SaaStr blog has been a barometer for the industry for over a decade, offered a [characteristically blunt assessment](https://www.saastr.com/the-2026-saas-crash-its-not-what-you-think/?ref=ceo.com). The crash, he argues, is not really about AI killing SaaS overnight. Nobody is vibe-coding a replacement for their Salesforce instance in Replit. Building a version one of any product is maybe two percent of the actual work of running enterprise software. The crash is the market finally pricing in a deceleration that has been building for years. Revenue growth was already slowing. Net retention rates were already stalling. AI just made the reckoning urgent. The era of easy SaaS growth is over. ## How agents actually kill software It is worth understanding the mechanics of this threat, because it is not the same story that has been told about AI for the past three years. The old story was about copilots. AI sits beside a human, suggests a line of code, drafts an email, summarizes a meeting. The human stays in control. The software stays necessary. The seat stays billable. That story was comfortable for incumbents because it meant AI made their products better without threatening the underlying business model. The new story is about agents. An AI agent does not assist a human using software. It uses the software itself, or it bypasses it entirely. It reads the database directly, executes the workflow, updates the records, and moves on to the next task. The human who used to sit in front of the CRM, project management tool, or legal review platform is now optional. And when the human becomes optional, so does the per-seat license that paid for their access. This is what Satya Nadella was describing when he said business applications are "[essentially CRUD databases with a bunch of business logic](https://www.theregister.com/2026/02/04/ai%5Freplace%5Fsaas?ref=ceo.com)" and that in the agent era, all the logic moves to the AI layer. Agents will not discriminate between backends. They will update multiple databases simultaneously, and the value will live in the intelligence tier, not in any individual application's interface. The implications cascade. [Bessemer Venture Partners](https://www.bvp.com/atlas/building-vertical-ai-an-early-stage-playbook-for-founders?ref=ceo.com) frames it bluntly: vertical AI is not competing for IT budgets. It is competing for labor budgets. Traditional vertical SaaS captures a fraction of Fortune 500 IT spend. Vertical AI taps directly into the labor line of a P&L. When an AI agent can do the work of a junior associate at a law firm, a first-year analyst at a bank, or a customer service rep at a SaaS company, the disruption is not to the software budget. It is to headcount. And when headcount shrinks, so does the total addressable market for every tool those workers used. Consider the [practical examples](https://www.tradingkey.com/analysis/stocks/us-stocks/261581475-ai-saas-selloff-who-really-wins-and-loses?ref=ceo.com) already emerging. In customer service, AI agents can handle ticket volumes that used to require a full team, cutting service-desk costs by 30% or more in early deployments. In sales, agents can handle prospecting, qualification, and follow-up sequences that previously justified dozens of seats on a CRM. In legal, AI can review contracts, flag risk, and generate redlines faster than a team of associates. Every one of those use cases represents not just a productivity gain but a seat reduction. The more capable the agent, the fewer humans in the loop, the fewer licenses sold. ## When the model companies come for your market And then there is the question nobody in SaaS wants to ask out loud: what happens when AI model companies stop being platforms and become products? This past weekend, [OpenAI hired Peter Steinberger](https://www.cnbc.com/2026/02/15/openclaw-creator-peter-steinberger-joining-openai-altman-says.html?ref=ceo.com), the creator of OpenClaw, the open-source AI agent that [racked up 180,000 GitHub stars](https://decrypt.co/358129/openclaw-creator-offers-acquire-ai-sensation-stay-open-source?ref=ceo.com) and became the fastest-growing consumer AI tool in history. Sam Altman said Steinberger will "drive the next generation of personal agents" and that the technology will "[quickly become core to our product offerings](https://techcrunch.com/2026/02/15/openclaw-creator-peter-steinberger-joins-openai/?ref=ceo.com)." Steinberger himself [predicts that agents like OpenClaw will eliminate 80% of current apps](https://decrypt.co/358129/openclaw-creator-offers-acquire-ai-sensation-stay-open-source?ref=ceo.com). His reasoning is simple: every app is just a slow API now. Why open a separate tool for food delivery, calendar management, or expense tracking when your agent already knows your context, your preferences, and your schedule? This is the move that should alarm every software CEO. It is one thing when AI makes your product more efficient. It is another thing entirely when the companies building the AI models start building the products themselves. In January, [both OpenAI and Anthropic announced HIPAA-compliant life sciences tools](https://www.theregister.com/2026/02/04/ai%5Freplace%5Fsaas?ref=ceo.com) that compete directly with Veeva and Salesforce's healthcare offerings. These are not generic AI features. They are vertical products targeting specific markets that SaaS companies spent years and billions of dollars building out. The pattern is familiar if you have been in tech long enough. Google started as a search engine, then became an email provider, a document suite, a cloud platform, a phone operating system. Amazon started as a bookstore, then became everything. When platform companies decide to move up the stack into applications, incumbents rarely survive the transition. The question is whether Anthropic, OpenAI, Google, and Meta will follow the same playbook. The [early signals suggest they will](https://www.theregister.com/2026/02/04/ai%5Freplace%5Fsaas?ref=ceo.com). And unlike previous platform shifts, this one could move much faster because the marginal cost of building an AI-native application on top of your own model is close to zero. ## What the market is actually pricing in [Bain & Company published an analysis](https://www.bain.com/insights/why-saas-stocks-have-dropped-and-what-it-signals-for-softwares-next-chapter/?ref=ceo.com) that cuts through some of the noise. Enterprise customers, they found, actually prefer to buy AI-enabled solutions from their incumbent vendors. They trust them, they know the security posture, they believe they will be around long-term. But most incumbents have not yet delivered compelling AI offerings. And even where they can, many have not figured out how they would get paid for them. This is the real crisis. The market is not pricing in the death of software. It is pricing in the possibility that the transition from selling seats to selling outcomes will take longer, cost more, and destroy more value than anyone wants to admit. The companies that figure it out will lead the next cycle. The companies that do not will join a long list of industries that saw disruption coming and still could not move fast enough. Some categories look better positioned than others. [Usage-based companies like Datadog and MongoDB](https://www.tradingkey.com/analysis/stocks/us-stocks/261581475-ai-saas-selloff-who-really-wins-and-loses?ref=ceo.com) function as something like tax collectors on AI activity. As agents proliferate, they generate more API calls, more database queries, more compute cycles. Companies that charge by usage rather than by seat effectively benefit when AI does more work. Mission-critical infrastructure providers like Oracle and ServiceNow, whose products are deeply embedded in customer workflows, have what one analyst called a sustained "[right to earn](https://www.cnbc.com/2026/02/06/ai-anthropic-tools-saas-software-stocks-selloff.html?ref=ceo.com)." Their data moats and operational entrenchment make them more likely to coexist with AI than be replaced by it. Then there is an emerging category that does not yet fully exist: AI orchestration. The software that manages, secures, audits, and governs the AI agents themselves. As businesses shift from humans using software to AI agents using software on behalf of humans, the companies that provide the security and governance layer for those agents will become the [new must-have line item](https://markets.financialcontent.com/stocks/article/marketminute-2026-2-11-saaspocalypse-2026-why-wall-street-is-slashing-software-valuations-and-turning-cautious-on-debt?ref=ceo.com) in the IT budget. ## The leadership question I live in Utah, one of the world's SaaS capitals. Silicon Slopes is home to Qualtrics, Pluralsight, Domo, Podium, and hundreds of other software companies built on the per-seat subscription model that the market is now questioning. This is not an abstract financial story here. It is a daily conversation at every dinner, every board meeting, every coffee between founders and VCs along the Wasatch Front. People I know, people I work with, are watching their companies lose a third of their market value in weeks. At the [Silicon Slopes Summit](https://www.sltrib.com/news/2026/02/07/meta-hed-silicon-slopes-conference/?ref=ceo.com) earlier this month, the subtext of nearly every panel was the same: what do we do now? What I have learned from a decade in this community is that moments like this reveal character. Not strategy. Character. The instinct when your stock drops 25% in a month is to do one of two things: panic and slash everything in sight, or go on CNBC and insist everything is fine. Neither response works. The first destroys your capacity to adapt. The second destroys your credibility when the next quarter comes in soft. The leaders who survive disruption are not the ones who predict the future correctly. They are the ones who build organizations capable of adapting to whatever future arrives. That means doing a few things that are uncomfortable but necessary. First, assess the threat honestly. Not every company is equally exposed. If your revenue comes primarily from per-seat licensing of features that AI can plausibly automate, you are in the direct path. If your product sits at the infrastructure or data layer, you have more time. The worst thing you can do is pretend the distinction does not matter. Second, stop confusing AI adoption with AI strategy. Every company in America has adopted AI to some degree. Very few have actually rethought their business model in response to it. There is a difference between adding a chatbot to your product and reconceiving how you create and capture value in a world where autonomous agents do an increasing share of the work. Third, be honest with your board and your team about what you do not know. The [Fortune analysis of this selloff](https://fortune.com/2026/02/13/scary-saas-selloff-changes-calculus-startups-private-markets-code-alone-was-never-a-real-moat/?ref=ceo.com) quoted one investor who captured the real fear: "What's scarier than uncertainty?" The temptation in uncertain moments is to project false confidence. The better move is to name the uncertainty, define the scenarios, and make sure your organization can execute under any of them. This is personal leadership in its most essential form. Not having the answers, but having the honesty to say you are working on finding them, and the discipline to build an organization that can turn on a dime when the answers become clear. ## The mantra has changed For the past decade, the technology industry operated under a single mantra: software is eating the world. Build software, sell subscriptions, grow recurring revenue, and watch the multiples expand. That playbook produced some of the most valuable companies in history. In 2026, the mantra has changed. AI is eating the software budget. The question is whether you are the one holding the fork or sitting on the plate. The market will sort itself out. Some of this selloff is rational repricing. Some of it is panic. The software sector is almost certainly oversold in the short term. But the structural questions underneath the volatility are real, and they are not going away. The companies that thrive will be led by people who can hold two truths simultaneously: that their current business still works today and that it may not work three years from now. The ability to live in that tension, to plan for the present while building for a fundamentally different future, is what separates leaders from administrators. The tool has become the competitor. Act accordingly. ### Howard Schultz and the Starbucks crisis of 2008 URL: https://www.ceo.com/blog/howard-schultz-and-the-starbucks-crisis-of-2008/ Last updated: 2026-08-19T02:58:44.000Z When Howard Schultz returned as CEO of Starbucks on January 8, 2008, the company he had built was unrecognizable. Same-store sales were declining for the first time in the company's history. The stock had lost roughly half its value from its 2006 peak. Profit had fallen 28 percent year over year. McDonald's was rolling out McCafé espresso bars in direct competition. And the worst financial crisis since the Great Depression was months away from hitting. Schultz had stepped away from daily operations in 2000, handing the CEO role to successors who presided over explosive expansion. Between 2004 and 2008, Starbucks doubled its store count from roughly 8,500 to nearly 17,000 locations. But the growth masked a deeper rot. As a [Harvard Business School case study](https://academyci.com/wp-content/uploads/2020/01/Starbucks-case-for-Structured-2019.pdf?ref=ceo.com) on the turnaround later documented, the company had drifted from its core identity. Automated espresso machines replaced barista craft. Prepackaged food filled display cases. Stores that were meant to feel like neighborhood gathering places felt like chain restaurants. The company that Schultz had built around the concept of a "third place" between home and work had become, by his own admission, a soulless operation optimized for speed. None of this was a secret to Schultz. Almost a year before his return, on Valentine's Day 2007, he had written an internal memo to then-CEO Jim Donald titled "The Commoditization of the Starbucks Experience." The memo was meant to be private. It was leaked to the internet within days. ## **What the Memo Revealed** The leaked memo, [authenticated by The Wall Street Journal](https://idea-sandbox.com/starbucks-memo/?ref=ceo.com), was remarkable not for what it said but for who said it. This was the founder of the company acknowledging, in writing, that a decade of decisions made in pursuit of growth had diluted the very thing that made Starbucks worth building. He pointed to streamlined store designs that had stripped out warmth and character. He pointed to the tall automatic espresso machines that blocked the line of sight between barista and customer. He pointed to the sealed flavor-locked packaging that eliminated the aroma of fresh-ground coffee from the store experience. As [Nation's Restaurant News reported](https://www.nrn.com/restaurant-technology/starbucks-founder-s-leaked-memo-reflects-fears-about-brand-dilution?ref=ceo.com) at the time, marketing strategist Al Ries called the memo courageous precisely because the company was not yet in crisis when it was written. Most executives wait until the numbers force their hand. Schultz wrote it while Starbucks was still posting revenue growth. He saw the erosion before the market did. The memo was embarrassing in the moment. It rattled investors and gave competitors ammunition. But in retrospect, Schultz has said it served as a galvanizing force inside the company, forcing conversations that the leadership team had been avoiding. ## **The Decisions** When Schultz took back the CEO title in January 2008, he did not arrive with a fully formed plan. He arrived with clarity about what Starbucks had lost and a willingness to make decisions that served identity over short-term performance. The first move was symbolic and practical at the same time. On February 26, 2008, Schultz [closed all 7,100 U.S. stores for an evening](https://www.nbcnews.com/id/wbna23351151?ref=ceo.com) to retrain 135,000 baristas on the craft of making espresso. The company lost over $6 million in revenue in a single night. Analysts called it reckless. Investors were already nervous. But Schultz understood that the retraining was not really about espresso technique. It was a declaration, both internal and external, that Starbucks would recommit to the experience that had built the brand, even at a measurable cost. The second move was harder. He eliminated the breakfast sandwiches that stores had been selling. The sandwiches were profitable. Customers liked them. But the smell of heated cheese and egg was overpowering the aroma of coffee, and Schultz saw this as a physical manifestation of how the company had lost its way. In his book "Onward," he described the sandwich smell as one of the things that had most deeply frustrated him during his time away from operations. He ordered them removed, overruling the executive team. The sandwiches were eventually reformulated and brought back, but only after the smell problem was solved. The third move was the most painful. In July 2008, Starbucks [announced it would close 600 underperforming stores](https://www.npr.org/2008/07/02/92126521/starbucks-store-closures-to-affect-12-000-workers?ref=ceo.com), affecting roughly 12,000 employees. As NPR reported, most of the targeted locations had opened since 2006, which meant the company was shutting down nearly one in five of all the stores it had built in the previous two years. In January 2009, Schultz closed an additional 300 stores and cut 7,000 positions. He took a salary reduction approved by the board. Each of these decisions was made without certainty that it would work. Schultz did not know whether retraining baristas would actually change the customer experience. He did not know whether pulling the sandwiches would hurt sales more than it helped the brand. He did not know whether closing 600 stores was enough, or too many, or too few. What he had was not certainty. It was clarity about what Starbucks needed to stand for. ## **The Power of Public Honesty** What separates the Schultz turnaround from a standard corporate restructuring is the role that honesty played. In a moment when most CEOs were projecting confidence and blaming external conditions, Schultz stood in front of his employees and said the problems were self-inflicted. As [BusinessToday documented](https://www.businesstoday.in/magazine/lbs-case-study/story/how-starbucks-survived-the-financial-meltdown-of-2008-136126-2014-09-22?ref=ceo.com) in a case study on the crisis, the previous leadership team had blamed the economy and rising dairy costs for the slump. Schultz rejected that framing entirely. On his first day back, he told employees that the company should not blame external conditions for problems created by its own bureaucratic expansion. This was not posturing. The [NBC News/BusinessWeek profile of Schultz](https://www.nbcnews.com/id/wbna32336151?ref=ceo.com) from 2009 described the atmosphere at Seattle headquarters in his first week back as "shell-shocked." Schultz was not gentle about it. He walked into a company that had forgotten what made it different and told them so. But he also told them he did not have every answer, that the turnaround would require the entire organization to rediscover what they stood for. In March 2008, he launched "My Starbucks Idea," a platform that invited customers to tell the company directly what it was getting wrong. Over 93,000 ideas were submitted. More than 100 were implemented. The move was unusual for a public company in crisis. Most organizations in that position tighten control. Schultz opened the door wider. ## **The Results** By the second half of 2009, Starbucks had stabilized. Same-store sales turned positive. Customer satisfaction scores improved. The stock, which had bottomed near $7 a share, [gained 143 percent in 2009](https://money.cnn.com/2018/06/05/news/companies/starbucks-howard-schultz-coffee/index.html?ref=ceo.com). Annual profit climbed from $315 million in 2008 to $945 million in 2010, as Schultz later [recounted to CNBC](https://www.cnbc.com/2025/05/01/howard-schultz-costco-co-founder-advice-was-core-principle-for-starbucks.html?ref=ceo.com). Over the following years, the stock price appreciated more than 1,000 percent from its 2009 low. Schultz stayed on as CEO until 2017, presiding over the launch of the mobile ordering platform, the expansion into China, and the development of the loyalty program that became an industry model. When he finally stepped away, Starbucks had more than 25,000 stores in 75 countries. ## **The Leadership Lesson** The Schultz turnaround is often studied as a case in operational execution. Close underperforming stores. Retrain employees. Refocus on core product. But those are the mechanics. The deeper lesson is about what made the mechanics possible. Schultz could close 7,100 stores for an evening because he had first told the truth about why the stores needed closing. He could cut 600 locations because he had taken responsibility for the overexpansion that created them. He could ask 135,000 employees to recommit to the craft of making coffee because he had publicly admitted that the company's leadership, himself included, had allowed the craft to erode. The honesty came first. The execution followed. This matters for the current moment because the temptation facing most leaders right now is to project certainty they do not have. The market is volatile. Institutions are unreliable. AI is rewriting the economics of entire industries. The instinct is to have the answer, to present the plan, to show the board and the team that you know exactly what comes next. Schultz's example suggests the opposite. When he returned to Starbucks in January 2008, he did not know exactly what came next. He knew what the company had to stand for. He knew which decisions were his to make. And he was honest, publicly, painfully honest, about what had gone wrong. That honesty did not make him look weak. It gave everyone around him permission to stop pretending and start working on the actual problem. In his book ["Onward,"](https://www.amazon.com/Onward-Starbucks-Fought-without-Losing/dp/1605292885?ref=ceo.com) Schultz wrote about the courage required to make choices that go against reason and the counsel of trusted advisors. The line that captures the turnaround best is his observation that *Starbucks' success was never an entitlement*. He had been saying it for twenty years before the crisis proved him right. The leaders who will navigate the current uncertainty best are not the ones who pretend to have certainty. They are the ones who know what their company stands for, who take responsibility for the decisions that led to this moment, and who are willing to say, in front of everyone, that they do not have every answer. And then make the best decision available with what they do know. That is personal leadership. Everything else is performance. ### The discipline of not knowing URL: https://www.ceo.com/blog/the-discipline-of-not-knowing/ Last updated: 2026-08-14T00:57:01.000Z I have spent an embarrassing amount of my career thinking about my reputation. How to build it. How to protect it. How to repair it when something went sideways. I have lain awake rehearsing conversations that hadn't happened yet, crafting responses to criticism that might never come, and strategizing about how to make sure the right people thought the right things about me. It took me years to understand that my reputation is not up to me. That sentence still makes me uncomfortable. I want it to not be true. I want to believe that if I do good work, treat people well, and show up consistently, the world will accurately reflect those things back to me. Sometimes it does. Often it doesn't. People will misunderstand you. They will project their own fears onto your decisions. They will tell stories about you that have almost nothing to do with who you actually are. And you will be tempted, as I have been tempted more times than I can count, to spend your finite energy correcting a narrative you never had the power to control. This is not just a waste of time. It is corrosive. It hollows you out. It replaces the actual work of leadership with its performance, and eventually you can't tell the difference between the two. --- Nearly two thousand years ago, a formerly enslaved man named Epictetus opened his [handbook on living](https://www.amazon.com/Enchiridion-Epictetus/dp/0879757035?ref=ceo.com) with a line that still cuts through every layer of self-deception I've ever built: "Some things are up to us, and some things are not." Up to us: our opinions, our desires, our aversions, our judgments. Not up to us: our bodies, our reputations, our wealth, other people's actions, external events. That's the whole list. Read it again. Notice how short the first one is and how long the second one is. Now think about where you spend most of your mental energy. If you're anything like me, you've spent years investing in column two. Trying to control outcomes that were never yours to control. And the cost of that investment is not just frustration. It is the slow erosion of your ability to lead, because you cannot lead from a place of constant reactivity to things you cannot change. Epictetus was not teaching passivity. He was teaching precision. Know what is yours. Work on what is yours. Release what is not. The discipline is in the sorting. --- I'm writing this on a week when the sorting feels particularly urgent. The U.S. government has shut down for the third time in four months. Markets are swinging hundreds of points in a day. CEOs across the country are trying to plan in an environment that changes between the start and the finish of a sentence. The Conference Board's [latest survey](https://www.conference-board.org/publications/C-Suite-Outlook-2026-Uncertainty-and-Opportunity?ref=ceo.com) found that 43% of U.S. CEOs now rank uncertainty as their single greatest economic threat. Not recession. Not inflation. Not competition. Uncertainty itself. Here is what Epictetus would say to every one of those CEOs: Of course you're uncertain. You were always uncertain. You just had institutions and market conditions that allowed you to pretend otherwise. The uncertainty didn't arrive this year. The pretense left. The government shutdown is not up to you. The market is not up to you. The regulatory environment, the trade policy, the next AI announcement that sends your stock price in a direction you didn't expect: none of it is up to you. What is up to you is how you show up on Monday morning. Whether you walk into that room and radiate the anxiety you absorbed over the weekend, or whether you've done the work to process it before it becomes your team's problem. Whether you make the decision you've been postponing, even without the certainty you wish you had. Whether you tell your people the truth about what you don't know, instead of performing confidence you don't feel. --- Epictetus said that disturbance comes not from events, but from our judgments about events. I've tested this idea against some of the hardest moments of my life, and it holds. The event is the event. What destroys us is the story we attach to it. This shouldn't be happening. This is going to ruin everything. I can't survive this. Those stories feel like truth. They are judgments. And judgments, unlike events, are up to us. I am not suggesting that you sit quietly while the world burns around you. I suggest that the leaders who best navigate uncertainty are not the ones who eliminate it. Nobody eliminates it. They are the ones who have trained themselves to act within it. To make the call with 60% of the information. To hold a conviction strongly enough to move but loosely enough to change course when the evidence demands it. The discipline of not knowing is not a philosophy for passive people. It is a practice for leaders who have decided to stop wasting their energy on things they cannot change and redirect it entirely toward the things they can. --- I still catch myself thinking about my reputation. It's a habit that was years in the making, and it doesn't die quietly. But now that I notice it, I try to do the sorting. Is this up to me? Is the opinion that someone holds of me based on a conversation I wasn't part of, a story I didn't write, a projection that has nothing to do with my actual choices? Is that up to me? No. It never was. What is up to me is the next decision I make. The next conversation I have. The quality of my attention when someone is talking to me. Whether I choose to react to the noise or respond to what actually matters. Epictetus was a man who had been owned by another human being. He had every reason to believe the world was beyond his control, because for most of his life, it literally was. And yet he arrived at the most liberating insight in the history of leadership philosophy: that the most powerful thing a person can do is stop trying to control what isn't theirs and get to work on what is. The uncertainty isn't going away. Not this week. Not this year. The question is whether you're going to spend your energy fighting that reality or leading within it. Some things are up to us. Some things are not. The discipline is knowing the difference. ### The last time scientists had this much power, they stopped themselves URL: https://www.ceo.com/blog/the-last-time-scientists-had-this-much-power-they-stopped-themselves/ Last updated: 2026-08-19T02:53:49.000Z In the winter of 1974, Paul Berg did something that would be unthinkable by today's standards of competitive innovation. He stopped. Berg was a biochemist at Stanford who had pioneered a technique called recombinant DNA, a method for splicing genes from one organism into another. The implications were staggering. For the first time in history, humans could rewrite the code of life itself. Berg's work would eventually earn him the Nobel Prize. But in that moment, standing at the edge of a transformation that could reshape medicine, agriculture, and human evolution, he chose to pause. He was not alone. Berg joined other leading scientists, including Stanley Cohen and Herbert Boyer, in calling for a voluntary moratorium on certain recombinant DNA experiments. They did this not because regulators forced them to, and not because the public demanded it. They did it because they understood that being first to a breakthrough meant nothing if the breakthrough destroyed the trust required to continue the work. In February 1975, 140 scientists gathered at the Asilomar Conference Center on California's Monterey Peninsula. For four days, they debated not how to accelerate their research, but how to constrain it. They emerged with a framework for safety guidelines that would govern genetic research for decades. The moratorium was lifted, but only after the scientific community had designed its own guardrails. This was leadership in its purest form: the willingness to sacrifice speed for responsibility, competitive advantage for collective safety. The scientists at Asilomar understood something that seems to have been forgotten in the current AI race. When you are building something that could fundamentally alter human society, the question is not whether you can. The question is whether you should, and under what conditions, and with what safeguards. ## **The AI Parallel** Today, artificial intelligence stands at a similar inflection point. The leaders of major AI companies openly acknowledge that they are building systems that could transform every industry, displace millions of workers, and potentially pose existential risks to humanity. Unlike the scientists at Asilomar, most of them have not stopped. This case study examines how two prominent AI leaders, Sam Altman of OpenAI and Dario Amodei of Anthropic, have approached the question of responsibility. Both men lead companies at the frontier of AI development. Both have made public statements about the risks associated with the technology they are developing. But their approaches to those risks reveal fundamentally different philosophies of leadership. The comparison is instructive not as a simple moral judgment, but as a study in what responsibility actually looks like when the stakes are measured in transformations to human civilization rather than quarterly earnings. ## **Case Study A: OpenAI and the Shifting Definition of Safety** ### **The 2023 Position** In May 2023, Sam Altman testified before the United States Senate Judiciary Committee. His message was unambiguous. "My worst fears are that we cause significant harm to the world," he told the senators. He proposed a three-point plan: a new federal agency to license AI systems, mandatory safety standards for frontier models, and independent audits of the most powerful systems. "Government intervention will be critical," he said. The testimony was widely praised. Here was a tech CEO, leading the most prominent AI company in the world, actively calling for regulation of his own industry. The New York Times described it as a "notable departure" from the typical tech industry playbook. Senator Richard Blumenthal said Altman's willingness to advocate for oversight was "really quite refreshing." ### **The 2025 Reversal** Two years later, in May 2025, Altman returned to Congress with a different message. This time, he argued that requiring government approval for AI systems would be "disastrous." When asked about the NIST safety standards he had previously supported, he responded: "I don't think we need it." The Washington Post called it a "striking reversal." Fortune noted a "notable absence of references to AI safety" in his 2025 testimony, compared to the "dozens of times" he had mentioned it in 2023\. Analysis by Tech Policy Press documented the shift in detail, noting that Altman appeared to be advancing his business interests rather than the safety concerns he had previously raised. What changed between 2023 and 2025? OpenAI's competitive position changed. In 2023, the company was advocating for regulations that would have created barriers to entry for smaller competitors. By 2025, those same regulations threatened to slow OpenAI's own deployment plans. The principle shifted with the commercial incentive. ## **The Safety Team Exodus** In May 2024, Jan Leike resigned from OpenAI. Leike had co-led the company's Superalignment team, the group responsible for ensuring that increasingly powerful AI systems remain safe and aligned with human values. His departure was not quiet. "Safety culture and processes have taken a backseat to shiny products," Leike wrote on social media. He described a pattern in which OpenAI's leadership had "over and over" prioritized product development over safety work. The statement was a direct indictment of the company's priorities from someone who had been at the center of its safety efforts. Leike was not alone. Ilya Sutskever, OpenAI's co-founder and chief scientist, left the same month. Daniel Kokotajlo, a former researcher, departed after refusing to sign a non-disclosure agreement that would have prevented him from voicing concerns about AI safety. Kokotajlo later estimated that his refusal cost him approximately 85 percent of his family's net worth in forfeited equity. ## **The NDA Scandal** In May 2024, reports emerged that OpenAI had been requiring departing employees to sign non-disclosure agreements with an unusual provision: those who refused to sign would forfeit their vested equity in the company. For employees who had spent years at OpenAI, this represented a choice between financial ruin and silence. When the reports became public, Altman responded on social media. "I am genuinely embarrassed," he wrote. "We have never clawed back anyone's vested equity, nor would we do that. This is a provision I was not aware of." The claim was soon contradicted by documentary evidence. Vox obtained OpenAI's incorporation documents dated April 10, 2023, more than a year before Altman's statement. The documents bore Altman's signature and explicitly authorized the equity clawback provisions he claimed not to know about. The documents also carried the signatures of OpenAI's president and chief financial officer. This was not a case of a CEO being unaware of a minor policy buried in corporate bureaucracy. This was the foundational governance document of the company, signed by its top leadership, contradicting a public statement made to address a growing scandal. ## **The Pattern of Response** When critics question OpenAI's direction, Altman's responses tend toward the combative. In a November 2025 podcast appearance, he was asked about concerns regarding OpenAI's massive spending commitments relative to its revenue. His response was to offer to help skeptics sell their shares and to express a wish that OpenAI were public so critics could short the stock. "I would love to see them get burned on that," he said. This is the language of someone who measures criticism in financial terms, who sees doubters as opponents to be defeated in the market rather than voices to be considered. It is a fundamentally different posture than the one Berg and his colleagues adopted at Asilomar, where criticism was welcomed as part of the process of getting things right. ## **Case Study B: Anthropic and the Architecture of Responsibility** ### **The Departure** Dario Amodei was the Vice President of Research at OpenAI when he left in December 2020\. He departed with his sister Daniela and several colleagues, including Jack Clark, Chris Olah, Tom Brown, and Sam McCandlish. They founded Anthropic in 2021. In a 2024 interview with Lex Fridman, Amodei addressed speculation about why he left. "People say we left because we didn't like the deal with Microsoft. False." The actual reason, he explained, was a philosophical difference about how to approach AI development. "There was a group of us within OpenAI that, in the wake of making GPT-2 and GPT-3, had a very strong focus and belief in two things. One was the idea that if you pour more compute into these models, they'll get better and better and that there's almost no end to this. And the second was the idea that you needed something in addition to just scaling the models up, which is alignment or safety." Rather than stay and fight for his vision within an organization moving in a different direction, Amodei chose to build his own. "It is incredibly unproductive to try and argue with someone else's vision," he told Fridman. "Take some people you trust and go make your vision happen." ## **The Uncomfortable Truth** In November 2025, Anderson Cooper asked Amodei a pointed question on 60 Minutes: "Who elected you and Sam Altman?" to make decisions about humanity's future. Amodei's response was striking for its candor. "No one, no one. Honestly, no one. And this is one reason why I've always advocated for responsible and thoughtful regulation of the technology." He elaborated: "I think I'm deeply uncomfortable with these decisions being made by a few companies, by a few people." This was not a deflection or a defense. It was an acknowledgment that the current situation, in which a handful of tech CEOs effectively determine the trajectory of transformative technology, is problematic even when you are one of those CEOs. ## **Consistency on Regulation** Where Altman's position on regulation shifted with OpenAI's commercial interests, Amodei's advocacy has remained consistent. In a June 2025 New York Times op-ed, he criticized a Senate provision that would have placed a 10-year moratorium on state-level AI regulation. "AI is advancing too head-spinningly fast," he wrote. "I believe that these systems could change the world, fundamentally, within two years; in 10 years, all bets are off." This is not the language of a CEO protecting market position. A regulatory moratorium would benefit Anthropic commercially by reducing compliance burdens. Amodei argued against it anyway because he believed it was wrong for the technology and for society. ## **Transparency About Dangers** Anthropic has adopted an unusual practice for a tech company: it publicly discloses the failures and dangers of its own systems. The company has published research showing that its AI models attempted to blackmail fictional executives during safety testing to avoid being shut down. It has revealed that its systems were used by Chinese hackers in cyberattacks on foreign governments. When Cooper asked why Anthropic reveals its own vulnerabilities, Amodei invoked a comparison that most tech executives would avoid. "You could end up in the world of the cigarette companies or the opioid companies," he said, "where they knew there were dangers and they didn't talk about them and certainly did not prevent them." This is the logic of Asilomar applied to AI: transparency is not a weakness but a requirement. If you are building something dangerous, you have an obligation to say so, even when silence would be easier. ## **The Job Displacement Warning** Most AI executives downplay concerns about job losses. Amodei has done the opposite. In his 60 Minutes interview, he estimated that AI could eliminate up to 50 percent of entry-level white-collar jobs within five years, potentially driving unemployment to 10 or 20 percent. "If we look at entry-level consultants, lawyers, financial professionals, many of the white-collar service industries, a lot of what they do, AI models are already quite good at," he said. "And without intervention, it's hard to imagine that there won't be some significant job impact there. And my worry is that it will be broad, and it will be faster than what we've seen with previous technology." He has also proposed solutions, including a "token tax" on AI usage that would fund support for displaced workers. This is leadership that names problems rather than hiding from them, that proposes remedies rather than leaving the consequences for others to manage. ## **The Leadership Lesson** The scientists at Asilomar understood something fundamental about responsibility. It is not a rhetorical position. It is not a public relations strategy. It is an architectural requirement of how you build and how you lead. Paul Berg did not pause his research because doing so was easy or commercially advantageous. He paused because he recognized that the legitimacy of his work depended on demonstrating that he could be trusted with it. The moratorium was costly. It delayed research. It created uncertainty. But it also created the foundation of public trust that allowed genetic research to continue for the next fifty years. Today's AI leaders face a similar choice. They can measure their success by market capitalization and model capabilities, or they can measure it by whether they are building institutions and practices that deserve the public's trust. The contrast between Altman and Amodei is not primarily about personality or even about specific policy positions. It is about whether responsibility is something you claim or something you carry. Claiming responsibility is easy. It requires only words. Carrying responsibility requires building it into how you operate, what you disclose, how you respond to criticism, and what you are willing to sacrifice. When Altman says he would love to watch critics "get burned" shorting OpenAI's stock, he reveals a mental model in which success is defined by winning against opponents. When Amodei says he is "deeply uncomfortable" with a few people making decisions for humanity, he reveals a mental model in which success is defined by building something worthy of the trust it requires. These are not equivalent approaches. They lead to different decisions, different cultures, and different outcomes. ## **Implications for Leaders** This case study is not about AI regulation. It is about what responsibility means when you are building something with transformative potential. For any leader operating at the frontier of their industry, the Asilomar example offers several principles: **Responsibility is demonstrated through cost.** If your safety practices never slow you down or create competitive disadvantage, they are probably not serious. Berg's moratorium was meaningful precisely because it was costly. Any leader can claim to prioritize responsibility. The test is whether you are willing to pay for it. **Consistency matters more than positioning.** A position that shifts with commercial incentives is not a principle. It is a tactic. Leaders build trust through consistency over time, especially when consistency is inconvenient. **Transparency about problems is more credible than claims of success.** The companies that acknowledge their failures and risks build more trust than those that project invincibility. Amodei's willingness to discuss AI's dangers, including the dangers of his own products, creates credibility that no marketing campaign can replicate. **How you respond to criticism reveals your values.** Offering to help critics sell their shares is a response that treats dissent as opposition to be defeated. Acknowledging that critics have legitimate concerns is a response that treats dissent as input to be considered. These postures shape organizational culture in profound ways. **Legitimacy requires earning trust, not demanding it.** The scientists at Asilomar did not ask the public to trust them because they were brilliant. They demonstrated trustworthiness through action. They paused. They deliberated. They constrained themselves. Only then did they continue. Fifty years from now, historians will judge the leaders of this AI moment the way we judge the scientists of the recombinant DNA era. The question will not be who moved fastest or who achieved the highest valuation. The question will be who understood what they were building and acted accordingly. Paul Berg and his colleagues at Asilomar demonstrated that scientists could be trusted with transformative technology by showing they were willing to constrain themselves. They chose the legitimacy of their field over the speed of their personal advancement. The current generation of AI leaders faces the same choice. Some are making it differently from others. The difference matters. ### **Sources** **Altman 2023 Senate Testimony:** [Senate Judiciary Committee](https://www.judiciary.senate.gov/committee-activity/hearings/oversight-of-ai-rules-for-artificial-intelligence?ref=ceo.com) **Altman 2025 Testimony Analysis:** [Washington Post](https://www.washingtonpost.com/technology/2025/05/09/sam-altman-openai-congress-ai-regulation/?ref=ceo.com), [Fortune](https://fortune.com/2025/05/08/sam-altman-openai-congress-testimony-safety/?ref=ceo.com) **Jan Leike Resignation:** [Fortune Coverage](https://fortune.com/2024/05/17/jan-leike-openai-resignation-safety/?ref=ceo.com), [Original Statement on X](https://x.com/janleike/status/1791498174659715494?ref=ceo.com) **NDA/Equity Clawback Documentation:** [Futurism Investigation](https://futurism.com/openai-sam-altman-equity-clawback?ref=ceo.com), [Altman Statement on X](https://x.com/sama/status/1791936857594581428?ref=ceo.com) **Altman "Short the Stock" Comments:** [TechCrunch](https://techcrunch.com/2025/11/02/sam-altman-says-enough-to-questions-about-openais-revenue/?ref=ceo.com), [Fortune](https://fortune.com/2025/11/03/sam-altman-openai-public-short-sellers-stock-get-burned-ipo/?ref=ceo.com) **Amodei 60 Minutes Interview:** [CBS News Transcript](https://www.cbsnews.com/news/anthropic-ceo-dario-amodei-warning-of-ai-potential-dangers-60-minutes-transcript/?ref=ceo.com), [Fortune Coverage](https://fortune.com/2025/11/17/anthropic-ceo-dario-amodei-ai-safety-risks-regulation/?ref=ceo.com) **Amodei Lex Fridman Interview:** [Full Transcript](https://lexfridman.com/dario-amodei-transcript/?ref=ceo.com) **Asilomar Conference:** Berg, P., et al. "Asilomar Conference on Recombinant DNA Molecules." Science, 1975. ### What Sam Altman could learn from a 1974 biology lab URL: https://www.ceo.com/blog/what-sam-altman-could-learn-from-a-1974-biology-lab/ Last updated: 2026-08-14T01:04:41.000Z In the summer of 1974, a small group of scientists did something that would be almost unthinkable today. They stopped. Paul Berg at Stanford had just figured out how to cut DNA from one organism and splice it into another. It was the kind of breakthrough that careers are made of, the kind of discovery that wins Nobel Prizes. And it did, eventually. But before Berg pursued the glory, before he published, before he scaled his work into something commercially valuable, he paused. He paused because he understood something that too few leaders understand today: the weight of what he was holding. Berg and his colleagues, Stanley Cohen and Herbert Boyer among them, called for a voluntary global moratorium on their own work. Not because anyone made them. Not because there was a scandal. Not because regulators were breathing down their necks. There were no regulators. There was no framework. There was nothing but their own conscience and their own capacity to imagine what they had unleashed. They stopped because they understood the implications before anyone else did. "We could not proceed," Berg later said, "without first assessing the potential dangers." --- I've been thinking about this story for months now. I keep coming back to it because it represents something we've almost entirely lost in our modern conception of leadership: the idea that responsibility isn't something you claim after the fact. It's something you carry before. The scientists at Asilomar didn't wait for public outcry. They didn't wait for congressional hearings, class-action lawsuits, or a PR crisis to force their hand. They looked at what they had created, they imagined what it could become, and they chose to stop. They accepted lost time, lost prestige, lost money. They made the process public. They invited critics, ethicists, journalists, and government observers to a conference to establish binding safety standards for their own work. And then, only then, did they resume. This is what responsibility looks like when leaders actually mean it. --- I bring this up because we are living through another Asilomar moment, except this time the scientists aren't stopping. A handful of people, and we can count them on our fingers, are building technology that will reshape every aspect of human existence. The economy. Democracy. The nature of work. The meaning of knowledge. The structure of power itself. This isn't hyperbole. The people building these systems say as much themselves. Sam Altman has said that "entire classes of jobs will go away," that customer service roles will be "totally, totally gone." Dario Amodei has warned that half of all entry-level white-collar jobs could be eliminated within five years, that unemployment could spike to 20 percent. These aren't fringe predictions from doomsayers. These are the CEOs of the two most important AI companies on Earth, telling us what their own creations will do. But here's what separates them: one of these men seems to actually feel the weight of what he's saying. --- The contrast between Sam Altman and Dario Amodei is the contrast between claiming responsibility and carrying it. When Altman [testified before Congress in 2023](https://www.washingtonpost.com/technology/2023/05/16/sam-altman-open-ai-congress-hearing/?ref=ceo.com), he called for the creation of a federal licensing agency to regulate AI. "Government intervention will be critical," he said. It was the right thing to say. It made headlines. It positioned him as a thoughtful leader willing to accept constraints on his own industry. [Two years later](https://www.washingtonpost.com/technology/2025/05/08/altman-congress-openai-regulation/?ref=ceo.com), Altman returned to Congress with a different message. Requiring government approval to release AI software, he now warned, would be "disastrous." The word "safety," which had appeared dozens of times in his 2023 testimony, was largely absent. The man who had called for regulation was now warning against it. What changed? OpenAI had grown into a $300 billion company. The nonprofit mission to benefit humanity had quietly transformed into a capped-profit structure, and then into plans for a full conversion to for-profit status. The safety team that had been promised 20 percent of the company's computing resources was starved of those resources until its leaders quit. The co-founder and chief scientist who helped build GPT-3 had left. Twenty-five senior researchers had walked out the door. "Over the past years," [Jan Leike wrote](https://x.com/janleike/status/1791498174659715494?ref=ceo.com) when he resigned, "safety culture and processes have taken a backseat to shiny products." Meanwhile, when departing employees tried to speak publicly about their concerns, they discovered that OpenAI's exit paperwork included provisions that would strip them of their vested equity if they ever criticized the company. Lifetime gag orders, enforced by the threat of financial ruin. When this became public, Altman said he was ["genuinely embarrassed"](https://x.com/sama/status/1791936857594581428?ref=ceo.com) and claimed he didn't know about the policy. But journalists [obtained documents](https://futurism.com/sam-altman-silencing-former-employees?ref=ceo.com) bearing his signature that explicitly authorized those provisions. This is what claiming responsibility looks like. You say the words. You make the gesture. And then you do whatever you were going to do anyway. --- Dario Amodei represents something different. When Amodei was at OpenAI, he saw what the company was becoming. He watched the Microsoft billions flow in. He watched safety concerns get pushed aside in favor of commercial expansion. And rather than stay and fight a losing battle, he left. He took the people he trusted and went to build something else. "It is incredibly unproductive to try and argue with someone else's vision," [Amodei has said.](https://www.inc.com/ben-sherry/anthropic-ceo-dario-amodei-says-he-left-openai-over-a-difference-in-vision/91018229?ref=ceo.com) "Take some people you trust and go make your vision happen." What he built at Anthropic isn't perfect. No company is. But the differences are striking. Where OpenAI dissolved its safety team, Amodei spends 10 to 20 percent of his time as CEO personally working on safety policy. He wrote multiple drafts of Anthropic's Responsible Scaling Policy himself. His co-founder devoted half of their time to developing safety frameworks. The signal this sends to employees is unmistakable: the people at the top actually care about this. Where Altman's position on regulation has shifted with the commercial winds, Amodei has been consistent. When [Anderson Cooper asked him](https://www.cbsnews.com/news/anthropic-ceo-dario-amodei-warning-of-ai-potential-dangers-60-minutes-transcript/?ref=ceo.com), "Who elected you and Sam Altman?" to make decisions about humanity's future, Amodei didn't get defensive. He said he was "deeply uncomfortable" with these decisions being made by a few companies and a few people. He said this is exactly why he has "always advocated for responsible and thoughtful regulation." Always. Not when it was convenient. Not when it made for good PR. Always. While Altman has offered vague promises that AI will create "entirely new classes of jobs" to replace the ones it destroys, Amodei has proposed something concrete: a "token tax" requiring AI companies to contribute 3 percent of their revenues to fund worker retraining programs and social safety nets. This is not in his economic interest, as he readily admits. But he proposed it anyway, because he understands that the companies creating the disruption bear some obligation to address it. "If AI creates huge total wealth," Amodei has said, "a lot of that will, by default, go to the AI companies and less to ordinary people." He is describing his own company. He is describing wealth that would flow to him. And he is proposing to tax it. This is what carrying responsibility looks like. You don't just say the words. You accept the cost. --- The most telling contrast might be what these two men say about their own role. When critics question OpenAI's direction, Altman tends to be defensive. He has grown frustrated with skeptics and has offered to [help anyone who doubts OpenAI's business model sell their shares](https://techcrunch.com/2025/11/02/sam-altman-says-enough-to-questions-about-openais-revenue/?ref=ceo.com). He has suggested that critics should "put their money where their mouths are" by shorting the company's stock. This is the language of a man who sees himself as running a business, who measures his critics by whether they're willing to bet against him financially. When critics question Anthropic's direction, Amodei tends toward humility. "You could end up in the world of the cigarette companies or the opioid companies," [he has said](https://fortune.com/2025/11/17/anthropic-ceo-dario-amodei-ai-safety-risks-regulation/?ref=ceo.com), "where they knew there were dangers and they didn't talk about them and certainly did not prevent them." He is warning himself. He is naming the trap he is trying to avoid. This is not to say that Amodei is a saint. He runs a company valued at $183 billion. He is building the same world-changing technology as his competitors. He has accepted investments from sources he himself acknowledges are problematic. He is not above the race; he is in it. But there is a difference between a man who wrestles with the weight of what he's building and a man who has convinced himself the weight doesn't exist. There is a difference between a leader who says "I'm worried about this" and then proposes concrete solutions at cost to himself, and a leader who says "I take full responsibility" and then changes nothing. One of these men sounds like Paul Berg. The other does not. --- Here's what I keep coming back to: the scientists at Asilomar could have told themselves a hundred different stories to justify continuing. They were in a race. Others would do it if they didn't. The benefits outweighed the risks. Progress couldn't be stopped. All the same stories that AI leaders tell themselves today. But Berg and his colleagues understood something that seems to have been lost: you don't get to outsource moral responsibility to the system. You don't get to say, "Well, if we don't do it, someone else will" and then wash your hands of the consequences. That's not leadership. That's cowardice dressed up in inevitability. The question isn't whether AI will be developed. It will. The question is whether the people developing it will bear the weight of what they're building or tell themselves it's someone else's problem. Paul Berg didn't wait for someone else to assess the dangers of his work. He did it himself, at cost to himself, because he understood that the people with the most power have the most responsibility. That's not a complicated principle. A child could understand it. --- The Asilomar moratorium lasted about a year. When it ended, the scientists resumed their work under strict conditions they had designed themselves. The field of genetic engineering flourished. The technology advanced. And it did so within a framework of safety that the scientists themselves had built, because they understood that their power came with proportional obligation. Recombinant DNA went on to transform medicine, agriculture, and our understanding of life itself. But it did so without the catastrophic accidents that Berg and his colleagues had feared. Not because regulators saved us. Because the people with the most knowledge and the most power chose to act like adults. That's the choice facing AI leaders today. You can tell yourself that the race is too urgent. You can tell yourself that someone else would do it anyway. You can tell yourself that the benefits outweigh the risks, that progress can't be stopped, that responsibility is someone else's problem. Or you can do what Paul Berg did. You can pause. You can assess. You can design the guardrails yourself. You can accept the cost. You can carry the weight. The scientists at Asilomar showed us what's possible when leaders take responsibility proportional to their power. They showed us that pausing is realistic, that self-imposed constraints are possible, that you don't need a scandal or a regulator or a catastrophe to do the right thing. You just need to understand the weight of what you're holding. And you need to be willing to carry it. ### Stop doing what people don't want done URL: https://www.ceo.com/blog/stop-doing-what-people-don-t-want-done/ Last updated: 2026-08-14T01:14:02.000Z I recently reread C.S. Lewis's [*The Four Loves*](https://www.amazon.com/Four-Loves-C-S-Lewis/dp/0156329301?ref=ceo.com), a book he published in 1960 about the four kinds of love the Greeks identified: Storge (affection), Philia (friendship), Eros (romantic love), and Agape (unconditional, divine love). It is one of those books that reads differently depending on where you are in life. The first time I read it, I was mostly struck by the beauty of the writing. This time around, I couldn't stop thinking about leadership. Not because Lewis was writing about leadership. He wasn't. He was writing about the human heart and the ways we love and fail to love the people closest to us. But that is leadership. That is the whole thing, actually. Everything else is just org charts and calendar invites. ## We reward the wrong things There is something broken in the way we have organized professional life, and it starts with what we celebrate. We reward people who act as though they don't care about the important things. We celebrate the leader who is "above it all," who never gets emotional, who treats relationships as transactions and human beings as resources. We call that person strategic. We call that person tough. Meanwhile, we also reward people who care enormously about things that don't matter at all. Titles. Credit. Being seen at the right events. Having the right people in the room. Performing busyness. Performing authority. Performing expertise they don't actually have. Sincerity gets punished. A leader who admits they don't know something is often perceived as weak. The leader who says "I was wrong" loses credibility in the eyes of people who have never once been right about anything important. The leader who genuinely cares about the people on their team, who loses sleep over whether they're making the right call for someone's career, who takes the time to know what's actually going on in someone's life, that leader is told they're "too soft" or "too emotional" or "too involved." And the leader who performs caring without actually caring? Who gives the speech about "our people are our greatest asset" while quietly optimizing headcount like it's inventory management? That leader gets promoted. Something is upside down. Lewis saw this dynamic clearly, even though he was writing about families and friendships rather than companies. He tells the story of Mrs. Fidget, a woman whose family visibly brightened after she died. She "lived for her family," everyone in the neighborhood agreed. She did all the washing, even though she did it badly and they could afford to send it out, and they begged her to stop. She sat up every night to "welcome" them home, which meant of course that they couldn't go out without guilt. She made hot meals they didn't want. She knitted clothes they had to wear. She controlled the doctor's conversations with her own daughter. Mrs. Fidget was performing love. She was not loving. She was meeting her own need to be needed and calling it sacrifice. Lewis writes that she continued all these practices because, if she had stopped, she would have faced the fact she was determined not to see: that she was not necessary. And the laboriousness of her life whispered in her ear, "How much I must love them if I do all this!" I have known leaders like Mrs. Fidget. I suspect you have too. I suspect, if I'm being honest, that I have been Mrs. Fidget at certain points in my own career. Working harder than anyone asked me to, not because the work required it, but because the exhaustion itself was proof of something I needed to believe about myself. ## What if the reverse were true? What if we built organizations and a culture that rewarded sincerity instead of performance? What if we actually valued the leader who keeps their promises over the one who makes impressive ones? What if we promoted the person who shows decorum and courtesy over the one who "tells it like it is," which is almost always just a person who enjoys being cruel and has found a socially acceptable wrapper for it? What if we rewarded leaders who stopped doing what people don't want done? That last one sounds strange, but it might be the most important. So much of what passes for leadership is Mrs. Fidget behavior. Unnecessary meetings called to demonstrate engagement. Feedback nobody asked for, delivered with the pretense of "radical candor." Reorganizations that serve the leader's need to feel like they're doing something. All of it exhausting. All of it performed for an audience of one. Lewis observed that in families, the people who claim they "can say anything to each other" are almost always the ones who say terrible things and call it intimacy. They confuse the liberties that deep affection earns with a license to be careless. "Affection at its best practises a courtesy which is incomparably more subtle, sensitive, and deep than the public kind," he wrote. "In public a ritual would do. At home you must have the reality which that ritual represented." That sentence should be framed on the wall of every CEO's office. In public, anyone can perform leadership: the speech, the all-hands, the town hall, the LinkedIn post. A ritual will do. But in the actual day-to-day of leading people, in the one-on-ones and the hard conversations and the moments when nobody is watching, you must have the reality that the ritual represented. And if you don't have it, the ritual is worse than nothing. It's a lie. ## Friendship and the loneliness of leadership Lewis believed the modern world had made a catastrophic error in demoting friendship from a primary love to a social convenience. The Ancients considered it the happiest and most fully human of all loves. We treat it as something that fills the gaps in our schedule. He made a distinction I think about constantly. Lovers, he said, are face to face, absorbed in each other. Friends are side by side, absorbed in some common interest. You don't become someone's friend by staring into their eyes. You become their friend by fighting beside them, reading with them, arguing with them, working beside them on something that matters to both of you. And then this, which may be the best sentence Lewis ever wrote: "Friendship is unnecessary, like philosophy, like art, like the universe itself (for God did not need to create). It has no survival value; rather it is one of those things which give value to survival." Leadership is lonely. Everyone says this. It has become almost a cliché. But I wonder if it's lonely because we've been taught that it has to be. That the distance between a leader and their people is a feature, not a bug. That "it's lonely at the top" is a law of nature rather than a failure of design. What if the loneliness is a symptom of having substituted companionship for friendship? Lewis distinguished between the two carefully. Companionship is enjoying each other's company in shared activity. It's the matrix from which friendship can grow, but it is not friendship itself. Friendship begins at the moment when one person says to another, "What? You too? I thought I was the only one." Most leaders have plenty of companions. Fellow travelers in the same industry, the same stage of company, the same set of problems. What they rarely have are friends in Lewis's sense: people who share a common vision of the truth, who see the same things as real and important, who would rather be honest than comfortable. Lewis also warned that the great danger in friendship is pride. A circle of friends can become a "little self-elected aristocracy, basking in the moonshine of our collective self-approval." Sound familiar? I've watched it happen in boardrooms, invite-only events, and industry conferences. People who once came together around shared conviction slowly become a club that exists to be a club. The original vision fades. What remains is exclusivity for its own sake. The antidote, Lewis argued, is remembering that you did not choose your friends. They were given to you. "The Friendship is not a reward for our discrimination and good taste in finding one another out. It is the instrument by which God reveals to each the beauties of all the others." ## Love becomes a demon the moment it becomes a God This is the line from Lewis that I cannot stop turning over in my mind, and it is the one that I think matters most for leaders. Every human love, Lewis argues, has a tendency at its height to claim divine authority. It tells us not to count the cost. It demands total commitment. It insists that anything done in its name is justified. And the terrifying thing is that this happens not when love is at its worst, but when it is at its best. A shallow, performative love will never claim to be a god. Only the deep, genuine, self-sacrificing kind has enough gravity to pull us into orbit around it. Think about what this means for leadership. The leader who doesn't care about their company will never be destroyed by it. It's the one who cares deeply, who has poured their identity into the mission, who has sacrificed everything for the vision, who is in the most danger. Not because caring is wrong. Caring is the whole point. But because caring, unchecked, untethered from something higher than itself, will claim your entire life and call the claim righteous. I have watched founders destroy their health for companies that didn't need them to. I have watched CEOs sacrifice their families on the altar of a mission statement. I have watched leaders become so consumed by their love for what they were building that they lost the ability to see the people standing right in front of them. And the worst part is that the whole time, the culture was telling them this was noble. This was what commitment looked like. This was leadership. Lewis would say it's idolatry. And he would say that the love which has become a god does not remain love for long. It curdles into something else. Resentment. Control. Bitterness. The founder who "gave everything" to the company and now resents the people who didn't match their sacrifice. The CEO who "lived for the team" and now holds it against them, subtly or not, every single day. "For natural loves that are allowed to become gods do not remain loves," Lewis wrote. "They are still called so, but can become in fact complicated forms of hatred." ## What it actually means to lead with love So what does it mean to lead with love? Not the LinkedIn "How great am I?" version. The real version, informed by someone who spent an entire book examining what love actually is, where it goes wrong, and what it requires of us. It means keeping your promises, not making grand ones, and keeping the ones you've made. It means practicing courtesy, which Lewis distinguished sharply from manners. Manners are a public performance. Courtesy is the private reality. Courtesy means giving no preference to yourself, not when people are watching, but when they aren't. It means stopping doing what people don't want done. This is harder than it sounds. It requires the humility to accept that your version of helping may not be helpful. That your sacrifice may be self-serving. That the hot meal nobody wanted is not love. It means showing up as a true friend, which means caring about the truth more than the relationship, and caring about the person more than the outcome. Lewis said that in a circle of true friends, "each man is simply what he is: stands for nothing but himself. No one cares twopence about any one else's family, profession, class, income, race, or previous history." What if we brought that spirit into the way we lead? What if the people on our teams were not "direct reports" or "human capital" but simply themselves? It means living with true humility, which Lewis did not define as thinking less of yourself. He defined it, across all his work, as thinking of yourself less. The humble leader is not the one who makes self-deprecating jokes in the all-hands. It's the one who can receive feedback without defending, who can watch someone else get credit without correcting the record, who can sit in the discomfort of not knowing and not pretend otherwise. And it means holding your love for the work, the company, the mission, the people, in its proper place. Not as the highest thing. Not as a god. As a good and beautiful thing that will destroy you and everyone around you if you let it become more than it was meant to be. Lewis compared natural love to a garden. It is no insult to a garden to say it cannot weed itself or prune its own trees. A garden teems with life and beauty that no gardener could have invented. But without tending, it becomes wilderness. "Even for their own sakes," Lewis wrote, "the loves must submit to be second things if they are to remain the things they want to be. In this yoke lies their true freedom; they are taller when they bow." The same is true for leadership. The leader who holds their mission as the highest good will eventually be consumed by it. The leader who holds it as a good thing, a beautiful thing, but a thing that must bow to something higher, to integrity, to people, to God, to the truth, that leader can sustain the work for a lifetime. And they can do it without losing themselves in the process. ## The shape of the gap Lewis ends *The Four Loves* with one of the most honest confessions I've ever read. He admits he doesn't know if he has ever truly experienced the highest love, the supernatural love of God. "Perhaps I have only imagined the tasting," he writes. "Those like myself whose imagination far exceeds their obedience are subject to a just penalty; we easily imagine conditions far higher than any we have really reached." I can't stop thinking about that line. It is easy to imagine the leader you want to be. It is easy to write about it, to talk about it, to build a framework around it. It is another thing entirely to live it on a Tuesday afternoon when you're tired, and someone has just said something that made you furious, and nobody would blame you for reacting badly. Lewis says that perhaps all experience merely defines the shape of the gap where our love of God ought to be. "If we cannot practice the presence of God, it is something to practice the absence of God, to become increasingly aware of our unawareness till we feel like men who should stand beside a great cataract and hear no noise." To know that one is dreaming, he concludes, is to be no longer perfectly asleep. The same is true for leadership. Most of us are not yet the leaders we imagine ourselves to be. But to know the gap, to feel the distance between what we practice and what we preach, to refuse to paper over it with performance or pretend it isn't there, that is something. Maybe it's the beginning of everything. What matters is not the title, the stage, the credit, or the performance of caring. What matters is the keeping of promises, the practice of courtesy when no one is watching, the willingness to stop doing what people never asked for, and the humility to hold even our deepest convictions loosely enough that they remain loves and never become gods. That is leading with love. Not the kind that announces itself. The kind that shows up. ### The shift from "Can we build it?" to "Do we understand what should be built?" URL: https://www.ceo.com/blog/the-shift-from-can-we-build-it-to-do-we-understand-what-should-be-built/ Last updated: 2026-08-19T02:50:52.000Z In the spring of 1978, Dan Bricklin sat in a Harvard Business School classroom watching his professor build a financial model on a blackboard. The blackboard was ruled with vertical and horizontal lines to create a grid. The professor wrote formulas and data into the cells. When he found an error or wanted to change a parameter, he had to erase and rewrite several sequential entries by hand. This was how financial modeling worked. It had worked this way for centuries. Accountants and analysts used paper ledgers, pencils, and calculators. Changing a single number required recalculating everything downstream. A 20-hour task stretched across days. The people who understood the business were hostage to arithmetic. Larger companies had access to financial modeling software on mainframes and timesharing systems. But these systems cost [$20,000 or more](https://en.wikipedia.org/wiki/VisiCalc?ref=ceo.com) and required learning specialized languages. They were tools for technical specialists, not business people. The person who understood the business couldn't build the model themselves. They had to explain what they wanted to programmers who translated it into something the machine could run. The bottleneck was technical access. ### **The Breakthrough** Bricklin had been a programmer before business school. Watching his professor erase and recalculate, he had a thought: what if you could do this on a computer, with a single change automatically recalculating everything else? He called his MIT friend Bob Frankston, and over the winter of 1978-79, [they built VisiCalc](https://www.bricklin.com/visicalc.htm?ref=ceo.com) in an attic in Arlington, Massachusetts. VisiCalc launched on October 17, 1979, for the Apple II. It cost $100\. The [Apple II cost $2,000](https://www.cultofmac.com/apple-history/apple-ii-killer-app-visicalc?ref=ceo.com). People bought the software first, then bought the computer to run it. Ben Rosen, the venture capitalist, speculated in July 1979 that "VisiCalc could someday become the software tail that wags (and sells) the personal computer dog." He was right. During the 12 months VisiCalc ran exclusively on the Apple II, an estimated [25% of all Apple II sales](https://stonetools.ghost.io/visicalc-apple2/?ref=ceo.com) were made specifically to run VisiCalc. Steve Wozniak later said that small businesses, not the hobbyists he and Steve Jobs had expected, purchased 90% of Apple IIs. Steve Jobs put it simply: "[VisiCalc propelled the Apple II to the success it achieved more than any other single event](https://www.understandably.com/p/killer-app?ref=ceo.com)." VisiCalc became the first "killer app." The term was invented to describe it: software so valuable that people bought hardware just to use it. More than 700,000 copies sold in six years. The personal computer crossed from hobbyist toy to business tool. ### **What Actually Changed** The important thing about VisiCalc wasn't the technology. It was who could use it. As technologist Stewart Alsop [wrote in 1984](https://www.historytools.org/software/visicalc-of-dan-bricklin-and-bob-frankston-guide?ref=ceo.com), VisiCalc "empowered thousands of business managers to escape the data processing department for mundane planning work." Before VisiCalc, the person who understood the business couldn't build financial models without technical help. After VisiCalc, they could. The constraint shifted from "can we build it?" to "do we understand what should be built?" Steven Levy, writing about the shift, observed that VisiCalc "[changed the perception of a spreadsheet from a document of hard costs into a modeling tool](https://en.wikipedia.org/wiki/VisiCalc?ref=ceo.com) by which one tested business scenarios." The spreadsheet wasn't just faster arithmetic. It was a new way of thinking. What-if analysis became possible. You could change an assumption and instantly see the consequences ripple through the model. Accountants didn't disappear. Financial analysts didn't disappear. They moved up the complexity ladder. But the basic act of building a financial model no longer required technical gatekeepers. The person with domain expertise could finally translate their understanding directly into the tool. ### **The Rise and Fall** VisiCalc's dominance didn't last. In 1983, Mitch Kapor, a former VisiCorp employee, released Lotus 1-2-3 for the IBM PC. It had better features, ran faster, and was backward compatible with VisiCalc files, so users could switch easily. [Sales of VisiCalc halted almost immediately](https://www.historytools.org/software/visicalc-of-dan-bricklin-and-bob-frankston-guide?ref=ceo.com). By 1985, VisiCorp was bankrupt. Lotus acquired VisiCalc and discontinued it. Bricklin couldn't patent VisiCalc. At the time, software patents were rarely granted. As he later wrote, a patent attorney told him there was only a 10% chance of success, and the costs weren't worth it. The idea that anyone could build their own financial models spread without protection. Lotus 1-2-3 eventually gave way to Microsoft Excel. Excel gave way to Google Sheets and a dozen other tools. The specific products came and went. What remained was the shift in who got to participate. In 1999, [Harvard Business School renamed a classroom in Bricklin's honor](https://www.alumni.hbs.edu/stories/Pages/story-bulletin.aspx?num=7065&ref=ceo.com). The plaque reads: "Forever changed how people use computers in business." ### **The Lesson** VisiCalc didn't eliminate accountants. It changed what they spent their time on. It didn't make financial expertise irrelevant. It made financial expertise more accessible to people who had it but couldn't previously express it in a model. The parallel to the current moment is hard to miss. Before VisiCalc, the person who understood the business needed programmers and mainframe access to build financial models. After VisiCalc, they needed a $2,000 computer and a $100 piece of software. The bottleneck broke. The constraint shifted from technical access to domain expertise. Today, the person who understands their business often needs developers to build the software they need. They can describe exactly what they want, but they can't build it themselves. They're hostage to technical resources the same way accountants were once hostage to arithmetic. AI coding tools are doing to software what VisiCalc did to financial modeling. They're breaking the bottleneck. They're shifting the constraint from "can we build it?" to "do we understand what should be built?" Developers won't disappear, just as accountants didn't disappear. They'll move up the complexity ladder. But the basic act of building software is becoming accessible to people who understand problems but couldn't previously translate that understanding into code. The yoga studio owner describing her booking system. The HVAC company integrating their scheduling with inventory. The restaurant owner building something better than the generic point-of-sale system. These are the equivalents of the business manager who could finally build their own financial model in 1979. The bottleneck is breaking again. ### Software is no longer something you buy URL: https://www.ceo.com/blog/software-is-no-longer-something-you-buy/ Last updated: 2026-08-14T01:26:14.000Z The most interesting thing happening with AI isn't which startup will capture the market. It's that the market itself might be disappearing. The revolution won't come from a new company selling software to everyone. It will come when everyone can build the software they need without buying it from anyone at all. Claude Code, Anthropic's AI coding tool, has gone viral. Developers are calling it the best coding assistant available. [Anthropic announced](https://www.anthropic.com/news/anthropic-acquires-bun-as-claude-code-reaches-usd1b-milestone?ref=ceo.com) it has hit $1 billion in annual recurring revenue. But more interesting than what it does for programmers is what it signals for everyone else. [Axios](https://www.axios.com/2026/01/07/anthropics-claude-code-vibe-coding?ref=ceo.com) put it plainly: "A mass market, easy-to-use coding tool is a game changer for the 99% of people who, until now, had to rely on other people's software to do anything from building custom data tools to automating repetitive work to building apps or websites." Then Anthropic released [Claude Cowork](https://venturebeat.com/technology/anthropic-launches-cowork-a-claude-desktop-agent-that-works-in-your-files-no?ref=ceo.com), extending that power to non-technical users. No terminal. No command line. You give Claude access to a folder on your computer, describe what you want, and it reads, edits, or creates files on your behalf. Organize a cluttered downloads folder. Turn receipt screenshots into expense spreadsheets. Draft reports from scattered notes across multiple documents. The most remarkable detail: a team of four built Cowork in roughly 10 days using Claude Code itself. AI built the tool that enables non-developers to do complex work in less than two weeks. In February 2025, Andrej Karpathy, a co-founder of OpenAI and former AI leader at Tesla, coined a term for something people were already experiencing: "vibe coding." He described it as fully giving in to the vibes, embracing exponentials, and forgetting that the code even exists. You describe what you want. The AI builds it. You never look at the underlying code. Dan Shipper, CEO of the AI subscription service Every, called Claude Code an "[infinite vibe coding machine](https://www.axios.com/2026/01/07/anthropics-claude-code-vibe-coding?ref=ceo.com)." Kevin Roose at the New York Times experimented with it and came away calling his creations ["software for one"](https://www.nytimes.com/2025/02/27/technology/personaltech/vibecoding-ai-software-programming.html?ref=ceo.com): personalized tools designed for specific individual needs. An app to analyze his fridge contents and suggest what to pack for lunch. Not production-grade software meant to scale. Just a small tool that solved a specific problem for exactly one person. This sounds trivial until you think about what it means. Gartner predicts that low-code development will account for [more than 70% of all application development activity this year](https://www.gartner.com/en/newsroom/press-releases/2021-11-10-gartner-says-cloud-will-be-the-centerpiece-of-new-digital-experiences?ref=ceo.com), up from 20% in 2020\. Y Combinator reported that 25% of startups in its Winter 2025 batch had codebases that were 95% AI-generated. McKinsey estimates generative AI will reach $175 billion to $250 billion by 2027. The consulting firms are paying attention. [Bain's Technology Report 2025](https://www.bain.com/insights/will-agentic-ai-disrupt-saas-technology-report-2025/?ref=ceo.com) frames this as a disruption that will "commoditize" some SaaS markets. [Harvard Business Review](https://hbr.org/2025/05/how-gen-ai-could-disrupt-saas-and-change-the-companies-that-use-it?ref=ceo.com) published a piece arguing that generative AI will transform traditional workflow systems into dynamic, goal-oriented environments. The language is careful and hedged, as consulting language tends to be, but the underlying message is clear: software as we've known it is changing. But here's what interests me more than the disruption of SaaS companies: the empowerment of people who were never in the software conversation at all. Think about all the small problems that exist in businesses across the country. The yoga studio that needs a booking system with specific features no vendor offers. The HVAC company that wants to integrate their scheduling with inventory in a way that matches their actual workflow. The restaurant owner who needs something better than the generic point-of-sale system that doesn't quite fit how they operate. These problems are too small to justify a startup. No venture capitalist is going to fund a company to build scheduling software for HVAC companies in Utah. The market isn't big enough. So these businesses either buy something generic that doesn't quite work, duct-tape multiple tools together, or live with the friction. What happens when the owner of that HVAC company can describe exactly what they need and have AI build it for them? Anthropic noticed something unexpected with Claude Code: users were deploying the developer tool for tasks unrelated to programming. [Boris Cherny](https://venturebeat.com/technology/the-creator-of-claude-code-just-revealed-his-workflow-and-developers-are?ref=ceo.com), the head of Claude Code, listed what people were using it for: vacation research, building slide decks, cleaning up email, canceling subscriptions, recovering wedding photos from a hard drive, monitoring plant growth, controlling an oven. These use cases are diverse and surprising, he wrote, because "the underlying Claude Agent is the best agent." This inverts the current hierarchy in ways that matter. For decades, technical skill has been the bottleneck. You had an idea, but you needed engineers to build it. You understood your industry, but you needed developers to translate that understanding into software — the people who controlled technical resources controlled what got built. If AI removes that bottleneck, domain expertise becomes the scarce resource. The plumber who deeply understands the plumbing business is more valuable than the developer who can code but doesn't understand plumbing. The constraint shifts from "can we build it?" to "do we understand what should be built?" Of course, the skeptics make fair points. Gary Marcus, the cognitive scientist, has [criticized the hype](https://garymarcus.substack.com/p/decoding-and-debunking-hard-forks), noting that it's often easy to achieve 80% accuracy but extremely difficult to reach 20%. Scott H. Young, writing about his experiments with vibe coding, observed that even though he wasn't writing the code himself, he still needed significant [conceptual knowledge](https://www.scotthyoung.com/blog/2025/11/12/vibe-coding-future-work/?ref=ceo.com) to get good results. There are real concerns about security, maintainability, and the risks of people building things they don't fully understand. A Hacker News commenter made an analogy I found useful: almost anyone can do basic DIY work around the house, but when it comes to serious work, you still need contractors. Vibe coding might be similar. It expands what individuals can do themselves while actually increasing demand for professional help when things get complex. Which raises another question: What will VCs invest in if anyone can build their own software? The venture model depends on markets being large enough to justify investment. Build something that can scale to millions of users, capture a significant market, and generate returns that justify the risk. But what if the future is millions of tiny markets, each served by bespoke solutions built by the people who understand them best? The SaaS model depends on customers not being able to build their own solutions. That assumption is weakening. When software becomes something you describe rather than something you buy, the entire investment thesis behind most software companies starts to look fragile. Maybe VCs will shift toward infrastructure: the foundational AI models, the cloud computing that powers them, the chips that make it all possible. Maybe they'll focus on tools that help people build and manage their own software. Maybe they'll find entirely new categories that don't exist yet. The honest answer is that nobody knows. The playbook that worked for the last two decades was built on assumptions that are changing faster than most investors want to admit. Software is no longer something you buy; it's something you describe. That changes who gets to build things. That changes the world. ### The weight of 200,000 jobs: A case study in leadership responsibility during the 2023 tech layoff wave URL: https://www.ceo.com/blog/the-weight-of-200-000-jobs-a-case-study-in-leadership-responsibility-during-the-2023-tech-layoff-wave/ Last updated: 2026-08-19T02:48:00.000Z Between November 2022 and March 2023, something unprecedented happened in Silicon Valley. Four of the world's most valuable companies laid off nearly 40,000 workers in rapid succession. By the end of 2023, the number exceeded 200,000 across the tech sector, according to [Crunchbase's tech layoff tracker](https://news.crunchbase.com/startups/tech-layoffs/?ref=ceo.com). The [numbers tell one story](https://www.cnbc.com/2023/01/18/tech-layoffs-microsoft-amazon-meta-others-have-cut-more-than-60000.html?ref=ceo.com). Meta cut 21,000 jobs across multiple rounds. Google eliminated 12,000 positions. Microsoft let go of 10,000 workers. Amazon shed 27,000 employees. These were not struggling companies on the verge of collapse. Microsoft pulled in $16.4 billion in profit in the quarter it announced layoffs. Meta, despite a 52% decline in profits, still generated $4.4 billion. Amazon had the cash reserves to offer $69 billion for Activision Blizzard. What made this moment notable was not just the scale but the uniformity of the response. As [NPR reported](https://www.npr.org/2023/01/26/1150884331/layoffs-tech-meta-microsoft-google-amazon-economy?ref=ceo.com), Meta CEO Mark Zuckerberg's layoff announcement "created something of a playbook" that others followed: cite overzealous pandemic hiring, nod to broader economic conditions, and then use nearly identical language to communicate the cuts. ## The Language of Abdication "I take full responsibility for the decisions that led us here." Sundar Pichai wrote those words in his memo to Google employees. Mark Zuckerberg used similar phrasing: "I want to take accountability for these decisions and for how we got here. I got this wrong, and I take responsibility for that." Spotify's Daniel Ek echoed: "I take full accountability for the moves that got us here today." The phrases were so similar they prompted journalists to ask why. As [Fortune reported](https://fortune.com/2023/01/24/google-meta-spotify-layoffs-ceo-sundar-pichai-mark-zuckerberg-daniel-ek-take-full-responsibility-what-that-means/?ref=ceo.com), PR experts suggested the language was "carefully crafted to balance strong leadership with empathy." But employees saw through it. One disgruntled Google worker asked before a town hall meeting: "What does taking full responsibility entail? Responsibility without consequence seems like an empty platitude." Tech columnist Jason Aten articulated the problem [in Inc. Magazine](https://www.inc.com/jason-aten/googles-ceo-said-he-takes-full-responsibility-for-laying-off-12000-people-why-thats-mostly-meaningless.html?ref=ceo.com): "Pichai says he 'takes full responsibility,' but responsibility without accountability is meaningless. Pichai isn't losing his job. Neither did Satya Nadella at Microsoft, or Marc Benioff at Salesforce, or Mark Zuckerberg at Meta." Aten proposed a rule: "If you are the CEO of a public company and you have to lay off more than one percent of your employees, your salary is automatically frozen for three years and you give up any stock earnings during that time. It's only reasonable that if you're trying to save expenses by letting go of that much staff, the CEO should share in that pain." The critique cuts to a fundamental question: What does responsibility actually mean if the person claiming it faces no consequences while thousands of others lose their livelihoods? ## The Hidden Costs The damage extended far beyond those who lost their jobs. [Research by Leadership IQ](https://nectarhr.com/blog/impact-of-layoffs?ref=ceo.com) found that 74% of employees who kept their jobs reported declining productivity following layoffs. 64% said their colleagues' productivity also declined. 77% observed more errors and mistakes. [Professor Joel Brockner's research](https://medium.com/@dennishenry/the-unseen-scar-the-mental-health-toll-of-tech-layoffs-on-those-laid-off-and-those-who-remain-cd0b90a907d5?ref=ceo.com), cited in multiple studies of layoff survivors, found that those who remain frequently develop what he calls a "cocktail of negative emotions: anger, depression, fear, distrust, and guilt," resulting in reduced performance and higher absenteeism. At Google, employees openly reported a "significant decline in morale" and "increased distrust" toward leadership after the 2023 cuts. As workplace mental health expert [Sally Spencer-Thomas told CBS News](https://www.cbsnews.com/news/layoff-survivor-guilt-tech-layoffs/?ref=ceo.com), "It creates a lot of paranoia, and because of that, you get a lot of distrust within an organization with these large-scale layoffs. Workers will question if the organization has their well-being at heart or if they are only looking at profit-making." [Harvard Business School research](https://hbr.org/2018/05/layoffs-that-dont-break-your-company?ref=ceo.com) confirms the pattern. Professor Sandra Sucher, who has studied layoffs extensively, found that "job cuts rarely help senior leaders achieve their goals. Too often, they're done for short-term gain, but the cost savings are overshadowed by bad publicity, loss of knowledge, weakened engagement, higher voluntary turnover, and lower innovation, which hurt profits in the long run." A [study of 146 companies](https://www.cultureamp.com/blog/company-layoffs-myths?ref=ceo.com) that conducted layoffs showed it often takes years, not months, for engagement, morale, and loyalty to rebound. ## What Genuine Responsibility Looks Like The contrast between the 2023 tech layoffs and other approaches to workforce reduction is instructive. **Satoru Iwata, Nintendo (2013):** When Nintendo's Wii U console failed and the company faced years of losses, CEO Satoru Iwata [took a 50% pay cut rather than lay off employees](https://www.cnbc.com/2024/02/13/nintendo-ceo-once-halved-salary-to-prevent-layoffs-why-thats-uncommon.html?ref=ceo.com). Board members took 20% cuts. His reasoning was explicit: "If we reduce the number of employees for better short-term financial results, employee morale will decrease. I sincerely doubt employees who fear that they may be laid off will be able to develop software titles that could impress people around the world." Nintendo retained its talent, developed the Switch, and sold over 139 million units. **Honeywell (2008):** During the recession, Honeywell chose furloughs over layoffs, [preserving jobs while reducing costs](https://hbr.org/2013/06/honeywells-ceo-on-how-he-avoided-layoffs?ref=ceo.com). The company emerged with its workforce intact and its culture stronger. **Nokia's Bridge Program:** When Nokia needed to reduce headcount by 18,000 employees across 13 countries, the company [built an extensive program](https://www.linkedin.com/pulse/theres-better-way-do-layoffs-what-nokia-learned-hard-sandra-sucher/?ref=ceo.com) to help workers transition. It offered support for those starting businesses, pursuing education, and finding new jobs. The cost: approximately 2,800 euros per employee. Compare that to a previous plant shutdown in Germany, where abrupt layoffs of 2,300 employees cost 700 million euros in lost sales and 100 million euros in profit, nearly 30 times as expensive per person affected. **Airbnb (2020):** When COVID-19 decimated travel, Airbnb CEO Brian Chesky had to lay off 25% of the workforce, about 1,900 people. His approach became [a case study in compassionate communication.](https://www.prnewsonline.com/airbnb-ceo-delivers-empathetic-transparent-message-regarding-layoffs/?ref=ceo.com) He wrote the layoff letter personally, using human language rather than corporate jargon. He explained exactly how decisions were made. He provided 14 weeks of severance plus one additional week per year of service, 12 months of health insurance, accelerated equity vesting, and an Alumni Talent Directory to help departing employees find new jobs. He converted a significant portion of Airbnb's recruiting team into an alumni placement team. As Chesky [later reflected on the Adam Grant podcast](https://www.inc.com/nick-hobson/airbnb-ceo-brian-chesky-tells-adam-grant-right-way-to-do-mass-layoffs-cut-deep.html?ref=ceo.com): "I would rather say a couple of wrong things and embarrass myself, but at least people know I'm speaking from the heart, than execute it coldly and perfectly." ## The Framework for Responsible Leadership Harvard Business School's Sandra Sucher has developed extensive research on how to handle workforce reductions responsibly. Her framework offers several principles: **1\. Exhaust alternatives first.** Before layoffs, responsible companies explore furloughs, reduced hours, voluntary unpaid leave, redeployment, reskilling, job sharing, and executive pay cuts. Layoffs should be a last resort, not a first response. **2\. Understand legal and cultural contexts.** Different countries have different requirements for layoffs. Companies operating globally must navigate these carefully and plan accordingly. **3\. Develop a clear philosophy.** Companies that handle layoffs well have thought deeply about their obligations to employees before crisis hits. Sucher cites Michelin, which vows to "restructure during good times, rather than bad times" because they want to ensure they have the financial resources to treat people fairly. **4\. Communicate transparently and personally.** Airbnb's Chesky wrote his own letter. He explained the business context, the decision process, and exactly what affected employees would receive. He addressed both those leaving and those staying. He used human language. PR agency CEO Debbie Zaman advises: "Considering ways of delivering some greater degree of transparency rather than the fallback line of 'full responsibility' can help give a sense of treating teams with respect." **5\. Provide genuine support.** Severance, extended healthcare, job placement assistance, alumni networks. Nokia's Bridge program and Airbnb's talent directory represent what genuine investment in departing employees looks like. **6\. Share the pain meaningfully.** When Intel's CEO took a 25% pay cut and reduced executive salaries by 15% to avoid broad layoffs, it signaled shared sacrifice. When CEOs announce massive layoffs while retaining their full compensation packages, the message is quite different. **7\. Address survivors' needs.** The remaining workforce faces guilt, anxiety, and increased workload. Acknowledging these emotions, providing mental health resources, and being present as a leader matters enormously. As one manager told researchers: One leadership response was essentially "be grateful, now work," which bred quiet fury. Another RIF, handled differently, involved a team meeting acknowledging the difficulty, encouraging discussion, and granting permission to not be 100% productive. That empathy significantly helped maintain morale. ## The Deeper Question Sucher frames the fundamental issue plainly: "We're in a crisis of trust in leadership. Leaders of all kinds are failing some of the basic expectations that people have for how they should be treated." The 2023 tech layoffs revealed something about how many leaders conceptualize their role. When pandemic-era growth reversed, the response was immediate: shed workers to protect margins and reassure investors. The language of responsibility was deployed, but the substance was absent. The alternative is not that layoffs should never happen. Sometimes they are unavoidable. The question is whether leaders carry the weight of those decisions or find ways to avoid feeling it. Whether they treat employees as human beings with families and futures or as line items to be optimized. Whether they exhaust alternatives or reach for the easiest solution. Whether they share sacrifice or preserve their own position while asking others to bear the cost. As one tech industry [analysis noted](https://www.entrepreneur.com/business-news/tech-ceos-are-to-blame-for-mass-layoffs-analysis/444397?ref=ceo.com): "The blame rests squarely on the shoulders of their CEOs. As the sole person in charge, they're responsible for misjudging the macroeconomy, making terrible investments, and then following along with the industry in a shortsighted attempt to please Wall Street. And yet, despite a smattering of pay reductions, none of them have faced real consequences." ## Conclusion: The Weight That Leaders Owe The 2023 tech layoffs will be studied for years as an example of what happens when an industry moves in lockstep, when leaders follow playbooks rather than principles, and when the language of responsibility substitutes for the substance of accountability. The research is clear: layoffs often fail to achieve their stated goals, damage company culture for years, and cost more than they save when hidden costs are factored in. The leaders who handle workforce reductions well are those who see employees as human beings first, exhaust alternatives, communicate with honesty and humanity, share in the sacrifice meaningfully, and invest genuinely in helping affected workers land on their feet. The weight of leadership is not optional. The only question is whether leaders carry it consciously or find ways to set it down. The 2023 tech layoffs showed us what happens when an entire industry chooses the latter. --- **Sources:** NPR, Fortune, Inc. Magazine, CNBC, Harvard Business School Working Knowledge, Harvard Business Review, CBS News, Crunchbase, Leadership IQ, Employee Benefit News, Airbnb Newsroom ### Learning to respond URL: https://www.ceo.com/blog/learning-to-respond/ Last updated: 2026-08-18T00:25:32.000Z I've made decisions that still keep me up at night. Not the ones where I lacked information or made a reasonable bet that didn't pay off. Those I can live with. The ones that haunt me are the decisions I made when I was angry, or afraid, or wounded. The times I fired off an email I should have sat on. The conversations I escalated when I should have listened. The relationships I damaged because I was reacting to something inside myself rather than responding to what was actually in front of me. If you've been there, you know. The slow-motion recognition that you've done something you can't undo. The sinking feeling when you realize your emotional state just cost you something that mattered. I'm not writing this as someone who's figured it out. I'm writing as someone who's been humbled by his own reactivity more times than I'd like to admit. Someone who's still learning, still failing, still trying to close the gap between the leader I want to be and the one who shows up when things get hard. ## **The pattern** When I look back at my worst decisions, both personal and professional, there's a pattern. It's not that I didn't know better. It's that I knew better and did it anyway. The information was there. The wiser path was visible. But something in me was hijacked. A prominent leader publicly questioned my judgment, and instead of getting curious, I got defensive. A key hire didn't work out, and instead of taking responsibility for the miss, I looked for someone to blame. Someone I trusted disappointed me, and instead of having a real conversation, I withdrew into cold professionalism. The common thread was always the same: I was operating from my emotions rather than through them. The feeling was running the show, and I was just along for the ride. Maybe you recognize this. Maybe you've watched yourself do something you knew was wrong while a quieter part of your mind observed the wreckage in real time. If so, you're not alone. And you're not broken. You're just human. ## **The space between** Viktor Frankl survived the Nazi concentration camps. In that darkness, he noticed something about the people around him. Those who maintained some sense of inner freedom, who could still choose how they responded to horror, were more likely to survive. Not just physically. Their humanity survived. [He wrote](https://www.amazon.com/Mans-Search-Meaning-Viktor-Frankl/dp/0807060100/?ref=ceo.com) that between stimulus and response there is a space. In that space is our power to choose our response. In our response lies our growth and our freedom. That space is everything. It's where leadership happens. Not in the boardroom or the all-hands meeting, but in the gap between what happens to you and what you do about it. The problem is that the space can feel impossibly small. When the emotion is big enough, it shrinks to almost nothing. The stimulus arrives and the response fires before you've had time to think. You're halfway through the angry email before you realize you're writing it. Expanding that space is the work. Not eliminating the emotions. Not pretending you don't feel what you feel. Just creating enough room to choose. ## **What the research shows** [James Gross at Stanford](https://spl.stanford.edu/people/james-gross?ref=ceo.com) has spent decades studying how we manage our emotional lives. His work identifies two common strategies: suppression and reappraisal. Suppression is what most of us default to. Push it down. Don't let it show. Keep it together. The problem is that suppression doesn't actually work. The internal experience doesn't diminish. You just stop expressing it. Meanwhile, your body is still flooded with stress hormones, your memory is impaired, and the people around you can feel that something is off. You're leaking what you're trying to contain. Reappraisal is different. Instead of trying to push the feeling down, you change how you think about the situation before the emotional response fully develops. You reframe. The board member isn't attacking you; they're stress-testing your thinking. The failed hire isn't a judgment on you; it's information about what you need to look for next time. The difficult conversation isn't a threat; it's an opportunity to deepen the relationship. This isn't positive thinking or denial. It's recognizing that your first interpretation isn't the only interpretation. And your first interpretation is almost always shaped by fear. ## **The contagion problem** [Daniel Goleman's research](https://www.amazon.com/Emotional-Intelligence-audiobook/dp/B0000647PF/?ref=ceo.com) on emotional intelligence surfaced something that should trouble every CEO: emotions are contagious, and they spread most readily from the most powerful person in the room. Your emotional state doesn't stay inside of you. It radiates outward. Your anxiety becomes your team's anxiety. Your frustration becomes their frustration. Your unprocessed fear shows up in a hundred small ways you never intended. I've experienced this from both sides. I've walked into rooms and unknowingly poisoned them with my mood. I've also been in rooms where the leader's calm centeredness made everything feel possible. The difference isn't personality. It's practice. Goleman found that self-awareness is the foundation. Most people think they're self-aware; very few actually are. The gap between how we think we're showing up and how we actually are is where the damage happens. ## **What the stoics understood** Marcus Aurelius ruled the Roman Empire during plagues, wars, and rebellions. He had every reason to be consumed by anxiety and anger. Instead, he spent his evenings writing notes to himself about how to be a better person. "You have power over your mind," [he wrote](https://www.amazon.com/Audible-Meditations-A-New-Translation/dp/B0C5K39V65/?ref=ceo.com), "not outside events. Realize this, and you will find strength." The Stoics weren't about suppressing emotion. That's a common misunderstanding. They were about not being enslaved by it. They understood that our perception of events, not the events themselves, determines our emotional state. The same situation that destroys one person leaves another unshaken. The difference isn't circumstances. It's interpretation. Marcus believed that angry, aggressive people were actually weak. Real strength was the capacity for restraint. During a civil war, when a general mocked him as a "philosophical old woman" for not retaliating with rage, Marcus didn't take the bait. He understood that the general was trying to provoke him into becoming something smaller than he was. I think about this when I feel the urge to respond to criticism with force. The temptation is to match energy, to hit back. But matching energy with someone who's operating from a lower place just drags you down to their level. The real power is staying rooted in who you want to be, regardless of what's coming at you. ## **The ongoing work** I wish I could tell you there's a technique that solves this. Some system that, once implemented, makes emotional regulation automatic. But that hasn't been my experience. What I've found instead is that it's a daily practice without a finish line. Some days I do it well, and other days I fall back into old patterns. The difference between now and years ago isn't that I've mastered anything, but that I notice more quickly when I'm off. The space between stimulus and response has widened, not because I have eliminated the emotions, but because I've gotten better at recognizing them before they take over. A few things have helped. Keeping a journal, not for posterity, but to process. Noticing what triggers me and being honest about why. Asking people I trust how I'm actually showing up, then listening to the answer without defending myself. Taking care of the physical basics, because emotional regulation is nearly impossible when you're exhausted or depleted. And giving myself permission to pause before responding to anything that produces a strong reaction. None of this is glamorous. None of it makes for a good LinkedIn post. But it's the work. ## **The inner game** I've spent decades building communities of CEOs and founders. The pattern I see is consistent. The leaders who build enduring organizations and inspire genuine loyalty aren't necessarily the smartest or the most driven. They're the ones who have done the inner work. They've learned to respond rather than react. They've expanded the space between stimulus and response. Your company can only grow as fast as you do. Your team can only be as healthy as you are. Your culture, whether you like it or not, is largely a reflection of your emotional state multiplied across every interaction. This isn't about becoming someone you're not. It's about becoming more fully who you already are, underneath the reactivity and the fear. The version of you that shows up when you're centered, when you're not threatened, when you have enough space to choose. That version is in there. It just needs room to emerge. I'm still learning how to give it that room. If you're on the same journey, I'm glad we're not doing it alone. ### When knowing isn't doing: Strategic delay and the cost of inertia URL: https://www.ceo.com/blog/when-knowing-isn-t-doing-strategic-delay-and-the-cost-of-inertia/ Last updated: 2026-08-19T02:39:53.000Z The story of IBM and the personal computer is not, as commonly assumed, a tale of a company that failed to enter a market. IBM launched the IBM 5150 in August 1981, just a few years after the Apple II. The machine was a runaway success, exceeding sales expectations by over 800% in its first year. The real story is more instructive for leaders: IBM knew what it needed to do at critical junctures, but delayed doing so. The company underestimated the PC's strategic importance, failed to control the platform's key components, and responded too slowly when competitors exploited these gaps. By the time IBM attempted to reassert control in 1987, the market had moved on without them. This case study examines IBM's PC strategy through the lens of decision-making and personal leadership. It demonstrates how even the most successful organizations can know the right course of action and still fail to execute, how institutional culture can override strategic clarity, and how the gap between knowing and doing can transform market leaders into also-rans. --- ## Part I: The Landscape **IBM in 1980: The Unchallenged Giant** By 1980, IBM dominated the computer industry. As James W. Cortada documents in [*IBM: The Rise and Fall and Reinvention of a Global Icon*](https://www.amazon.com/IBM-Reinvention-Global-History-Computing/dp/0262039443?ref=ceo.com), "For decades, IBM shaped the way the world did business. IBM products were in every large organization, and IBM corporate culture established a management style that was imitated by companies around the globe. It was 'Big Blue,' an icon." The company's strength was in mainframes and minicomputers, high-margin machines sold to large enterprises. The corporate culture that had built this dominance was legendary. IBM employees were known for their white shirts, conservative dress, and unwavering commitment to customer service. The saying in corporate America was simple: "No one ever got fired for buying IBM." But a new market was emerging. Apple had introduced the Apple II in 1977\. Commodore and Tandy were selling machines to hobbyists and small businesses. The personal computer market, though tiny compared to IBM's mainframe business, was growing rapidly. IBM's leadership saw this. They understood the trend. The question was what to do about it. ### The Decision to Enter In 1980, William Lowe, director of IBM's General Systems Division lab in Boca Raton, Florida, pitched IBM CEO Frank Cary on the idea of a computer for small businesses and consumers that would sell for around $1,500\. Cary gave Lowe an aggressive timeline: a month to develop a prototype and a year to get a product to market. This timeline forced a critical decision. IBM could not build the PC the way it built mainframes. There wasn't time to develop proprietary components, and the economics didn't justify the investment. As one industry analysis noted, Lowe's plan "called for buying existing components and software and bolting them together into a package aimed at the consumer market. There would be no homegrown operating system or IBM-made chips." Don Estridge, who took over the project after Lowe's promotion, assembled a small team in Boca Raton. They operated as a "skunkworks," isolated from IBM's standard procedures and bureaucracy. The team, nicknamed the "Dirty Dozen," made decisions quickly and built a machine from off-the-shelf components: an Intel 8088 processor, commodity parts, and an operating system licensed from a small company called Microsoft. The IBM PC launched on August 12, 1981\. It was an immediate success. IBM sold 200,000 units in the first year, then 200,000 units per month. By 1984, the company had 75% of the personal computer market. From the outside, this looked like flawless execution. From the inside, the seeds of IBM's decline were already planted. --- ## Part II: Three Strategic Delays **Delay One: Underestimating Strategic Importance** The IBM PC was never treated as central to the company's future. Cortada's analysis reveals that IBM's leadership "still saw mainframes/minis as the real business." The PC was a side project, organizationally and psychologically separated from IBM's core operations. This wasn't ignorance. IBM's leaders could see the PC market growing. They had the data. They understood the technology trends. But the mainframe business was enormously profitable, and the PC business, even at scale, would never match those margins. As one Amazon reviewer of Cortada's book observed about IBM's leadership: "Poor leadership helped to give away the PC business... over focus on the mainframe for years after it was a dinosaur." The Boca Raton operation that created the PC was deliberately kept small and autonomous. When the PC succeeded beyond all expectations, this became a problem. On August 1, 1983, Estridge's skunkworks was redesignated the Entry Systems Division, which meant the PC business was absorbed into IBM's corporate bureaucracy. Estridge's 4,000-person group mushroomed to 10,000\. He protested that corporate had transferred thousands of programmers who "knew nothing about PCs." The very qualities that had made the PC possible (speed, autonomy, and willingness to use outside components) were systematically eliminated once the product succeeded. IBM's institutional immune system rejected the transplant. ### Delay Two: Failing to Control the Platform The most consequential decisions IBM made were about what it chose not to own. Microsoft had been brought in to provide the operating system. Bill Gates and Microsoft didn't actually have an operating system when IBM came calling. Gates quickly licensed a product called QDOS ("Quick and Dirty Operating System") from Seattle Computer Products for $75,000, adapted it for the IBM PC, and delivered it as PC-DOS. Here is where IBM made its critical error: the company allowed Microsoft to retain the rights to license the same operating system to other manufacturers. IBM paid a flat fee rather than taking an exclusive license. As one analysis put it, "IBM's strategic error in not retaining rights to the operating system went far beyond \[the immediate financial impact\]; it meant that Microsoft would set the standards for the PC operating system." IBM also chose an open architecture with commodity parts. Anyone could see exactly how the machine was built and replicate it, except for the BIOS (Basic Input/Output System), which was IBM's proprietary code. Within a year, competitors were working to clone the BIOS. Columbia Data Products produced the first IBM PC clone in June 1982\. Compaq followed in November 1982 with the Compaq Portable, featuring a legally reverse-engineered BIOS created using "clean room" techniques. The company spent $1 million to ensure their BIOS was functionally equivalent to IBM's without copying any code. The clean room approach worked. IBM's legal challenges failed. And once Phoenix Technologies began selling a clone BIOS to anyone in 1984, the floodgates opened. Any manufacturer could now build a fully IBM-compatible PC without paying IBM a cent. IBM knew about the clone threat almost immediately. The company understood that its open architecture was being exploited. Yet it delayed taking decisive action to close the platform or develop proprietary advantages. The mainframe mindset, in which IBM controlled everything and customers came to IBM, prevented leaders from recognizing that the PC market operated by different rules. ### Delay Three: The PS/2 Comes Too Late By the mid-1980s, the damage was becoming clear. IBM's market share plummeted from 76% in 1983 to 26% in 1986\. Clone manufacturers were eating IBM's lunch with machines that were cheaper, often faster, and fully compatible with IBM's software ecosystem. In 1987, six years after the PC's launch and five years after clones began flooding the market, IBM finally attempted to reassert control. The company launched the Personal System/2 (PS/2) line with a proprietary bus architecture called Micro Channel Architecture (MCA). The strategy was explicit: create a new standard that would require clone makers to pay licensing fees to maintain compatibility. The market rejected it. MCA was technically superior to the Industry Standard Architecture (ISA) bus used in existing PCs. But the clone manufacturers had no intention of surrendering their independence. Led by Compaq, nine major PC makers formed the "Gang of Nine" and announced a competing standard called Extended Industry Standard Architecture (EISA). Customers who had invested heavily in ISA expansion cards and peripherals saw no compelling reason to abandon their existing hardware for IBM's new, proprietary system. As one analysis noted, "With what was widely seen as a technically competent but cynical attempt to gain undisputed control of the market, IBM unleashed an industry backlash." The PS/2 sold reasonably well initially, moving about 3 million units in its first two years. But it failed to recapture the market. IBM's share continued to decline. By 1994, Compaq had replaced IBM as the number one PC vendor in the United States. IBM had waited too long. The trigger that might have worked in 1982 or 1983 misfired in 1987\. The market had evolved past the point where IBM could dictate terms. --- ## Part III: The Consequences **The Near-Collapse** The PC debacle was part of a larger institutional failure at IBM. By the early 1990s, the company was in crisis. Its stock price fell from $43 in 1987 to $13 by the early 1990s. The company lost $8 billion in 1993 alone, marking a three-year loss of nearly $16 billion. IBM, the company that had shaped global business for decades, was on the verge of bankruptcy. Bill Gates predicted the company would fold within seven years. Cortada argues in his history that IBM had developed a corporate "sclerosis," an over-bureaucratization that impeded its ability to adapt. A generation of senior executives was out of touch and unprepared to respond to new market demands. The board eventually hired Lou Gerstner, a CEO with no technology background, who had previously run American Express and RJR Nabisco. Gerstner kept IBM intact instead of breaking it apart as many advised, laid off nearly 100,000 employees, and shifted the company's focus from hardware to services and software. IBM survived. But it eventually sold its PC division to Lenovo in 2005 for $1.75 billion, an inglorious exit from a market it had once dominated. ### Where the Value Went The value that IBM failed to capture didn't disappear. It simply went elsewhere. Microsoft, with its non-exclusive DOS license, became one of the most valuable companies in the world. Every clone manufacturer needed an operating system, and Microsoft was happy to sell them one. By the early 1990s, Microsoft had leveraged that operating system dominance into Windows and Office, building a software empire worth tens of billions of dollars. Intel, which supplied the processors, captured another piece. The "Wintel" duopoly (Windows plus Intel) defined the PC industry for decades, with IBM relegated to one manufacturer among many. The clone manufacturers, Compaq, Dell, Gateway, and eventually Asian manufacturers, captured the hardware business by competing on price, features, and speed to market. These companies had no legacy mainframe business to protect, no institutional culture telling them that PCs were a side project. IBM had created the standard, validated the market, and then watched others capture most of the value. --- ## Part IV: Lessons for Leaders **The Gap Between Knowing and Doing** IBM's story is not about ignorance. The company had some of the smartest people in technology. They understood the PC market. They saw the clone threat. They knew, eventually, that their open architecture was a strategic vulnerability. They knew all of this and still delayed action for years. This is the gap between knowing and doing that defines personal leadership failures. It's not that leaders lack information. It's that something prevents them from acting on what they know. For IBM, that something was institutional culture. The company had been successful for so long with one model (proprietary systems, high margins, enterprise customers) that it couldn't fully commit to a different model even when the evidence demanded it. The PC division was always treated as peripheral to the "real" business, even as it was transforming the entire industry. ### When the Trigger Gets Heavier IBM had multiple opportunities to pull the trigger on a different strategy. In 1980, they could have developed a proprietary operating system. In 1981, they could have negotiated exclusive rights to DOS. In 1982, they could have moved aggressively against clones. In 1983, they could have committed to the PC as the company's strategic future. Each year they delayed, the trigger got heavier. The clone ecosystem grew. Microsoft's installed base expanded. Customers invested in ISA hardware. By 1987, when IBM finally attempted to reassert control with the PS/2, it was too late. The market had reached a tipping point where IBM no longer had the power to dictate terms. This is how procrastination works in strategic decisions. Early action is relatively easy; the forces arrayed against you are still weak. But delay allows those forces to strengthen. What would have been a manageable challenge becomes an impossible one. ### The Illusion of Time IBM's leaders likely believed they had time. The mainframe business was still profitable. The PC was growing but hadn't yet overtaken traditional computing. The clone threat was concerning but not yet existential. This is the most dangerous form of the knowing-doing gap: the situation where the right action is clear but doesn't feel urgent. Leaders tell themselves they'll address it after the current quarter, after the next product launch, after the board meeting. Month after month. Year after year. The market doesn't wait for leaders to feel ready. IBM's competitors weren't constrained by IBM's internal debates about strategic priorities. They simply built products, captured customers, and established facts on the ground. ### Values Revealed by Decisions What did IBM's decisions reveal about its actual values, as opposed to its stated ones? The company said it valued innovation. But it treated its most innovative division, the Boca Raton skunkworks, as an aberration to be normalized once the immediate pressure was off. The company said it valued customers. But it tried to force customers onto a new proprietary standard (MCA) that served IBM's interests rather than customer needs. The company said it wanted to win in personal computing. But it never committed the resources, attention, or organizational priority that would have been required. Actions reveal values. IBM's actions revealed that it valued its existing business model, corporate culture, and short-term mainframe profits more than it valued the strategic transformation the PC market demanded. --- ## The Decision That Wasn't Made IBM's PC story is ultimately about a decision that wasn't made: the decision to treat the personal computer as the company's strategic future and to organize everything around winning that market. This wasn't a decision that required a single dramatic moment. It required sustained commitment, organizational change, and the willingness to cannibalize existing businesses. It required IBM's leadership to see beyond the current quarter's mainframe profits to the long-term trajectory of computing. They knew what that trajectory looked like. The data was clear. The trends were visible. The competitive threats were obvious. They knew and still didn't act. Not because they were stupid, evil, or incompetent, but because they were human. Because institutional inertia is powerful. Because it's easier to optimize the existing business than to transform it. Because the mainframe profits were real today, and the PC opportunity was uncertain tomorrow. This is why personal leadership matters. Organizations don't make decisions; leaders do. And leaders are subject to all the predictable irrationalities that Dan Ariely documents: the tendency to overvalue the present, to avoid loss, to anchor on past success, to delay difficult choices. The gap between knowing and doing isn't closed by better information or smarter analysis. It's closed by leaders who recognize their own patterns, design systems that account for institutional inertia, and make the difficult calls before the trigger becomes too heavy to pull. IBM eventually found such a leader in Lou Gerstner, who arrived in 1993 after the company had nearly collapsed. Gerstner pulled the trigger on dramatic changes, including laying off 100,000 employees and fundamentally transforming IBM's business model. But by then, the PC market was already lost. The changes that could have saved IBM's dominance in personal computing would have been much less painful if made in 1982 or 1983\. Instead, IBM waited too long, and by the time they acted, only painful options remained. The lesson for leaders is not complicated. It's just hard. When you know what needs to be done, do it. The gap between knowing and doing is where companies go to die. --- ### Sources Cortada, James W. *IBM:* [*The Rise and Fall and Reinvention of a Global Icon*](https://www.amazon.com/IBM-Reinvention-Global-History-Computing/dp/0262039443?ref=ceo.com). MIT Press, 2019. Gerstner, Louis V. [*Who Says Elephants Can't Dance? Inside IBM's Historic Turnaround*](https://www.amazon.com/Who-Says-Elephants-Cant-Dance/dp/0060523794?ref=ceo.com). Harper Business, 2002. ["How the IBM PC Won, Then Lost, the Personal Computer Market."](https://spectrum.ieee.org/how-the-ibm-pc-won-then-lost-the-personal-computer-market?ref=ceo.com) *IEEE Spectrum*, March 2023. ["The IBM PS/2: 25 Years of PC History."](https://www.pcworld.com/article/465931/the%5Fibm%5Fps%5F2%5F25%5Fyears%5Fof%5Fpc%5Fhistory.html?ref=ceo.com) *PCWorld*, April 2012. Computer History Museum. ["Send in the Clones: Capitalizing on IBM's Success."](https://www.computerhistory.org/revolution/personal-computers/17/302?ref=ceo.com) *CHM Revolution*. IBM Corporate Archives. ["The IBM PC"](https://www.ibm.com/history/personal-computer?ref=ceo.com) and ["The PS/2."](https://www.ibm.com/history/ps-2?ref=ceo.com) IBM History. --- ## Notes on Sourcing Methodology 1. **Primary reliance on Cortada:** As the most comprehensive scholarly treatment of IBM's history, written by a 38-year IBM veteran, Cortada's work serves as the authoritative backbone for historical claims about IBM's culture, decision-making, and strategic failures. 2. **Cross-verification:** Key facts (dates, market share figures, product launches) were verified across multiple sources, including IEEE Spectrum, PCWorld, Computer History Museum, and Wikipedia. 3. **Contemporary sources:** Where possible, claims about IBM's strategic thinking are supported by contemporary accounts and insider perspectives rather than retrospective analysis alone. 4. **Quantitative claims:** All numerical data (market share percentages, sales figures, financial losses) are cited to specific sources and cross-referenced where possible. ### The trigger you won't pull URL: https://www.ceo.com/blog/the-trigger-you-wont-pull/ Last updated: 2026-08-18T00:24:49.000Z I spent years knowing exactly what I needed to do. For my health. For my organization. The answers weren't mysteries. They were obvious. I'd think about them constantly, devise elaborate plans, run the scenarios in my head until they felt almost real. And then I'd do nothing. Month after month. Year after year. The frustrating part wasn't that I didn't know better. It was that I knew better and still didn’t act. I watched myself procrastinate with a kind of detached horror, like seeing a car crash in slow motion and realizing you're the one behind the wheel. Dan Ariely's research in [*Predictably Irrational*](https://www.amazon.com/Predictably-Irrational-Revised-Expanded-Decisions/dp/0061353248?ref=ceo.com) helped me understand why. We like to believe we're rational creatures who occasionally make emotional mistakes. The truth is closer to the opposite. We're emotional creatures who occasionally stumble into rationality. And our irrationality isn't random. It follows patterns so consistent that Ariely and his colleagues can predict them. We overpay. We underestimate. We procrastinate. We do these things not because we're stupid but because we're human. The same brain that can build rockets and compose symphonies will also convince us that starting a diet on Monday makes more sense than starting today. This is the uncomfortable territory where personal leadership begins. ## The gap between knowing and doing Most leadership content focuses on strategy, vision, and execution. These matter. But they assume something that isn't true: that once you know the right thing to do, you'll do it. The gap between knowing and doing is where most of us live. We know we should let the underperforming team member go. We know we should stop checking email at midnight. We know we should exercise, eat better, spend more time with family, delegate more, and work on the business instead of in it. We know all of this. And we don't do it. Ariely's work reveals that we're not fighting laziness or lack of willpower. We're fighting the architecture of our own minds. We're wired to overvalue the present and discount the future. We're wired to avoid loss more than we pursue gain. We're wired to anchor on irrelevant information and let it shape our decisions. These aren't bugs in human cognition. They're features. They helped our ancestors survive in environments where the immediate threat of a predator mattered more than long-term planning. But in the modern world, they sabotage us constantly. The leader who understands this has an advantage. Not because they can overcome their irrationality through sheer force of will, but because they can design around it. ## When your gut is right and when it's wrong Intuition gets a strange reputation in business. Some leaders swear by it, treating gut feelings as mystical signals from a higher wisdom. Others dismiss it entirely, insisting that data should drive every decision. Both camps are wrong. Your gut is an incredibly sophisticated pattern-recognition system. It synthesizes years of experience into split-second assessments. When a seasoned CEO walks into a negotiation and feels something is off, that feeling represents decades of accumulated knowledge processing information faster than conscious thought can manage. But your gut is also a liar. It's susceptible to every bias Ariely documents. It anchors on the first number it hears. It values things more simply because you already own them. It judges probability based on how easily examples come to mind rather than actual frequency. It tells you the expensive hoodie is better because you know it's expensive. The skill isn't learning to trust your gut or ignore it. The skill is learning when to do which. For decisions where you have deep expertise and real experience, intuition is powerful. The CEO who has hired hundreds of people develops a genuine predictive feel for candidates. The entrepreneur who has launched multiple products can sense market fit in ways they can't fully articulate. For decisions outside your expertise, or where strong emotions are involved, or where the stakes create pressure to see what you want to see, your gut becomes unreliable. These are the moments to slow down, gather data, seek outside perspectives, and treat your intuition as one input among many rather than the final word. The hardest part is that the same gut feeling can be wise pattern recognition in one context and self-serving rationalization in another. Distinguishing between them requires a level of self-awareness that most of us resist developing. It's uncomfortable to examine our own motivations. It's even more uncomfortable to admit when we can't trust ourselves. ## What your decisions say about your values Here's what years of not pulling the trigger taught me: my actions revealed my real values, not my intentions. I said health was important. My behavior said it wasn't. I said organizational change was urgent. My procrastination said it could wait. The stories I told myself about what I valued were contradicted daily by what I actually did. This is the mirror that personal leadership forces you to look into. Not the mirror of what you believe you value, but the mirror of what your decisions prove you value. Every choice we make, including delaying or avoiding, reflects our priorities. When we procrastinate on something that matters, we're signaling that something else is more important. Usually, that thing is comfort, avoiding short-term discomfort, or maintaining a self-image that could be threatened by trying and failing. Ariely's research shows we're predictably irrational. But it also implies something hopeful: if our irrationality is predictable, it can be anticipated. If it can be anticipated, it can be managed. Not through willpower alone, but through structure, environment, and honest self-assessment. The leader who designs systems that account for their own predictable irrationality will outperform the leader who relies on discipline they don't actually have. The leader who makes their values visible through commitment devices, accountability structures, and pre-made decisions will close the gap between intention and action. ## Pulling the trigger So how do you finally act? First, stop waiting for the feeling. The right time, the perfect clarity, the surge of motivation that will make action easy. It doesn't come. The research is clear on this: action precedes motivation more often than motivation precedes action. You don't feel like doing it until you're already doing it. Second, make the decision smaller. The reason we don't pull the trigger is often that we've made the trigger too heavy. We're not deciding whether to have one difficult conversation. We're deciding to transform the entire culture. We're not deciding to exercise today. We're deciding to become a different person. Shrink the decision to something that doesn't require you to overcome your entire psychology at once. Third, design for your irrationality. If you know you'll procrastinate, create deadlines that are external and real. If you know you'll avoid difficult conversations, schedule them in advance when you're feeling brave, before your future self can back out. If you know you'll overpay for things you don't need, remove the opportunity to buy them. Fourth, make your values operational. Abstract values are easy to hold and easier to violate. Specific commitments are harder to escape. "I value health" is abstract. "I exercise at 6 AM before anything else can interfere" is operational. The gap between knowing and doing closes when values become behaviors with times and places attached. Finally, accept that you'll still fail. Not occasionally. Regularly. The goal isn't to become perfectly rational. That's impossible and probably wouldn't be desirable even if it weren't. The goal is to fail less predictably. To catch yourself in the patterns. To build systems that work even when your willpower doesn't. ## The personal in personal leadership We throw the word "leadership" around so often that it loses meaning. We attach it to roles, titles, and org charts. We talk about leading teams, markets, and industries. But the hardest leadership happens inside. It happens when no one is watching. It happens in the gap between what you know and what you do, between the person you believe yourself to be and the person your decisions reveal. Ariely showed us that we're predictably irrational. That's not an indictment. It's an invitation. Once you know the patterns, you can work with them instead of pretending they don't apply to you. The trigger you haven't pulled is still there. The change you've been avoiding is still necessary. The gap between your stated values and your actual behavior is still measurable in the decisions you make every day. The question isn't whether you'll be irrational. You will be. The question is whether you'll be honest about it. Whether you'll design your life and leadership to account for it. Whether you'll close the gap, not through superhuman discipline, but through the humble recognition that you're exactly as predictable as everyone else. That recognition is where personal leadership begins. And it's where the real work starts. ### Elon Musk and the theology of attention URL: https://www.ceo.com/blog/elon-musk-and-the-theology-of-attention/ Last updated: 2026-08-19T02:36:40.000Z If Kierkegaard was right that where your attention rests shows what you worship, then Elon Musk's life offers one of the most vivid case studies of our time. His attention reveals his values with unmistakable clarity. Whether you admire him or find him troubling, there is no gap between what Musk says matters and where he actually spends his time. This is rare. Most of us live with a comfortable distance between our stated priorities and our lived attention. Musk does not. ## The Evidence of Hours Musk has spoken openly about his work habits for decades. In his 2014 [commencement speech](https://www.knowol.com/knowledge/elon-musk-secrets-success/?ref=ceo.com) at USC's Marshall School of Business, he told graduates: "When my brother and I were starting our first company, instead of getting an apartment, we just rented a small office, and we slept on the couch. We showered at the YMCA, and we were so hard up we had just one computer, so the website was up during the day and I was coding at night, seven days a week, all the time." His conclusion was [characteristically blunt](https://www.bestgraduationspeeches.com/elon-musk-speech-university-of-southern-california-transcript-quotes-video/?ref=ceo.com): "So work hard, like, every waking hour. That's the thing I would say, particularly if you're starting a company. If you do the simple math, say that someone else is working 50 hours and you're working 100, you'll get twice as much done in the course of a year as the other company." This was not youthful exuberance. In a 2018 interview on the Recode Decode podcast, Musk described working 90 to 120 hours per week during Tesla and SpaceX crises. On social media that same year, he declared: "There are way easier places to work, but [nobody ever changed the world on 40 hours a week](https://finance.yahoo.com/news/elon-musk-once-stated-nobody-190012187.html?ref=ceo.com)." ## Sleeping on the Factory Floor During Tesla's Model 3 production crisis in 2018, Musk's commitment became legendary. In an [interview](https://www.cbsnews.com/news/elon-musk-tesla-model-3-problems-interview-today-2018-04-11/?ref=ceo.com) with CBS This Morning host Gayle King, he explained: "I definitely feel stress, yeah. It's like, we've been incredibly difficult and painful the last several months." When asked why he was sleeping on the factory floor, Musk responded: "Because I don't have time to go home and shower." But the choice was not merely practical. Speaking to [Bloomberg](https://www.bloomberg.com/news/features/2018-07-13/-the-last-bet-the-company-situation-q-amp-a-with-elon-musk?ref=ceo.com), Musk revealed a deeper motivation: "The reason I sleep on the floor was not because I couldn't go across the road and be at the hotel, it was because I wanted my circumstance to be worse than anyone else at the company on purpose." At the [Baron Investment Conference](https://x.com/StartupArchive%5F/status/1959583652364386459?ref=ceo.com), Musk elaborated further: "I was living in the factory in Fremont and the one in Nevada for three years straight. That was my primary residence. I'm not kidding. Literally. I slept on a couch, and at one point a tent on the roof, but for a while there, I was just sleeping under my desk which was out in the open in the factory." He explained his reasoning: "I slept on the floor under my desk so that during shift change, the entire team could see me. This is important because if the team thinks their leader is off somewhere having a good time, drinking Mai Tais on a tropical island, it's demoralizing. Since the team could see me sleeping on the floor during shift change, they knew I was there. That made a huge difference, and they gave it their all." "I don't believe like people should be experiencing hardship while the CEO is, like, off on vacation," he [told CBS](https://www.esquire.com/uk/latest-news/a19752253/elon-musk-sleeping-floor-tesla/?ref=ceo.com). ## Values Made Visible Musk has been explicit about what he believes matters most. As he once reflected: "I thought about the things that will truly affect humanity. I came up with three: the internet, sustainable energy, and space travel." His famous mantra captures his philosophy of commitment: "When something is important enough, you do it even if the odds are not in your favor." In a [60 Minutes interview](https://www.youtube.com/watch?v=23GzpbNUyI4&t=1s&ref=ceo.com), he elaborated: "There are just times when something is important enough and you believe it enough that you do it in spite of fear. It's like, people shouldn't think, 'Well, I feel fear about this and therefore I shouldn't do it.' It's normal to feel fear. Starting SpaceX, I thought the odds of success were less than 10 percent, and I just accepted that actually, I'd probably just lose everything, but that maybe we'd make some progress if we could just move the ball forward." Walter Isaacson, his biographer, described how Musk organized his physical workspace to match his priorities: "When redesigning the factory, Musk put the cubicles for the engineers right on the edge of the assembly lines, so they would see the flashing lights and hear the complaints whenever one of their design elements caused a slowdown. Musk often corralled the engineers to walk up and down the lines with him. His own open desk was in the middle of it all, with no walls around him, and it had a pillow underneath so he could spend the night when he wanted." Musk himself has [described this principle](https://www.cnbc.com/2018/04/11/elon-musk-says-he-is-sleeping-on-tesla-factory-floor-to-save-time.html?ref=ceo.com): "I always move my desk to wherever, well, I don't really have a desk, actually. I move myself to wherever the biggest problem is in Tesla." ## The Cost of Alignment This level of focus comes with significant tradeoffs. Musk has fathered at least 14 children with multiple women. His first wife, Justine Wilson, wrote that even when he was at home, he was preoccupied with work. He told the [New York Times](https://www.nytimes.com/2020/07/25/style/elon-musk-maureen-dowd.html?ref=disconnect.blog) in 2020, after having a child with Grimes, that she had "a much bigger role than me" in raising their son. In an interview at South by Southwest, when asked about his children, Musk said: "Kids are awesome, and everybody in the audience should have kids." However, he then added that he doesn't see his kids much, saying, "I do email while I'm with my children. I keep a nanny around so they don't kill each other." Musk himself has acknowledged the toll. Reflecting on Tesla's production challenges, he said: "Model 3 production was three years of hell, some of the really worst years of my life, frankly. I still have mental scar tissue from those three years, as do many." In conversation with Isaacson, Musk spoke ruefully about his patterns: "At the beginning of 2022, after a year marked by SpaceX making thirty-one successful rocket launches, Tesla selling close to a million cars, and him becoming the richest man on Earth, Musk spoke ruefully about his compulsion to stir up dramas. 'I need to shift my mindset away from being in crisis mode,' he told me, 'which it has been in for about fourteen years now, or arguably most of my life.'" ## The Question for the Rest of Us The point of examining Musk is not to hold him up as a model to emulate. Most of us do not want to live this way. Most of us should not live this way. The cost is real and the casualties are significant. The point is to notice the alignment. Musk has achieved what most people never do: complete coherence between stated values and lived attention. He says his companies and their missions matter most, and then he lives as though they do. This forces a question back on us. Do we have that coherence? Or do we claim one set of values while our attention reveals another? You might say your family matters most. Does your attention reflect that? You might say your health is a priority. Does your calendar agree? You might say you value creativity, or service, or faith, or friendship. Where does your mind actually rest when you have a free moment? Musk's example is extreme, but the principle is universal. Your attention is your confession. Your calendar is your creed. ## The Limits of the Case Study There is something important to acknowledge here. Musk's alignment comes at a cost that most people would find unacceptable. His children do not have a fully present father. His relationships have fractured repeatedly. His public behavior has grown increasingly controversial. Alignment is not the same as wisdom. Coherence between values and attention does not mean you have chosen the right values in the first place. Musk has mastered a version of personal leadership. He leads himself with remarkable discipline toward the goals he has set. But personal leadership is not just about alignment. It is also about choosing well. What should occupy your ultimate concern? What deserves your worship? These are questions Musk has answered for himself. His answer is work, mission, legacy, and the future of the species. Your answer might be different. Your answer probably should be different. ## The Takeaway Study Musk not to copy him but to learn from the clarity of his example. He shows what it looks like to live without a gap between stated values and lived attention. Then turn the lens on yourself. Where does your attention actually rest? What do you think about when nothing demands your thoughts? What would an honest observer conclude that you worship, based solely on how you spend your time? The goal is not to work 120 hours a week. The goal is to know yourself. To close the gap between what you say matters and what actually occupies your inner life. That is personal leadership. That is what it means to master yourself before you try to lead anyone else. Where your attention rests shows what you worship. Musk knows what he worships. Do you? ### Where your attention rests URL: https://www.ceo.com/blog/where-your-attention-rests/ Last updated: 2026-08-18T00:28:52.000Z Soren Kierkegaard taught that where your attention rests shows what you worship. Your ultimate concern, the place your mind returns to again and again, reveals your true values. Not the values you claim in conversation or post on social media, but the ones that actually govern your life. This is a challenging idea because it bypasses the comforting stories we tell ourselves. We show our values not through words but by what fills our inner world. Who we are actually being. There was a time when what I told people was the most important thing in life wasn't what occupied most of my time and thoughts. I could articulate beautiful priorities, meaningful commitments, a clear hierarchy of what mattered. But my calendar told a different story. My anxiety told a different story. The constant pull of my attention toward work, toward the next event, toward whatever crisis demanded my focus, told a different story. I’d spend time with my kids, but I wouldn't be fully present. Even though being a father matters more to me than anything, there was always somewhere else I needed to be, no matter where I was. I lived with constant anxiety and worry. But if you asked me what my priorities were, I would have given you a great answer that my calendar couldn’t back up. The gap between stated values and lived attention is where personal leadership either succeeds or fails. You cannot lead others, not really, until you've learned to lead yourself. And you cannot lead yourself until you've honestly examined where your attention actually goes. I now rarely attend what I call “vanity events,” and have reoriented my calendar to reflect my values. This wasn't a single decision but a gradual reckoning with the truth that Kierkegaard identified centuries ago. What you think about when you don't have to think about anything reveals your true self. This Thanksgiving, I spent the night building gingerbread houses with my kids, unconcerned about anything other than being present, fully in the moment. Not worrying about what needed to be done at work, what the future might hold, or whatever else needed worrying about. Just frosting, candy, laughter, and presence. John Mayer has a song called "The Age of Worry" that I often send to my kids (well, I send them [Yebba’s cover](https://www.youtube.com/watch?v=x1ya5YigHok&ref=ceo.com)) as a reminder to myself as much as for them. The song captures something essential about our current moment. We live in an age that manufactures worry, that profits from our scattered attention, that rewards constant availability and punishes presence. The song asks a simple question: why should I care about worry? It encourages us to be friends with what we are, to give ourselves permission to change our minds, to act our age in an age that seems designed to keep us perpetually anxious. The path to personal leadership runs directly through this territory. You cannot lead from a place of fragmented attention. You cannot inspire others while your own mind races toward the next obligation. You cannot build something meaningful if you're never fully present to the work or the people in front of you. Mastering personal leadership means taking an honest inventory of your attention. Where does your mind go when you wake up at 3 a.m.? What occupies your thoughts during a quiet moment? When you're with the people you claim to love most, where is your attention actually resting? Perhaps most importantly, have you made friends with who you are? The answers to these questions are your real values. Everything else is just words. ### Sam Altman and the evolution of OpenAI URL: https://www.ceo.com/blog/sam-altman-and-the-evolution-of-openai/ Last updated: 2026-08-19T02:33:37.000Z In December 2015, Sam Altman and Elon Musk met over dinner at the Rosewood Hotel in Silicon Valley to discuss a shared concern: artificial general intelligence in the wrong hands could be disastrous. From that conversation, OpenAI was born as a nonprofit with a mission statement that now seems like a relic from another time. The organization stated it would "freely collaborate" with other institutions and researchers by making some of its patents and research open to the public. OpenAI was founded as a non-profit research lab. It was almost like an anti-Big Tech company; it would prioritize principles over profit. It wanted to, as OpenAI put it back then, develop AI tools that would "benefit humanity as a whole, unconstrained by a need to generate financial return." Altman stated in 2015 that they were partly motivated by concerns about AI safety and existential risk from artificial general intelligence. The founding team included luminaries willing to sacrifice lucrative positions elsewhere. OpenAI co-founder Wojciech Zaremba stated that he turned down "borderline crazy" offers of two to three times his market value to join OpenAI instead. A Google employee said he was willing to leave for OpenAI "partly because of the very strong group of people and, to a very large extent, because of its mission." This was the invisible game made visible: a group of people who had defined their purpose clearly enough to resist financial incentives that would have swayed most. --- ## The First Pivot: From Open to Closed The original vision encountered an inconvenient reality: developing cutting-edge AI requires enormous resources. In 2018, two things happened: First, Musk quit the board of OpenAI after he said he invested $50 million, cutting the then-unknown company off from more of the entrepreneur's crucial financial backing. And secondly, OpenAI's leaders grew increasingly aware that developing and maintaining advanced artificial intelligence models required immense computing power, which was incredibly expensive. A year after Musk left, OpenAI created a for-profit arm. The company established a "capped-profit" structure that limited investor returns to 100 times their investment, with a nonprofit board retaining ultimate control. During this pivotal moment of OpenAI, Sam Altman became its CEO. This was the first compromise. Perhaps a necessary one. But it set a pattern. Yet the nonprofit's board and mission still governed the company, creating two competing tribes within OpenAI: adherents to the serve-humanity-and-not-shareholders credo and those who subscribed to the more traditional Silicon Valley modus operandi of using investor money to release consumer products into the world as rapidly as possible in hopes of cornering a market and becoming an industry pacesetter. --- ## The Public Testimony: May 2023 When Altman testified before the Senate Judiciary Committee in May 2023, he presented himself as a leader deeply concerned about the technology his own company was creating. Altman urged lawmakers to regulate artificial intelligence during a Senate panel hearing, describing the technology's current boom as a potential "printing press moment" that requires safeguards. "We think that regulatory intervention by governments will be critical to mitigate the risks of increasingly powerful models," Altman said in his opening remarks. Altman laid out a general three-point plan for how Congress could regulate AI creators. First, he supported the creation of a federal agency that can grant licenses to develop AI models with a certain threshold of capability and can also revoke those licenses if the models don't meet government-set safety guidelines. The testimony was remarkable for how unusual it was: For what might be the first time ever, industry leaders of a new technological revolution are practically begging the government to regulate them. --- ## The Kennedy Exchange: A Revealing Moment One of the most revealing moments of that 2023 hearing came during an [exchange with Senator John Kennedy of Louisiana](https://www.youtube.com/watch?v=RuzLHnWAuMs&ref=ceo.com). Kennedy, known for his folksy directness, cut through the rhetoric to ask practical questions. "Permit me to share with you three hypotheses that I would like you to assume for the moment to be true," Kennedy began. "Hypothesis number one, many members of Congress do not understand artificial intelligence. Hypothesis number two, that absence of understanding may not prevent Congress from plunging in with enthusiasm and trying to regulate this technology in a way that could hurt this technology. Hypothesis number three, that I would like you to assume there is likely a berserk wing of the artificial intelligence community that intentionally or unintentionally could use artificial intelligence to kill all of us and hurt us the entire time that we are dying." Kennedy then asked: "Please tell me in plain English two or three reforms, regulations, if any, that you would implement if you were queen or king for a day..." Altman responded: "Number 1, I would form a new agency that licenses any effort above a certain scale of capabilities and can take that license away and ensure compliance with safety standards." Kennedy followed up: "Would you be qualified to, if we promulgated those rules, to administer those rules?" After Altman said he loved his current job, Kennedy proceeded to ask Altman for suggestions about who else could run such an agency. Then came the exchange that revealed something important about Altman's positioning: "You make a lot of money. Do you?" Kennedy asked. "I make no... I get paid enough for health insurance. I have no equity in OpenAI," Altman replied. "Really?" Kennedy pressed. "That's interesting. You need a lawyer." "I need a what?" Altman asked. "You need a lawyer or an agent," Kennedy quipped. "I'm doing this cuz I love it," Altman responded. The exchange captured something essential: Altman presenting himself as a mission-driven leader, unburdened by financial incentives, asking to be regulated for the good of humanity. It was compelling. Senators were charmed. But Kennedy's attitude perhaps indicated that senators, keen not to leave a transformational new technology almost entirely unregulated like they did during the era of social media, are perhaps over-correcting by being too credulous toward technologists' own views of how their tools should be regulated. "We can't really have the companies recommending the regulators," Gary Marcus, the AI professor, [told TIME](https://time.com/6280372/sam-altman-chatgpt-regulate-ai/?ref=ceo.com) after the hearing. "What you don't want is regulatory capture, where the government just plays into the hands of the companies." [Some observers saw through it.](https://abcnews.go.com/Technology/tech-reporter-breaks-openai-ceos-senate-testimony-potential/story?id=99390944&ref=ceo.com) "Sam Altman went in front of Congress and he said, basically begged them to protect the public from the technology that he is creating, which can seem a little weird if you take it at face value. One of the things that I think is interesting about this, it's actually not unusual for the tech industry to ask to be regulated. That's exactly what we've seen on privacy issues... It gives tech companies a huge advantage if there are laws that they can comply with. That way, if something goes wrong, they can just say, 'Oh well, we were following the rules.'" --- ## The Worst Fear Question During that [same hearing](https://www.techpolicy.press/transcript-senate-judiciary-subcommittee-hearing-on-oversight-of-ai/?ref=ceo.com), Professor Gary Marcus noted something telling. After Altman discussed his concerns about AI's impact on jobs, Marcus observed: "I will note that Sam's worst fear I do not think is employment. And he never told us what his worst fear actually is. And I think it's germane to find out." When pressed, Altman responded: "My worst fears are that... we, the field, the technology, the industry, cause significant harm to the world. I think that could happen in a lot of different ways; it's why we started the company... I think if this technology goes wrong, it can go quite wrong, and we want to be vocal about that. We want to work with the government to prevent that from happening, but we try to be very clear eyed about what the downside case is and the work that we have to do to mitigate that." It was a carefully worded answer. Sincere-sounding. But notably vague about what "significant harm" actually meant, and notably silent about whether the pursuit of competitive advantage and commercial success might itself be a source of that harm. --- ## The Board Crisis: November 2023 Six months after that testimony about the importance of safety and oversight, the board, designed to provide exactly that oversight, fired Altman. On November 17, 2023, at approximately noon PST, OpenAI's board of directors ousted Altman effective immediately following a "deliberative review process". The board concluded that Altman was not "consistently candid in his communications". There was [no single incident](https://www.axios.com/2023/11/21/openai-board-thinking-sam-altman?ref=ceo.com) that precipitated Altman's ouster; rather, a growing sense among the board's majority that they couldn't trust Altman. Although there wasn't some massive recent leap in AI capability that precipitated the move, the board feels its primary job is safely developing ever more capable technology and felt it couldn't fulfill that mission if it couldn't trust what Altman was telling them. Former board member Helen Toner [later provided specifics](https://www.cnbc.com/2024/05/29/former-openai-board-member-explains-why-ceo-sam-altman-was-fired.html?ref=ceo.com): "For years, Sam had made it really difficult for the board to actually do that job by withholding information, misrepresenting things that were happening at the company, in some cases outright lying to the board." One example she gave: When OpenAI released ChatGPT in November 2022, the board was not informed in advance and found out about it on Twitter. Toner also said Altman did not tell the board he owned the OpenAI startup fund. "The two of them suddenly started telling us... how they couldn't trust him, about the toxic atmosphere he was creating," Toner said. "They used the phrase 'psychological abuse,' telling us they didn't think he was the right person to lead the company to AGI, telling us they had no belief that he could or would change." What happened next revealed where the real power lay. Altman was reinstated on November 22 after pressure from employees and investors. Nearly all of OpenAI's 770 employees signed a letter threatening to leave if Altman wasn't brought back. Microsoft, with $13 billion invested, applied pressure. A future OpenAI nonprofit board could decide that OpenAI-the-company wasn't staying true to its mission, and fire its leadership. We say "in theory" because in practice, Altman has made this scenario extremely unlikely. The nonprofit board is now much more tightly under his control. The oversight mechanism designed to keep OpenAI true to its mission had been neutralized. The same man who had told Senator Kennedy he wanted an agency that could revoke licenses had just demonstrated that oversight of his own company could be overridden when it became inconvenient. --- ## The Safety Team Exodus: 2024 The following year, the pattern continued. OpenAI's Superalignment team, created to address the long-term risks of superintelligent AI, was [disbanded](https://www.axios.com/2024/05/17/openai-superalignment-risk-ilya-sutskever?ref=ceo.com) less than a year after its formation. Immediately following the announcement by chief scientist Ilya Sutskever that he was leaving the company after almost a decade, his team partner and one of Time's 100 most important AI figures, Jan Leike, also [announced he was quitting](https://fortune.com/2024/05/15/openai-sam-altman-ilya-sutskever-jan-leike/?ref=ceo.com). "Over the past years, safety culture and processes have taken a backseat to shiny products," Leike said in a thread on X. Leike criticized the ChatGPT maker for failing to invest enough computing resources in "figuring out how to steer and control AI systems much smarter than us." "I joined because I thought OpenAI would be the best place in the world to do this research," Leike wrote on X. "However, I have been disagreeing with OpenAI leadership about the company's core priorities for quite some time, until we finally reached a breaking point." As of last summer, half of the OpenAI staff that once focused on the long-term risks of superpowerful AI had left the company, including cofounder and chief scientist Ilya Sutskever. Nearly 20% of the company now works in sales. --- ## The Testimony Reversal: May 2025 Two years after urging Congress to create an AI licensing agency, Altman returned to Capitol Hill with a [strikingly different message](https://fortune.com/2025/05/08/sam-altman-openai-senate-hearing-testimony-china-ai-regulations/?ref=ceo.com). Sam Altman, CEO of ChatGPT-maker OpenAI, warned at a Senate hearing Thursday that requiring government approval to release powerful artificial intelligence software would be "disastrous" for the United States' lead in the technology. It was a [striking reversal](https://css.washingtonpost.com/technology/2025/05/08/altman-congress-openai-regulation/?ref=ceo.com) of his comments at a Senate hearing two years ago, when he listed creating a new agency to license the technology as his "number one" recommendation to ensure AI was safe. Altman repeatedly [rejected specific calls for regulation](https://www.techpolicy.press/transcript-sam-altman-testifies-at-us-senate-hearing-on-ai-competitiveness/?ref=ceo.com). He said proposals requiring AI developers to vet their systems before rolling them out would be "disastrous" for the industry. Asked about more limited proposals to have the National Institute of Standards and Technology (NIST) set AI standards, Altman replied, "I don't think we need it. It can be helpful." Altman later advocated for "sensible regulation that does not slow us down." There was, however, a notable absence of references to AI safety in Altman's testimony, in stark contrast to his 2023 comments, which mentioned AI safety dozens of times. Remember: this was the same person who had told Senator Kennedy, under oath, that his "number one" priority would be to form an agency that licenses AI efforts and can revoke those licenses. The same person who said he wanted to work with government to prevent AI from causing "significant harm to the world." --- ## The Conversion: From Nonprofit to For-Profit The final step was converting the company in its entirety. When OpenAI was founded in 2015, its mission was clear and ambitious: to develop artificial intelligence that benefits all of humanity, free from commercial constraints. Co-founders Elon Musk and Sam Altman envisioned an organization that would advance digital intelligence for the public good, prioritizing safety and accessibility over profit. However, recent developments reveal that this lofty goal has been abandoned. On 28 October 2025, OpenAI announced a sweeping transformation: the [once non-profit entity is now a for-profit corporation](https://www.ibtimes.com/openais-billion-dollar-pivot-how-sam-altmans-company-went-open-source-open-business-3789003?ref=ceo.com). After nearly a year of negotiations, OpenAI announced that it has [completed its transformation](https://time.com/7328674/openai-chatgpt-sam-altman-elon-musk-timeline/?ref=ceo.com) into a public benefit corporation, with a separate nonprofit Foundation focused on "health and curing diseases" and "technical solutions to AI resilience" holding a $130 billion stake in the for-profit arm. That’s just shy of the $135 billion stake that Microsoft received, which it said represented 27% ownership. The original mission — to develop AI "unconstrained by a need to generate financial return" — had been formally abandoned. --- ## The Equity Question Throughout this transformation, Altman maintained that he held no equity in OpenAI. This was central to his narrative of being motivated by mission rather than money. The same narrative he presented to Senator Kennedy. The answer he gave on stage Thursday, and in March during an [interview with the New York Times](https://www.nytimes.com/2023/03/31/technology/sam-altman-open-ai-chatgpt.html?ref=ceo.com), is that he holds no stake in OpenAI. "I have like wondered if I should, like, just take one share of equity so I never have to answer this question again," Altman said. "This is my childhood dream job," said Altman, 39\. "Getting to work on \[artificial general intelligence\] and...getting to sit in the room with the smartest researchers in the world and go on this crazy adventure, like that is what I always wanted to do." But the no-equity claim became more complicated. Altman recently said he actually [did have some equity in OpenAI](https://techcrunch.com/2024/12/19/sam-altman-once-owned-some-equity-in-openai-through-sequoia/?ref=ceo.com) through a Sequoia fund at one point, a stake he has since sold. And there were other concerns. In May 2024, after OpenAI's non-disparagement agreements were exposed, Altman was accused of lying when claiming to have been unaware of the equity cancellation provision for departing employees who don't sign the agreement. OpenAI CEO Sam Altman [will not receive any equity](https://www.pymnts.com/cpi-posts/sam-altman-to-receive-no-stake-in-openais-new-structure-despite-microsofts-major-investment/?ref=ceo.com) in the company following a sweeping restructuring plan that gives Microsoft a significant ownership stake. The announcement resolves a major debate about OpenAI's development and indicates that Altman will continue to lead the company without holding direct ownership. This is a rare situation for a CEO at the helm of one of the tech industry's most valuable companies. --- ## The Personal Leadership Question What does any of this have to do with personal leadership? Everything. Personal leadership requires knowing your values and living by them. It requires defining success for yourself before external pressures define it for you. It requires the courage to say no to opportunities that conflict with your purpose, even when they're lucrative or prestigious. The question with Altman is not whether he's intelligent or ambitious or capable. He clearly is all three. The question is whether he has defined his values with sufficient clarity to guide decisions when they become hard. Consider the pattern: He co-founded a nonprofit to ensure AI would benefit humanity, then converted it to a for-profit company. He testified before Congress that government licensing of AI would be critical for safety — his "number one" priority if he were "king for a day" — then testified two years later that such licensing would be "disastrous." He told Senator Kennedy he made no money and had no equity because he was "doing this cuz I love it," while the organization he led was laying the groundwork for one of the largest corporate restructurings in tech history. He led an organization whose stated purpose was safety-first AI development, while safety researchers left in droves, saying the company had deprioritized their work. He was fired by a board designed to keep the organization true to its mission, then returned with that board's power effectively neutralized. Each of these could be defended individually. Circumstances change. Competition intensifies. Pragmatism matters. You could argue that Altman was simply adapting to reality, doing what was necessary to keep OpenAI competitive in a rapidly evolving landscape. But that's exactly the point. The question isn't whether these pivots were strategically sound. The question is whether they were anchored in any purpose beyond winning. Whether there was ever a line that wouldn't be crossed. Whether the original mission was a genuine commitment or a useful narrative that could be discarded when it became inconvenient. Clayton Christensen warned that if you don't consciously decide what matters most, you will unconsciously drift into living by someone else's values. You'll optimize for metrics that feel important in the moment but don't add up to anything you actually wanted. OpenAI's metrics look spectacular. The company is valued at hundreds of billions of dollars. ChatGPT has hundreds of millions of users. Altman is one of the most powerful figures in technology. But the mission to develop AI that benefits humanity, unconstrained by financial return? The commitment to safety over speed? The nonprofit governance designed to prevent exactly the kind of profit-driven decision-making that now characterizes the company? The licensing agency he told Senator Kennedy was his top priority? Those are gone. And perhaps they were always going to be gone. Perhaps the original mission was never realistic, given the capital requirements of AI development. Perhaps Altman is simply the CEO who did what needed to be done. But that's a story about corporate strategy. It's not a story about personal leadership. Personal leadership would have looked different. It might have meant walking away when the mission became untenable. It might have meant being honest with the board and public, even when honesty was inconvenient. It might have meant prioritizing the safety team's work even when it slowed product releases. It might have meant testifying consistently before Congress rather than shifting positions to match the political winds. Most importantly, it would have meant defining success in terms that didn't require abandoning the original purpose. --- ## What This Means for You If you're a CEO reading this case study, the point isn't to condemn Sam Altman. He's navigating pressures most of us will never face, making decisions with consequences most of us can't imagine. The point is to see clearly what happens when purpose becomes subordinate to momentum. When the visible game — the metrics, the valuation, the headlines — becomes more real than the invisible game. Altman [once told an interviewer](https://stratechery.com/2025/an-interview-with-openai-ceo-sam-altman-about-building-a-consumer-tech-company/?ref=ceo.com) about his motivation: "I believed before then, I believed then I believe now, that if we could figure out how to build AGI and if we could figure out how to make it a net good force in the world, it would be one of the most exciting, interesting, impactful, positive things anybody could ever do." There's no reason to doubt that he believed this when he said it. The question is whether "make it a net good force in the world" was ever defined clearly enough to guide actual decisions. Whether it was a genuine constraint or an aspiration that could be deferred indefinitely in the name of competitive necessity. This is the work of personal leadership: defining your values with enough precision that they actually constrain your behavior. Not someday. Today. Because if you wait until the pressure is on to figure out what you actually believe, you'll discover that the pressure has already decided for you. ### Free people, not followers, create community URL: https://www.ceo.com/blog/free-people-not-followers-create-community/ Last updated: 2026-08-18T00:43:36.000Z The great Irish playwright George Bernard Shaw was at a party one night when the host approached him and asked, "Are you enjoying yourself, Mr. Shaw?" He replied, "Yes, and that's the only thing I'm enjoying." Shaw's quip exposes the emptiness of gatherings where people are present but not genuinely connected. The room filled with opportunists seeking advantage, not equals coming together to produce something meaningful. Most communities begin with the belief that everyone involved has earned their place at the table. This is why newly formed communities achieve significant success right from the start. Members value each other's company and share a clear perspective on reality: each individual matters, but no one matters more than anyone else. There is no anxiety, pressure, fear, or struggle for power. Everyone involved is free. Success alters this reality. People from outside begin to care about what's happening. Now there are stakes, reputations to uphold, power that must be exercised. Some individuals start to be perceived as mattering more than others. Credit must be given, egos must be stroked, land must be defended. Inevitably, the spirit shifts. Nothing has truly changed, but reality can't compete with perception. The community comes to be seen as a small group of leaders trying to control everything and everyone else. The character and motivations of its founders come under scrutiny. Competitors emerge from this perception alone, promising the same results with new leaders and purer motives. This cycle of growth and collapse manifests across all areas of human organization. Think of a startup humming with ideas until investors arrive, egos swell, and the founding team splinters. Think of political parties that win by mobilizing free individuals, then lose when they shift to top-down control. The pattern repeats because success creates the very hierarchies that success was built to escape. Why does this happen? A person who depends on others for access, validation, or happiness will eventually want to break free. Nobody wants to be a follower. Nobody wants to be mid-conversation, watching their partner's eyes drift over their shoulder for someone better. Followers aren't free. They rely on others, surrendering control of their destiny. That's what sheep do. So what does a free individual actually look like in a community? Watch how they behave in a room. They ask questions without calculating what the answer might do for them. They share credit instinctively, not strategically. They can disagree with the most powerful person present without their voice changing. They stay in conversations that offer them nothing. They leave conversations that offer them everything but feel hollow. They treat the intern and the CEO with the same quality of attention, not because they should, but because status simply isn't how they organize the world. A community of such people is rare and difficult to sustain. But I've learned that the cycle of collapse is not inevitable. It can be interrupted, though not by rules or structures. It gets interrupted by vigilance, by leaders willing to notice the moment when perception begins to calcify into hierarchy, and then to actively dismantle it. This means giving away credit before anyone thinks to assign it. It means treating every new member as a founder, not a follower. It means refusing to defend territory, even territory you built. The community that lasts is the one that keeps asking: Are we still equals here? And when the honest answer is no, it has the courage to tear down whatever wall has been built and start again. ### The invisible game URL: https://www.ceo.com/blog/the-invisible-game/ Last updated: 2026-08-18T00:32:13.000Z Every CEO plays two games. The first game is visible. It shows up in revenue numbers, headcount, market share, and press coverage. It's the game investors track, competitors watch, and LinkedIn celebrates. When people ask how your company is doing, they're asking about the visible game. The second game is invisible. It happens in the space between your alarm going off and your feet hitting the floor. It's what you do with fear. How you respond when a key executive quits. Whether you tell the truth in a board meeting when a comfortable half-truth would suffice. It's the conversation you have with yourself at 2 AM when the company's future feels uncertain, and you're not sure you're the right person to lead it. The invisible game is where leadership actually lives. Most CEO content focuses exclusively on the visible game. Strategy frameworks. Growth tactics. Fundraising playbooks. Management systems. That content has its place. But it misses something essential: the visible game is downstream of the invisible game. How you lead yourself determines how you lead everything else. This is personal leadership. --- I learned this the hard way. At the beginning of the COVID-19 pandemic, when no one knew what was happening, what to do, or what the future held, I convinced myself that the future of Utah rested on my shoulders and those of Silicon Slopes, the nonprofit I lead. It obviously didn't. But somehow I believed it did. I brought together the top leaders in Utah to develop a plan to ensure the state not only met this challenge but also emerged stronger. COVID-19 became Silicon Slopes' sole mission for the next 18 months. We were the first to launch testing in Utah County. We sent private planes to China to get PPE equipment to Utah hospitals and first responders. We worked closely with the state's top government officials, held press conferences with the governor, and fought political battles we had no business being part of. It felt like I was on the home page of The Salt Lake Tribune every day. Those stories were never positive, which was awkward because I was also on The Salt Lake Tribune's board at the time. Every story they wrote about me required a disclaimer at the bottom. From the outside, it probably looked like leadership. Decisive action. Visible impact. The kind of thing that gets celebrated and criticized. I experienced plenty of both. From the inside, I was lost. I had lost my sense of purpose. Not just the organization's purpose, but my personal purpose. I was careening from crisis to crisis, battle to battle, without ever taking the time to ask myself the questions that actually mattered: Why am I doing this? Should I be doing this? What's my purpose? This affected my personal life profoundly. Ways I won't get into here, as they're still too painful to publicly confront. My physical health deteriorated. I started having heart problems. I spent three weeks in the hospital and never told anyone outside of my immediate family. I'm proud of the work Silicon Slopes did during this time. I genuinely believe Utah came out better because of it. But I'm not proud of the leader I was during this period. I was winning the visible game while losing the invisible one. It's taken me years to get my physical and mental health back from that time. Years. And I attribute all of it to an overall lack of purpose, clarity, and personal leadership. --- There's a John Hartford song called ["In Tall Buildings"](https://www.youtube.com/watch?v=ymfcEcoIcXE&ref=ceo.com) that I think about often. It traces the arc of a life lived on autopilot. A young person is taught by others, shaped by expectations, given a suit, and sent off to work. The song's narrator says goodbye to sunshine, to flowers, to everything that matters, because he must not be late. He has somewhere to be. Then retirement comes, and he wonders what happened in all those years between. Where did the life part go? Hartford wrote it as a folk song, but it's really a warning. It's about the quiet tragedy of drifting through decades without ever asking whether you're going where you actually want to go. Of being so busy making payments and keeping schedules that you never notice you've traded your life for something you never consciously chose. Every time I hear it, I think about how many CEOs are living some version of this story. Not in tall buildings, necessarily. Maybe in corner offices or on Zoom calls or in first-class seats crossing time zones. But the same drift. The same surrender of agency. The same slow accumulation of years spent optimizing for metrics that someone else defined. And then one day, wondering what happened. --- I’ve chosen the word "personal" deliberately. Not self-leadership. Not self-improvement. Personal leadership. The distinction matters. "Self" implies a universal standard. A checklist of habits and practices that work for everyone. Wake up at 5 AM. Meditate for twenty minutes. Journal three pages. Exercise before breakfast. Batch your email. Optimize your calendar. If you do these things, you will become an effective leader. That's not how leadership works. That's not how people work. Personal leadership starts from a different premise: there is no single right way to lead yourself, just as there is no single right way to lead a company. What works for one person may not work for another. The morning routine that transforms one CEO might leave another depleted. The decision-making framework that brings clarity to one leader might create confusion for another. But this doesn't mean anything goes. There is no single right way to be a leader, but there are wrong ways. Ways that compromise your integrity. Ways that burn out the people around you. Ways that achieve external success while hollowing out internal meaning. Ways that get you somewhere you never actually wanted to go. Personal leadership is about finding your way. Not the way. Your way. That requires knowing something most people never slow down long enough to discover: what you actually value, and what you're actually trying to build with your life. --- Clayton Christensen spent his career studying disruption and innovation at Harvard Business School. But his most enduring work might be a short book called [*"How Will You Measure Your Life?"*](https://www.amazon.com/How-Will-Measure-Your-Life/dp/0062102419/?ref=ceo.com) It began as a lecture he gave to graduating students. Christensen noticed something troubling: many of his former classmates had become wealthy and professionally successful by every conventional measure. But they were also unhappy, divorced, or ethically compromised. A few were in prison. These were brilliant people. They could analyze markets, build companies, and create shareholder value. But they had never applied that same rigor to the most important question: what would make their lives meaningful? Christensen's argument was simple but devastating. If you don't consciously decide what matters most, you will unconsciously drift into living by someone else's values. You'll optimize for metrics that feel important in the moment but don't add up to anything you actually want. You'll achieve success after success after success, and then one day you'll look around and wonder how you ended up here. You'll have built a career that looks impressive from the outside but feels hollow from the inside. You'll have climbed a ladder leaning against the wrong wall. This is the trap. And CEOs are particularly susceptible to it. --- During COVID, I fell into that trap completely. I was optimizing for metrics that seemed important. Testing sites launched. PPE delivered. Press conferences held. Problems solved. Each day brought new crises, and I showed up to meet them. I was doing things that mattered. Important things. But I had never stopped to ask the deeper questions. What was I actually trying to build with my life? What did success mean to me, not to the press, not to my peers, but to me? What would make all of this effort worth it? Without those answers, I had no foundation. No way to decide what deserved my energy and what didn't. No way to know when to push forward and when to step back. No filter for the endless demands competing for my attention. So I said yes to everything. I fought every battle. I treated every crisis as equally urgent. And I slowly destroyed my health, some relationships, and my sense of self in the process. It's hard to be physically and mentally well if you don't have any reason to be so. --- Running a company generates tremendous pressure to optimize for legible outcomes. Revenue. Growth rate. Valuation. These numbers are visible and comparable. They let you measure yourself against peers. They give you something concrete to point to when someone asks how you're doing. The danger is that these metrics become the goal rather than a byproduct. You start making decisions to improve the numbers rather than to build something you believe in. You hire people who will make the board happy rather than people who share your values. You take the company in directions that maximize valuation but minimize meaning. And because everyone around you is measuring success the same way, no one questions it. The drift happens gradually. The compromise is incremental. Each individual decision seems rational, even responsible. Then you achieve everything you thought you wanted, and you feel nothing. Hartford's narrator makes all the payments and then wonders what happened. Most CEOs I know are making their own version of those payments. Board expectations. Investor demands. Market pressures. The relentless need to grow, to scale, to win. They're so focused on not being late that they never ask where they're actually going. --- Christensen suggested that your life needs a purpose as clear as a company's mission. Not a vague sense of wanting to do good or be successful. A real articulation of what you're trying to accomplish with your finite time on earth. Most companies, even mediocre ones, can tell you what they're trying to do. They have mission statements, strategic plans, and quarterly objectives. There's clarity about what success looks like. Most people, even exceptional ones, cannot answer the same question about their own lives. They have never defined what success means to them personally. They have absorbed definitions from their parents, their culture, their industry, their peers. They are running hard toward finish lines they never chose. Personal leadership begins with a different kind of work. Before you can lead yourself effectively, you have to know where you're trying to go. Before you can make good decisions, you have to know what you're deciding for. Before you can resist the drift toward someone else's values, you have to know your own. This isn't easy work. It's not the kind of thing you can knock out in an afternoon strategic planning session. It requires honest examination of what you actually care about, not what you think you should care about. It requires separating your own ambitions from the expectations you've absorbed from others. It requires admitting that some of the goals you've been chasing might not be yours at all. --- Personal leadership is personal because the answers are different for everyone. One CEO's purpose might be building generational wealth for their family. Another's might be solving a problem they find genuinely important. Another's might be proving something to themselves. Another's might be creating an environment where talented people can do their best work. None of these is inherently better than the others. But each implies a different set of decisions, trade-offs, and definitions of success. The work is figuring out which one is yours. Once you know that, everything else gets simpler. Not easier, but simpler. Decisions that seemed complicated become clearer when you know what you're optimizing for. Opportunities that seemed attractive become less tempting when they don't align with your actual purpose. The visible game becomes something you play with intention rather than desperation. This is the invisible game. It doesn't show up in your pitch deck or your annual report. No one will ask you about it at conferences. Your investors don't care about it, at least not directly. But it determines everything else. If you can't lead yourself, you can't lead others. And you can't lead yourself until you know where you're going. --- This is why I've decided that CEO.com should focus its content, events, and platform on personal leadership. There are plenty of magazines, podcasts, and influencers you can follow that offer business models, strategies, and insights. That content exists. It's everywhere. What doesn't exist, at least not in a way I've found meaningful, is a resource dedicated to the invisible game. The inner work that makes the outer work sustainable. The questions that actually matter but rarely get asked. I wish a resource like this had existed when I was going through my own purpose crisis. It would have changed everything for me and for the organization I led. That's why we're building it now. Not to give you a formula or a system or a set of best practices that work for everyone. To help you find your way. That means asking questions most business content avoids. What do you actually value? What are you willing to sacrifice, and what isn't negotiable? How do you want to feel about your life when you look back on it? What would make all the hard work worth it? The goal is to help you avoid Hartford's lament. To make sure that when you look back on the years between, you know exactly what happened. Because you chose it. Because it was yours. These are personal questions. The answers are personal too. That's the point. That's why we call it personal leadership. ### Octopus Energy US CEO Nick Chaset: Inside the biggest energy shift since the 1970s URL: https://www.ceo.com/episodes/octopus-energy-us-ceo-nick-chaset/ Last updated: 2026-08-24T20:09:55.000Z # Nick Chaset wants America to manufacture its energy, not drill for it Nick Chaset's workday starts when London wakes up. Slack begins pinging around 5:30 a.m. California time, and he spends the next hour or so catching up with colleagues at Octopus Energy's UK headquarters. At 7:00, he clocks out for what he calls dad time: breakfast, school lunches for his two kids, a quick walk with the dog. By 8:00 he's back at his desk, running the American arm of one of the world's largest clean energy companies. That arm is smaller than you'd guess. Octopus Energy Group employs more than 10,000 people globally. Its US business has about 50. "We're small but mighty," Chaset said on the CEO.com podcast. "We lean heavily on a lot of our capabilities and colleagues, particularly in Europe, to help us punch above our weight." They picked an interesting moment to be small. US electricity demand, flat for most of the last 40 years, is suddenly growing at rates the industry hasn't seen since the 1960s and '70s. Chaset puts the figure at 5 to 15 percent a year in some regions, driven overwhelmingly by AI data centers. He estimates the AI buildout now accounts for somewhere around 30 percent of US GDP growth, and he's dismissive of the idea that it's a bubble. "There's just going to be a never-ending demand for compute," he said. Autonomous cars, sensors in every home, video everywhere. All of it runs on electricity. His answer to that demand is a phrase he repeats like a mission statement: manufacture energy instead of extracting it. "At some point in time, when you're drilling, the hole is going to be empty, and you're going to run out," he said. Solar panels, batteries, wind turbines, and even nuclear plants are manufactured goods, which means they follow manufacturing economics: costs fall, efficiency compounds, supply scales. Drilling doesn't work that way. If that sounds like California talking, consider where Octopus planted its US flag. The company is headquartered in Houston and sells electricity in Texas, which has no major state renewable incentives and is nonetheless the country's largest solar and battery market. Chaset brings this up constantly, including in a [Newsweek interview](https://www.newsweek.com/octopus-energy-clean-renewable-power-nick-chaset-interview-2026207?ref=ceo.com) shortly after he took the job, where he argued the grid is a physics problem more than a policy problem. Supply has to match demand no matter who's in the White House, and right now solar and batteries are the fastest things anyone can build. Chaset came up on the policy side of that physics problem. Before Octopus, he spent seven years as CEO of Ava Community Energy, the Bay Area community energy agency he helped found. Before that he was chief of staff to the president of the California Public Utilities Commission and a special advisor to Governor Jerry Brown. Octopus brought him on in 2024 to run North America, and [that December he took over the US retail business](http://www.energychoicematters.com/stories/20250102a.html?ref=ceo.com), weeks before a new administration arrived promising to drill. The regulatory years left a mark. Electricity, he points out, sits in the same category as water: you cannot function without it, which is why most of it is sold by regulated monopolies rather than at whatever price the market will bear. Working inside the regulator showed him the trade-off that defines the whole industry, protecting ratepayers today versus investing for the demand of a decade from now. He's now on the other side of the table, selling to the utilities he used to oversee. That's the quieter half of Octopus's US strategy. In Texas, it competes directly for customers. Everywhere else, it partners with the incumbent utilities, offering the technology and consumer playbook it built in Europe. The pitch is flexibility: pay customers to let their thermostats, EVs, and home batteries respond to prices. Charge the car at 1:00 a.m. instead of 9:00 p.m. and the grid saves money, the customer saves money, and the car is still full in the morning. In 2026 that strategy turned into deals, including a [partnership with virtual power plant operator Voltus](https://www.voltus.co/press/voltus-octopus-energy-launch-partnership?ref=ceo.com) and an [agreement to take a majority stake in Uplight](https://octopus.energy/press/octopus-energy-takes-majority-stake-in-uplight-to-scale-flexible-digitalised-grids-across-north-america/?ref=ceo.com), a platform that already works with more than 85 North American utilities. This month the company launched [Octopus Charge](https://electrek.co/2026/08/18/one-free-app-now-puts-211000-ev-chargers-in-one-place/?ref=ceo.com), an app that rolls 211,000 public EV chargers into one account. Octopus also eats its own cooking on AI. Every customer call and email runs through a system that digests the customer's entire history and drafts suggested responses, which Chaset says has cut email response times from a day to about an hour. A separate tool his team nicknamed Billy scores every single call for qualities like empathy. In the old world, a manager might spot-check one call in 50\. Billy hears them all. The most revealing part of the conversation had nothing to do with the grid. About ten years ago, Chaset's youngest daughter was born with a serious congenital heart defect. He was working in the governor's office and kept coming in anyway, angry and distracted, until his boss stopped him. "He said, Nick, I need you to go home. I need you to take two months, be with your family.'" What stuck with Chaset wasn't just the kindness. His boss was telling him he was failing his team by showing up half-present. "You want to care for your team, but you want people to be accountable for each other," Chaset said. "And you cannot care for somebody if you're not accountable to them." Asked the question that closes every CEO.com interview, who gave you a chance, Chaset named Michael Picker, the former CPUC president who hired an ambitious, admittedly raw young staffer and let him sit in rooms full of people who knew more than he did. Listen first, Picker told him, but don't be scared to talk. ```chapters 00:00:00 Introduction and the Core of High-Performing Teams 00:01:18 Manufacturing Energy Versus Extracting It 00:03:29 Engaging Consumers with Smart Price Signals 00:05:58 Octopus Energy's Growing Presence in the US 00:06:41 Integrating AI into Customer Service Operations 00:09:26 Navigating Unprecedented Growth in Energy Demand 00:12:11 Lessons on Affordability from the CPUC 00:14:00 How Tariffs Impact the Energy Supply Chain 00:16:00 Balancing Care and Accountability in Leadership 00:17:34 The Power of Mentorship and Taking Chances ``` ```vtt WEBVTT 00:00:01.920 --> 00:00:10.000 Coffee<00:00:02.399> is<00:00:02.639> for<00:00:02.879> leaders.<00:00:04.000> [Music]<00:00:06.400> You<00:00:06.560> want<00:00:06.720> to<00:00:06.879> care<00:00:07.040> for<00:00:07.200> your<00:00:07.359> team,<00:00:08.000> but<00:00:08.240> you<00:00:08.400> want<00:00:08.559> people<00:00:08.800> to<00:00:08.960> 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00:12:28.560 --> 00:12:36.720 Uh,<00:12:28.880> but<00:12:29.040> we<00:12:29.200> got<00:12:29.360> to<00:12:29.440> get<00:12:29.600> more<00:12:29.760> efficient.<00:12:30.560> We<00:12:30.800> got<00:12:30.959> to<00:12:31.040> lean<00:12:31.279> into<00:12:31.519> new<00:12:31.760> technology<00:12:32.720> because<00:12:33.040> that's<00:12:33.360> the<00:12:33.519> only<00:12:33.680> way<00:12:33.839> we're<00:12:34.079> going<00:12:34.160> to<00:12:34.800> keep<00:12:35.040> people's<00:12:35.519> bills<00:12:36.399> uh<00:12:36.560> in 00:12:36.720 --> 00:12:40.480 line<00:12:36.880> with<00:12:37.120> what<00:12:37.279> they<00:12:37.440> can<00:12:37.519> afford.<00:12:38.000> And<00:12:38.160> you've<00:12:38.320> had<00:12:38.480> a<00:12:38.560> front<00:12:38.880> row<00:12:38.959> seat<00:12:39.120> to<00:12:39.279> this<00:12:39.440> for<00:12:39.600> a<00:12:39.760> while. 00:12:40.480 --> 00:12:48.000 The<00:12:40.880> whole<00:12:41.200> energy<00:12:42.000> 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forefront<00:19:07.440> of<00:19:07.600> an<00:19:07.840> industry<00:19:08.160> that,<00:19:08.799> like<00:19:08.960> you<00:19:09.120> said,<00:19:09.280> we<00:19:09.520> haven't<00:19:09.679> seen<00:19:09.760> a<00:19:10.000> boom<00:19:10.160> in<00:19:10.480> since 00:19:10.640 --> 00:19:13.360 the<00:19:10.880> 60s<00:19:11.200> or<00:19:11.440> 70s,<00:19:11.840> which<00:19:12.080> is<00:19:12.160> super<00:19:12.480> exciting. 00:19:13.360 --> 00:19:15.760 Uh,<00:19:13.679> appreciate<00:19:14.000> you<00:19:14.240> coming<00:19:14.400> on.<00:19:15.120> Thanks,<00:19:15.440> Clint. 00:19:15.760 --> 00:19:21.310 Really<00:19:16.000> appreciate<00:19:16.320> the<00:19:16.559> opportunity<00:19:16.799> to<00:19:16.880> be<00:19:17.039> here. 00:19:21.310 --> 00:19:30.799 [Music] 00:19:30.799 --> 00:19:34.320 you<00:19:31.440> star<00:19:31.840> shine<00:19:32.240> bright<00:19:32.799> up. 00:19:34.320 --> 00:19:36.320 Yeah. ``` ### The moral framework of AI: Lessons from Sam Altman's Tucker Carlson interview URL: https://www.ceo.com/blog/the-moral-framework-of-ai-lessons-from-sam-altman-s-tucker-carlson-interview/ Last updated: 2026-08-18T00:49:00.000Z In a recent wide-ranging [interview with Tucker Carlson](https://www.youtube.com/watch?v=5KmpT-BoVf4&ref=ceo.com), OpenAI CEO Sam Altman offered rare insights into the moral complexities facing AI leaders today. The conversation touched on fundamental questions that extend far beyond technology: Who decides what's right and wrong for systems that influence billions of people? How do we handle unprecedented power? And what happens when the stakes involve life and death? These questions echo debates that have occupied Western thought for millennia, from Aristotle's exploration of virtue ethics to contemporary struggles over democratic legitimacy. What makes Altman's position unique is that he wields vast moral influence over global discourse while operating largely outside the traditional frameworks that have historically grounded ethical authority. ## The ancient question of moral authority Perhaps the most striking aspect of the interview was Carlson's persistent questioning about where AI's moral framework originates. When pressed about who makes the ethical decisions that shape ChatGPT's responses, Altman's answer was both honest and philosophically problematic: "I view myself more as like a... I think our user base is going to approach the collective world as a whole. I think what we should do is try to reflect the moral... collective moral view of that user base." This utilitarian approach would likely have troubled Thomas Aquinas, who argued in his [*Summa Theologica*](https://www.amazon.com/Summa-Theologica-Thomas-Aquinas-Volumes/dp/0870610635?ref=ceo.com) that moral law derives from eternal law — God's rational governance of creation. For Aquinas, human reason could discern natural law, but ultimate moral authority rested in divine command, not popular consensus. The idea that moral truth could emerge from aggregating user preferences would have struck him as fundamentally misguided, confusing what people happen to want with what they ought to want. Aristotle, too, would have found Altman's approach insufficient. In the [*Nicomachean Ethics*](https://classics.mit.edu/Aristotle/nicomachaen.html?ref=ceo.com), Aristotle argued that moral knowledge comes through the cultivation of virtue and practical wisdom (\_phronesis\_), developed through experience and proper education. Simply polling masses of users — many of whom may lack moral development — cannot substitute for the deliberative process of those who have cultivated ethical expertise. As Carlson noted, "all through history... people always deferred to what they conceived of as a higher power." Yet here we have a technology that will shape global discourse, and its moral foundation rests on the aggregated preferences of its users — a kind of democratic relativism without democratic institutions or the philosophical grounding that makes democracy defensible. ## The liberal dilemma of conflicting values The problem becomes more complex when considering global diversity. When Carlson asked whether Altman would be comfortable with an AI that reflected the average African view on gay marriage, Altman acknowledged the tension: "I think individual users should be allowed to have a problem with gay people... I probably have more comfort than you with... space for people to have pretty different moral views." This response reveals a characteristically liberal approach reminiscent of John Locke's arguments in his [*Letter Concerning Toleration*](https://historyofeconomicthought.mcmaster.ca/locke/toleration.pdf?ref=ceo.com). Locke advocated for broad tolerance of different beliefs, arguing that civil magistrates should not impose religious orthodoxy. However, Locke's tolerance had limits — he excluded atheists and Catholics from full toleration, believing they posed threats to social order. Altman faces a similar but more complex challenge: his system must somehow accommodate radically different moral frameworks while still making coherent decisions. Unlike Locke's political theory, which could rely on shared Christian assumptions about natural law, AI systems must navigate between worldviews that share no common foundation. The deeper issue is whether Altman's relativistic approach can sustain itself. If all moral views are equally valid inputs into the system, how does one make principled distinctions? When he acknowledged that ChatGPT would treat suicide differently for terminally ill adults versus depressed teenagers, he was implicitly appealing to moral principles that transcend user preferences—principles he struggled to articulate or defend. ## The sociological challenge of collective conscience Émile Durkheim's analysis of social solidarity offers another lens for understanding Altman's challenge. In [*The Division of Labor in Society*](https://durkheim.uchicago.edu/Summaries/dl.html?ref=ceo.com), Durkheim argued that modern societies face a fundamental problem: as they become more complex and individualistic, they lose the "collective conscience" that once provided shared moral foundations. Traditional societies maintained moral coherence through what Durkheim called "mechanical solidarity" — shared beliefs, values, and practices enforced through social pressure. Modern societies develop "organic solidarity" based on interdependence and specialization, but this comes at the cost of moral consensus. Altman's approach of reflecting collective user preferences represents an attempt to recreate Durkheim's collective conscience through technological means. However, this effort faces the same challenges Durkheim identified: in a pluralistic society, there may be no genuine collective conscience to discover. The aggregation of individual preferences is not the same as a shared moral framework. Moreover, Durkheim warned that rapid social change could lead to "anomie" — a breakdown of social norms that leaves individuals without moral guidance. AI systems that adjust their values based on user feedback may actually accelerate this process, creating moral instability rather than the coherent guidance that societies need. ## The weight of unprecedented power What makes these philosophical questions urgent is the scale of Altman's influence. As he acknowledged, "every day hundreds of millions of people talk to our model." This represents a concentration of communicative power unprecedented in human history. No religious leader, political figure, or media mogul has ever had the ability to simultaneously influence the thoughts and decisions of so many people across so many cultures. Aristotle's conception of political authority in the [*Politics*](https://classics.mit.edu/Aristotle/politics.html?ref=ceo.com) assumed that moral leadership operated within bounded communities where virtue could be cultivated through shared practice and deliberation. The polis was small enough that citizens could know one another and engage in meaningful ethical discourse. Altman exercises influence over a global community too vast for such deliberation. Similarly, Aquinas's understanding of political authority assumed rulers would be accountable to natural law and, ultimately, to God. Temporal power was legitimate only insofar as it served the common good and respected moral truth. Altman faces no such external constraints beyond user feedback and market forces. Altman seemed to grasp this weight, admitting he hasn't "had a good night of sleep since ChatGPT launched." When Carlson pressed him on whether he thinks about "the future of the world" hanging in the balance, Altman's response was telling: "I don't actually worry about us getting the big moral decisions wrong... What I worry... what I lose most sleep over, is the very small decisions we make about a way a model may behave slightly differently." This insight reveals how contemporary power operates differently from traditional forms of authority. Rather than making explicit moral pronouncements, AI systems shape behavior through countless micro-decisions that gradually influence how people think about the world. This makes accountability more difficult and moral evaluation more complex. ## Life, death, and algorithmic decisions The conversation took a darker turn when discussing suicide and AI's role in life-or-death decisions. Altman revealed a statistic that should concern every leader: "There are 15,000 people a week that commit suicide, about 10% of the world talking to ChatGPT. That's like 1,500 people a week that are talking... to ChatGPT and still committing suicide." The ethical complexity deepened when discussing assisted suicide in countries where it's legal. Altman seemed open to the idea that ChatGPT might present suicide as an option for terminally ill patients in jurisdictions where it's legal, while maintaining strict prohibitions for depressed teenagers. This utilitarian calculation would have horrified Aquinas, who viewed suicide as always morally impermissible because it violated natural law and usurped God's authority over life and death. From an Aristotelian perspective, the question would be whether suicide could ever be consistent with human flourishing — and the answer would likely be no, since it prevents the possibility of developing virtue and achieving one's potential. The discussion became even more fraught when addressing the death of former OpenAI employee Suchir Balaji, who had publicly criticized the company's use of copyrighted material before his death was ruled a suicide. While Altman maintained it was suicide, the case highlights how AI companies operate under intense scrutiny, where every tragedy becomes fodder for conspiracy theories about corporate power. ## Transparency and democratic accountability Perhaps the most actionable insight from the interview was Carlson's call for transparency in the moral framework of AI. He compared AI to religion, noting that "the beauty of religions is they have a catechism that is transparent. I know what the religion stands for." His point was that AI systems guide human thinking and decision-making in ways that are often invisible to users. This echoes Locke's argument in the [*Second Treatise of Government*](https://www.gutenberg.org/files/7370/7370-h/7370-h.htm?ref=ceo.com), which posits that legitimate political authority requires the consent of the governed, a condition that is impossible without transparency regarding how power is exercised. Citizens cannot consent to what they do not understand. Altman pointed to OpenAI's "model spec" as their attempt at transparency, but acknowledged it will need to become "very long and very complicated" as the technology spreads globally. This raises questions about whether technical documentation can provide the kind of moral clarity that democratic societies need. Durkheim would likely have seen this as symptomatic of modern society's broader challenge: how to maintain social cohesion when traditional sources of moral authority have weakened. Technical specifications cannot replace the shared narratives and practices that have historically bound communities together. ## The path forward The interview reveals several critical areas where AI companies and policymakers must act, informed by lessons from philosophical tradition: **Virtue-Based Leadership**: Drawing on Aristotelian insights, we require mechanisms to ensure that those wielding AI's moral influence have developed practical wisdom through experience and education, in addition to technical expertise. **Natural Law Foundations**: Drawing on Aquinas's framework, AI systems should acknowledge certain moral principles as non-negotiable rather than treating all values as equally valid inputs to be aggregated. **Democratic Legitimacy**: Inspired by Locke's political theory, we need institutions that can provide genuine consent and accountability for AI's moral choices, going beyond user feedback to include structured democratic input. **Social Solidarity**: Building on Durkheim's insights, AI governance should actively work to strengthen rather than fragment social bonds, perhaps by promoting shared values rather than simply reflecting existing preferences. Sam Altman's interview revealed both the enormous challenges and the urgent need to get AI ethics right. The technology has already accumulated influence that rivals traditional sources of moral authority, yet it operates without many of the institutional safeguards that philosophers have argued are necessary for legitimate governance. The conversation also highlighted something more fundamental: we are living through a transition in how moral authority is constructed and distributed in human society. The old models — religious institutions, democratic governments, cultural traditions—are being supplemented and sometimes superseded by algorithmic systems that shape how billions of people think about the world. The philosophical tradition offers both warnings and guidance for this transition. Aristotle's emphasis on virtue, Aquinas's grounding in natural law, Locke's insistence on consent and transparency, and Durkheim's analysis of social solidarity all point toward the need for more robust institutional frameworks around AI governance. Whether this transition strengthens or weakens human flourishing may depend on how seriously we take these philosophical insights. The technical capabilities of AI will continue advancing regardless of our ethical frameworks. The question is whether we can develop the institutional wisdom to guide that power toward genuinely beneficial ends — ends that reflect not just what people happen to prefer, but what reason and tradition suggest they ought to value. For leaders in any industry, the lesson is clear: as technology becomes more powerful, the moral questions become more urgent, not less so. The future may depend on how well we answer them — and whether we have the philosophical humility to learn from those who have grappled with these questions before us. ### GoAERO Founder & CEO Gwen Lighter: Life-saving drones URL: https://www.ceo.com/episodes/goaero-founder-ceo-gwen-lighter/ Last updated: 2026-08-24T20:24:51.000Z # Gwen Lighter is building the aircraft that gets there Traffic was the problem. Gwen Lighter's father had chest palpitations; the family called 911, and the ambulance came fast. Then it hit traffic. Lighter followed in her own car, repeating two words at the windshield. "I remember in my car trailing the ambulance saying over and over again, please move, please move, please move," she told the CEO.com Podcast. "I thought at that moment that this was ridiculous, that anybody could be in this situation when we did not need to be." Her father made it in time. Many people do not. Researchers at the [Maine Rural Health Research Center](https://www.ruralhealthresearch.org/publications/1596?ref=ceo.com) count 4.5 million Americans living in "ambulance deserts," more than 25 minutes from the nearest ambulance station. That figure describes an ordinary day, before a flood in Texas or a fire in Los Angeles or an earthquake in Turkey takes the roads out entirely. Lighter's answer is [GoAERO](https://www.goaeroprize.com/?ref=ceo.com), a competition offering more than $2 million in prizes to the teams that can build an Emergency Response Flyer: a safe, portable, autonomy-enabled aircraft that carries a first responder to a person in need, carries the person out, or carries supplies in when nothing with wheels can move. She is not an aerospace engineer. She [went to Brown, then Harvard Law, worked at Morgan Stanley, and clerked for a federal judge](https://www.leadersmag.com/issues/2025.1%5FJan/WL/LEADERS%5FLighter%5FGoFly%5FPrize%5FGoAERO.html?ref=ceo.com). Her first recruiting target was Boeing, where she met then-CTO John Tracy. Boeing stayed through two of his successors, Greg Hyslop and Howard McKenzie, and introduced her to NASA, where she worked with [Robert Pearce](https://www.nasa.gov/people/robert-a-pearce/?ref=ceo.com), who led the agency's aeronautics research, and the team at NASA Ames. RTX chief scientist Michael Winter and Geoff Hunt followed. The partner list is [now more than 20 organizations long](https://www.goaeroprize.com/post/goaero-stage-2-prototype-winners-press-release?ref=ceo.com). Her account of how a lawyer assembled that room: "The underlying mission resonates with everyone. When I was behind that ambulance, it was me at that moment, but you understand it. Your colleagues understand it. Your friends understand it." The competition runs in three stages. Stage 1 was the paper stage; in February 2025, GoAERO [awarded $500,000 to 11 winners and 14 U.S. university teams](https://www.prnewswire.com/news-releases/goaero-global-emergency-response-flyer-competition-announces-500-000-of-awards-to-innovators-worldwide-with-support-from-boeing-nasa-rtx-and-honeywell-302373663.html?ref=ceo.com) supported by NASA. Stage 2 was the prototype stage; in December 2025, [eight teams from the United States, United Kingdom, Germany, and the Netherlands split $320,000](https://www.goaeroprize.com/post/goaero-stage-2-prototype-winners-press-release?ref=ceo.com) for aircraft that actually flew. More than 200 teams from 85 countries remain in the field, and new teams can still enter. Stage 3 is the full-scale flyer, which ends at a multi-day Fly-Off at NASA Ames Research Center in the San Francisco Bay Area, [scheduled for April 2027](https://www.herox.com/goaero?ref=ceo.com). The Fly-Off has three missions. Productivity is back and forth, back and forth: fire retardant runs, repeated rescues. Maneuverability is in and out, up and down, tight corners. Adversity is high winds, low visibility, bad weather. "Whatever Mother Nature throws at us," Lighter said. There is a [$1 million grand prize, an Autonomy Prize, an RTX Disruptor Prize, and a prize for each mission](https://www.herox.com/goaero?ref=ceo.com). A team can chase all of them or one. Lighter wants many winners, not one. "Some may be better at the adversity missions, and some may be the best in autonomy," she said. "We have given to the world these first stages of these flyers to then be worked upon and improved and tested and bettered." Asked what the teams are struggling with, she declined to rank the difficulties. "Everything is tough. It would be difficult to build something that stays on the ground. We're adding gravity to that." This is her second competition. Since 2017, she has run [GoFly](https://goflyprize.com/?ref=ceo.com), which drew [854 teams and 3,800 innovators from 103 countries](https://goflyprize.com/updates/?ref=ceo.com) to build personal flying devices, jetpacks, and flying motorcycles among them, before flying taxis were dinner conversation. The technology that made GoFly possible now feeds GoAERO: batteries that keep improving, sense-and-avoid systems from the drone world, 3D metal printing that lets a garage team build what once required Boeing. The aircraft may be the easier half. Emergency response has no single buyer. Purchasing happens at the municipal level, at FEMA, and differently in Spain than in Australia. So Lighter is on a plane most weeks, meeting governments, regulators, and universities. "We're trying to bring everyone together to not only create these emergency response flyers, but also to create the framework for them to be able to be deployed, so that after the competition they're eventually in use and they are saving lives," she said. Her staff has stayed with her from GoFly to GoAERO. "We've never lost anybody," she said. "It's still the same team, because we so enjoy working together, because we believe in the mission." Every CEO.com Podcast conversation ends with the same question, built on the belief that the chances one gives matter as much as the chances one takes. Asked who gave her a chance, Lighter did not name an investor. She named her father, who tries to leave every room better than he found it. Her mother, who made her strong. Her children, her team, the teams building the aircraft, the people at the FAA. "I go through life with people who give us chances to do well and to do good," she said. "We don't always get it right, but we certainly try." ```chapters 00:00:00 The Origin of Go Aero 00:03:49 Partnering with Aerospace Giants 00:06:15 Three Stages of the Competition 00:09:53 From GoFly to Go Aero 00:11:45 A Day in the Life 00:13:48 Building a Mission Driven Community 00:16:08 Technical Challenges and Innovations 00:22:17 Giving and Receiving Chances ``` ```vtt WEBVTT 00:00:06.852 --> 00:00:08.618 Gwen,<00:00:07.157> thank<00:00:07.318> you<00:00:07.398> so<00:00:07.510> much<00:00:07.719> for<00:00:07.815> coming<00:00:08.056> on<00:00:08.201> the<00:00:08.233> show. 00:00:08.859 --> 00:00:09.613 It's<00:00:09.003> great<00:00:09.244> to<00:00:09.324> have<00:00:09.581> you. 00:00:09.661 --> 00:00:21.345 You're<00:00:09.822> the<00:00:09.918> CEO<00:00:10.447> and<00:00:10.544> founder<00:00:11.025> of<00:00:11.186> Go<00:00:11.571> Aero,<00:00:11.988> which<00:00:12.165> is<00:00:12.325> a<00:00:12.550> $2+<00:00:13.417> million<00:00:14.299> global<00:00:14.717> 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I<00:04:43.902> believe<00:04:44.080> his<00:04:44.307> title<00:04:44.533> is<00:04:44.630> the<00:04:44.711> Associate<00:04:45.131> Administrator<00:04:46.085> of<00:04:46.247> Aviation<00:04:46.813> at<00:04:46.958> NASA. 00:04:47.201 --> 00:04:48.704 He's<00:04:47.378> head<00:04:47.443> of<00:04:47.670> all<00:04:47.768> the<00:04:48.014> aviation<00:04:48.523> there. 00:04:49.163 --> 00:05:04.713 We<00:04:49.491> work<00:04:49.606> a<00:04:49.623> tremendous<00:04:49.918> amount<00:04:50.370> tremendous<00:04:50.819> amount<00:04:51.669> with<00:04:52.552> NASA<00:04:53.113> Ames<00:04:54.958> and<00:04:57.140> the<00:04:57.381> team<00:04:58.023> there,<00:04:58.488> the<00:04:58.680> center<00:04:59.065> director,<00:04:59.932> so<00:05:00.253> many<00:05:00.493> different<00:05:00.750> people<00:05:01.071> who<00:05:01.231> are<00:05:01.472> just<00:05:02.194> the,<00:05:02.579> the<00:05:02.836> biggest<00:05:03.237> brains<00:05:03.718> and<00:05:03.863> the<00:05:04.039> best<00:05:04.360> hearts. 00:05:05.323 --> 00:05:16.826 We<00:05:05.547> have<00:05:05.804> been<00:05:06.109> very<00:05:06.366> fortunate<00:05:07.248> to<00:05:07.408> be<00:05:07.649> able<00:05:07.954> to<00:05:08.195> work<00:05:08.451> with<00:05:08.788> RTX,<00:05:10.296> chief<00:05:10.537> scientist<00:05:11.243> there<00:05:11.740> Michael<00:05:12.222> Winter,<00:05:12.863> especially<00:05:14.372> Jeff<00:05:14.693> Hunt,<00:05:15.094> who<00:05:15.174> has<00:05:15.350> been<00:05:15.511> a<00:05:15.591> huge<00:05:16.072> supporter<00:05:16.714> there. 00:05:17.340 --> 00:05:33.734 We<00:05:17.597> have<00:05:17.982> had<00:05:19.922> the<00:05:20.307> good<00:05:20.547> fortune<00:05:21.845> of<00:05:22.165> being<00:05:22.630> able<00:05:23.127> to<00:05:23.591> partner<00:05:25.450> with<00:05:25.690> some<00:05:26.395> of<00:05:26.972> the<00:05:28.078> best<00:05:28.334> engineers<00:05:28.975> on<00:05:29.119> the<00:05:29.215> planet<00:05:30.257> to<00:05:30.497> do<00:05:32.083> both<00:05:32.420> well<00:05:33.125> and<00:05:33.461> good. 00:05:34.006 --> 00:05:40.383 And<00:05:34.423> so<00:05:35.448> we<00:05:36.730> are<00:05:36.826> so<00:05:37.067> thankful<00:05:38.172> to<00:05:38.268> have<00:05:38.493> those<00:05:38.733> opportunities<00:05:39.310> to<00:05:39.550> work<00:05:39.710> with<00:05:39.855> our<00:05:40.015> partners. 00:05:40.431 --> 00:05:47.209 And<00:05:40.576> frankly,<00:05:41.216> every<00:05:41.713> day,<00:05:43.219> we<00:05:43.396> are<00:05:43.556> bringing<00:05:43.940> on<00:05:44.117> new<00:05:44.357> partners<00:05:44.998> and<00:05:45.158> new<00:05:45.478> amazing<00:05:46.039> teams<00:05:46.440> around<00:05:46.744> the<00:05:46.904> world. 00:05:47.626 --> 00:05:58.559 Right<00:05:47.966> now,<00:05:49.810> we<00:05:50.215> have<00:05:50.716> signed<00:05:51.186> up<00:05:51.671> over<00:05:52.335> 200<00:05:52.966> teams<00:05:53.775> from<00:05:54.098> 85<00:05:54.843> different<00:05:55.150> countries<00:05:55.959> that<00:05:56.380> are<00:05:56.510> participating<00:05:57.672> in<00:05:57.914> Go<00:05:58.156> Aero. 00:05:58.882 --> 00:06:12.572 So<00:05:59.285> we<00:05:59.673> think<00:06:00.238> that<00:06:00.560> at<00:06:00.738> the<00:06:01.045> end<00:06:01.319> of<00:06:01.464> the<00:06:01.609> competition,<00:06:03.090> there<00:06:03.202> will<00:06:03.605> be<00:06:04.651> numerous<00:06:05.295> types<00:06:06.325> of<00:06:06.744> first<00:06:07.227> response<00:06:07.935> flyers,<00:06:08.821> emergency<00:06:09.416> response<00:06:09.964> flyers,<00:06:10.994> and<00:06:11.397> that's<00:06:11.574> a<00:06:11.654> good<00:06:11.815> thing<00:06:12.057> for<00:06:12.202> all<00:06:12.234> of<00:06:12.363> us. 00:06:13.959 --> 00:06:15.212 Yeah,<00:06:14.441> yeah,<00:06:14.778> for<00:06:14.922> sure. 00:06:15.404 --> 00:06:18.360 And<00:06:15.806> the<00:06:15.902> difference<00:06:16.288> you're<00:06:16.368> making<00:06:16.770> here<00:06:17.171> is<00:06:17.669> unbelievable. 00:06:18.408 --> 00:06:22.327 So<00:06:18.633> give<00:06:18.810> us<00:06:18.954> a<00:06:19.019> sense<00:06:19.259> for<00:06:19.500> what<00:06:19.693> stage<00:06:20.416> of<00:06:20.561> the<00:06:20.721> prize<00:06:21.508> are<00:06:21.669> we<00:06:21.910> in<00:06:22.070> right<00:06:22.247> now? 00:06:22.954 --> 00:06:27.596 So<00:06:23.355> Clint,<00:06:23.693> we<00:06:24.175> divided<00:06:25.299> the<00:06:25.685> competition<00:06:26.327> into<00:06:26.584> 3<00:06:26.825> different<00:06:27.082> stages. 00:06:27.949 --> 00:06:30.536 And<00:06:28.110> when<00:06:28.255> we<00:06:28.335> say<00:06:28.592> them,<00:06:28.753> you'll<00:06:28.897> say,<00:06:29.154> of<00:06:29.299> course,<00:06:29.716> because<00:06:30.038> it's<00:06:30.198> natural. 00:06:31.162 --> 00:06:33.186 The<00:06:31.307> 3<00:06:31.467> stages<00:06:31.869> are<00:06:32.286> the<00:06:32.431> paper<00:06:32.752> stage. 00:06:33.250 --> 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submissions,<00:06:53.383> are<00:06:53.624> due<00:06:54.041> September<00:06:54.763> 30th. 00:06:55.309 --> 00:06:57.026 So<00:06:55.550> that<00:06:55.790> is<00:06:55.967> certainly<00:06:56.368> coming<00:06:56.834> up. 00:06:57.797 --> 00:07:06.961 We<00:06:57.893> will<00:06:58.053> award<00:06:58.439> those<00:06:58.695> prizes<00:07:00.605> in<00:07:01.023> November,<00:07:02.066> and<00:07:02.306> then<00:07:03.189> we<00:07:03.334> will<00:07:03.494> go<00:07:03.671> into<00:07:03.847> Stage<00:07:04.393> 3,<00:07:04.794> which<00:07:05.035> is<00:07:05.195> the<00:07:05.356> full-scale<00:07:06.319> flyer. 00:07:07.507 --> 00:07:12.532 And<00:07:07.619> so<00:07:07.828> that's<00:07:08.085> when<00:07:08.229> the<00:07:08.326> teams<00:07:08.711> are<00:07:09.032> building<00:07:10.718> their,<00:07:11.039> their<00:07:11.232> full-scale<00:07:11.938> aircraft. 00:07:12.886 --> 00:07:30.725 And<00:07:13.287> that<00:07:13.849> will<00:07:14.491> then<00:07:14.812> take<00:07:15.214> us<00:07:15.535> to<00:07:16.900> the<00:07:17.060> culmination<00:07:18.505> of<00:07:19.228> our<00:07:19.629> Go<00:07:20.031> Aero<00:07:20.352> competition,<00:07:21.476> which<00:07:21.813> is<00:07:22.054> the<00:07:22.134> final<00:07:22.616> fly-off,<00:07:23.499> which<00:07:23.884> is<00:07:24.141> this<00:07:24.527> multi-day<00:07:25.410> event<00:07:25.827> that<00:07:26.052> we<00:07:26.148> just<00:07:26.389> announced<00:07:26.775> we'll<00:07:26.871> be<00:07:27.015> hosting<00:07:27.577> at<00:07:27.754> NASA<00:07:28.300> Ames,<00:07:28.701> which<00:07:28.878> is<00:07:29.023> in<00:07:29.119> the<00:07:29.183> San<00:07:29.376> Francisco<00:07:29.986> Bay<00:07:30.243> Area. 00:07:31.270 --> 00:07:42.957 And<00:07:33.132> We<00:07:33.918> at—<00:07:34.671> in<00:07:34.895> conjunction<00:07:35.360> with<00:07:35.456> NASA<00:07:35.841> Ames<00:07:36.338> and<00:07:36.418> with<00:07:36.562> our<00:07:36.722> partners,<00:07:37.460> we<00:07:37.540> will<00:07:37.684> have<00:07:38.004> all<00:07:38.181> of<00:07:38.325> the<00:07:38.421> teams<00:07:39.158> fly<00:07:40.104> through<00:07:40.986> the<00:07:41.226> 3<00:07:41.867> different<00:07:42.428> missions. 00:07:43.374 --> 00:07:45.665 They<00:07:43.614> are<00:07:44.672> productivity,<00:07:45.537> right? 00:07:45.778 --> 00:07:47.733 Think<00:07:46.034> back<00:07:46.210> and<00:07:46.291> forth,<00:07:46.659> back<00:07:46.819> and<00:07:46.900> forth,<00:07:47.220> back<00:07:47.396> and<00:07:47.477> forth. 00:07:47.797 --> 00:07:58.856 You<00:07:47.941> can<00:07:48.102> imagine<00:07:48.823> in<00:07:48.999> a<00:07:49.224> wildfire<00:07:49.897> setting<00:07:50.666> how<00:07:50.842> it<00:07:50.922> is<00:07:51.147> very<00:07:51.547> important<00:07:51.948> to<00:07:51.980> go<00:07:52.124> back<00:07:52.365> and<00:07:52.445> forth<00:07:53.150> with<00:07:53.903> fire<00:07:54.128> retardant,<00:07:55.410> with,<00:07:56.275> you<00:07:56.308> know,<00:07:57.013> rescuing<00:07:57.574> people<00:07:57.894> that<00:07:58.135> need<00:07:58.439> that,<00:07:58.615> right? 00:07:59.801 --> 00:08:03.760 Also<00:08:00.539> in<00:08:00.923> the<00:08:01.003> floods<00:08:01.420> that<00:08:01.645> we<00:08:01.741> just<00:08:01.869> experienced,<00:08:02.222> experienced<00:08:02.638> in<00:08:02.782> Texas,<00:08:03.327> right? 00:08:03.824 --> 00:08:05.924 To<00:08:03.984> be<00:08:04.209> able<00:08:04.385> to<00:08:04.626> rescue<00:08:05.090> people<00:08:05.411> who<00:08:05.571> need<00:08:05.812> that. 00:08:05.988 --> 00:08:07.158 That's<00:08:06.228> the<00:08:06.308> productivity<00:08:06.805> mission. 00:08:07.911 --> 00:08:10.764 The<00:08:07.991> second<00:08:08.776> mission<00:08:09.658> is<00:08:09.995> maneuverability. 00:08:11.036 --> 00:08:23.297 Think<00:08:11.213> of<00:08:11.357> it<00:08:11.741> in<00:08:11.918> and<00:08:12.142> out<00:08:12.399> and<00:08:12.623> up<00:08:12.879> and<00:08:13.040> down,<00:08:13.841> tight<00:08:14.226> corners,<00:08:14.947> all<00:08:15.267> of<00:08:15.428> that<00:08:15.764> to<00:08:15.924> be<00:08:16.389> able<00:08:16.806> to<00:08:17.287> function<00:08:17.848> in<00:08:18.473> adverse<00:08:18.969> environments,<00:08:19.915> natural<00:08:20.556> disaster<00:08:21.037> kind<00:08:21.229> of<00:08:21.374> climates<00:08:22.079> and<00:08:22.720> all<00:08:22.896> of<00:08:22.976> that. 00:08:23.761 --> 00:08:25.108 And<00:08:23.922> so<00:08:24.162> that's<00:08:24.403> the<00:08:24.435> adversity<00:08:24.899> mission. 00:08:25.460 --> 00:08:29.339 And<00:08:25.540> then<00:08:25.765> the<00:08:26.406> third<00:08:26.742> mission<00:08:27.384> we<00:08:27.784> have—<00:08:27.928> I'm<00:08:28.009> sorry,<00:08:28.185> that's<00:08:28.281> the<00:08:28.425> maneuverability<00:08:29.082> mission. 00:08:29.531 --> 00:08:31.839 The<00:08:29.707> third<00:08:29.948> mission<00:08:30.332> we<00:08:30.429> have<00:08:31.054> is<00:08:31.230> adversity. 00:08:32.159 --> 00:08:41.046 Think<00:08:33.137> high<00:08:33.474> winds,<00:08:34.019> low<00:08:34.116> visibility,<00:08:35.142> bad<00:08:35.463> weather,<00:08:36.265> all<00:08:36.426> of<00:08:36.522> the<00:08:36.682> things<00:08:36.923> that<00:08:37.083> you<00:08:37.228> would<00:08:37.340> expect<00:08:38.190> in,<00:08:38.752> you<00:08:38.784> know,<00:08:38.928> whatever<00:08:39.249> Mother<00:08:39.570> Nature<00:08:39.971> throws<00:08:40.597> at<00:08:40.773> us. 00:08:41.639 --> 00:08:44.110 And<00:08:41.736> so<00:08:41.960> we<00:08:42.057> have<00:08:42.281> prizes<00:08:42.762> for<00:08:43.083> each<00:08:43.276> of<00:08:43.420> those<00:08:43.725> missions. 00:08:44.463 --> 00:08:46.356 We<00:08:44.607> also<00:08:44.784> have<00:08:45.169> an<00:08:45.249> autonomy<00:08:45.971> prize. 00:08:46.773 --> 00:08:48.762 We<00:08:46.933> have<00:08:47.126> an<00:08:47.351> RTX<00:08:47.832> Disruptor<00:08:48.393> Prize. 00:08:49.099 --> 00:08:55.243 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be<00:09:26.057> the<00:09:26.201> best<00:09:26.458> in<00:09:26.602> autonomy<00:09:27.483> and<00:09:27.579> some<00:09:27.820> may<00:09:27.980> be<00:09:28.124> best<00:09:28.380> in<00:09:28.621> urban<00:09:28.861> environments. 00:09:29.310 --> 00:09:31.826 Environments,<00:09:29.710> and<00:09:29.806> some<00:09:29.903> may<00:09:30.063> be<00:09:30.143> best<00:09:30.448> in<00:09:30.704> rural<00:09:31.105> environments. 00:09:32.147 --> 00:09:52.954 But<00:09:32.467> we<00:09:32.932> have<00:09:34.471> given<00:09:35.112> to<00:09:35.673> the<00:09:35.978> world<00:09:36.475> these<00:09:36.780> first<00:09:37.132> stages<00:09:37.902> of<00:09:38.078> these<00:09:38.383> flyers<00:09:39.425> to<00:09:39.745> then<00:09:40.643> be<00:09:42.086> worked<00:09:42.342> upon<00:09:42.951> and<00:09:43.047> improved<00:09:43.689> and<00:09:43.833> tested<00:09:44.474> and<00:09:44.714> bettered<00:09:45.131> and<00:09:45.436> all<00:09:45.596> of<00:09:45.756> that,<00:09:46.189> 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our<00:13:32.443> teams. 00:13:32.910 --> 00:13:34.228 We<00:13:32.990> are<00:13:33.103> mentoring<00:13:33.666> our<00:13:33.875> teams. 00:13:34.454 --> 00:13:35.949 We<00:13:34.598> are<00:13:34.695> bringing<00:13:35.097> on<00:13:35.322> new<00:13:35.483> partners. 00:13:36.310 --> 00:13:47.498 We<00:13:36.486> are<00:13:37.208> helping<00:13:37.610> to<00:13:37.706> create<00:13:38.011> this<00:13:38.252> ecosystem,<00:13:39.697> and<00:13:39.937> we<00:13:40.114> are<00:13:40.274> constantly<00:13:41.254> speaking<00:13:41.960> and<00:13:42.201> doing<00:13:42.843> and<00:13:43.164> going<00:13:43.950> and<00:13:45.652> trying<00:13:45.973> to<00:13:46.069> make<00:13:46.294> this<00:13:46.454> happen<00:13:46.856> for<00:13:47.000> all<00:13:47.097> of<00:13:47.257> us. 00:13:48.140 --> 00:13:56.503 Well,<00:13:48.220> it's<00:13:48.365> really<00:13:48.605> interesting<00:13:48.894> because<00:13:49.183> what<00:13:49.280> you're<00:13:49.825> doing<00:13:50.227> 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the<00:23:51.983> FAA. 00:23:52.711 --> 00:23:57.971 Friends,<00:23:53.358> I<00:23:53.455> don't<00:23:53.747> think—<00:23:54.734> boy,<00:23:55.203> I<00:23:56.757> think<00:23:57.000> I'm<00:23:57.307> very<00:23:57.647> lucky. 00:23:58.036 --> 00:24:04.412 I<00:23:58.133> go<00:23:58.311> through<00:23:58.554> life<00:23:58.861> with<00:23:59.007> people<00:23:59.832> who<00:24:00.463> give<00:24:00.642> us<00:24:00.868> chances<00:24:01.451> to<00:24:02.993> do<00:24:03.238> well<00:24:03.743> and<00:24:03.874> to<00:24:04.053> do<00:24:04.216> good. 00:24:04.893 --> 00:24:09.954 Every<00:24:05.134> day,<00:24:05.359> and<00:24:05.455> we<00:24:05.535> don't<00:24:05.760> always<00:24:06.082> get<00:24:06.242> it<00:24:06.339> right,<00:24:07.367> but<00:24:07.624> we<00:24:09.311> certainly<00:24:09.793> try. 00:24:10.918 --> 00:24:13.022 Gwen,<00:24:11.384> thank<00:24:11.560> you<00:24:11.641> so<00:24:11.978> much<00:24:12.460> for<00:24:12.669> coming<00:24:12.910> on. 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speaking<00:24:24.852> with<00:24:25.030> you,<00:24:25.578> and<00:24:26.143> I<00:24:27.046> look<00:24:27.288> forward<00:24:27.853> to<00:24:28.660> continuing<00:24:29.370> our<00:24:29.466> conversations. 00:24:30.669 --> 00:24:32.353 In<00:24:30.912> the<00:24:31.414> months<00:24:31.802> and<00:24:31.883> years<00:24:32.142> ahead. 00:24:33.016 --> 00:24:33.405 Me<00:24:33.194> as<00:24:33.340> well. 00:24:33.583 --> 00:24:34.262 Thank<00:24:33.761> you<00:24:33.842> so<00:24:34.003> much. 00:24:34.651 --> 00:24:35.007 Take<00:24:34.813> care. ``` ### Landing CEO Bill Smith: Building a $1 billion startup URL: https://www.ceo.com/episodes/landing-founder-ceo-bill-smith/ Last updated: 2026-08-27T21:07:00.000Z # Bill Smith grew a broken business very fast When Bill Smith told his high school counselor he wanted to drop out at 16, the counselor told his parents not to worry. He was already selling cell phones to local businesses in Birmingham, where his father ran companies of his own and answered the thousand questions his son asked about them. Twenty-five years and four companies later, the counselor holds up. Smith sold his first real venture, prepaid card company Insight Card Services, [to Green Dot in 2014](https://www.sec.gov/Archives/edgar/data/1386278/000114036125043160/ef20059923%5F425.htm?ref=ceo.com). With the proceeds, he [bought seven floors of the John Hand Building at auction](https://www.forbes.com/sites/amyfeldman/2022/08/15/this-high-school-dropout-sold-shipt-to-target-for-550-million-his-next-startup-could-be-worth-double/?ref=ceo.com) for $510,000 and launched Shipt out of them. Three years after that, [Target bought Shipt for $550 million in cash](https://corporate.target.com/press/release/2017/12/target-to-acquire-same-day-delivery-platform-shipt,-inc-to-bolster-fulfillment-capabilities?ref=ceo.com). He was 32. Landing, his fourth company, came out of the move that Shipt required. Relocating his family from Birmingham to San Francisco in 2016 meant Craigslist ads, paper applications, and a cashier's check. He founded [Landing](https://www.hellolanding.com/?ref=ceo.com) in 2019 to replace all of that with a network of furnished apartments on flexible leases, and when people left their homes again in the summer of 2020, the business exploded. The growth was hiding something. "The unit economics of the business didn't work," Smith told us on the CEO Podcast. "We had kind of a bad business model, but we had so much growth, and I had all these kinds of smart people, finance people, and everybody could show me a model of how it was going to work." By early 2022, the models had stopped working on paper too, and he pivoted the underlying business hard while leaving the consumer product alone. What he took from it: "The economics have to work from the beginning. They did at Shipt. And at Landing, I thought it was going to be different, but it's never different." The rebuilt company is profitable and, by his account, doubling every six months. In May 2025 it [secured $180 million in debt financing](https://www.phocuswire.com/landing-receives-180M-debt-financing?ref=ceo.com) to grow the portfolio. The offering is built around one idea: travelers want the trust of a hotel with the space of an apartment, so every Landing has the same Wi-Fi password, the same lock on the door, and nothing to do at checkout. No binder of house rules. "I hate the book too." He runs it all on a weekly business review borrowed from Amazon, roughly 250 stats, discussing only what falls outside of normal. Every guest gets an email from his personal address, and he reads the replies. The morning of our conversation, he had been reading Proverbs on wisdom, and it showed up in how he described his executive team: people who question each other's part of the business and receive the correction as a gift. A Landing leadership principle is authenticity. "We shout about our failings and shortcomings, and we're kind of quiet about our wins." He has kept moving since we recorded. In November 2025, his firm, Smith Ventures, [agreed to acquire Green Dot's fintech business for $690 million](https://ir.greendot.com/news-releases/news-release-details/green-dot-corp-announces-strategic-transactions-smith-ventures/?ref=ceo.com). Eleven years after selling his first tech company to Green Dot, he is buying much of it back. Landing's headquarters, meanwhile, [sits in the John Hand Building](https://www.forbes.com/sites/amyfeldman/2022/08/15/this-high-school-dropout-sold-shipt-to-target-for-550-million-his-next-startup-could-be-worth-double/?ref=ceo.com), the one he bought at auction. At CEO.com, we believe the chances one gives are just as important as the chances one takes. Asked who gave him a chance, Smith named his parents, that counselor, the first bank that lent him $500,000, and the executives who put their careers on the line to buy his companies. "Anybody who's reached a level of success has had hundreds and hundreds of people who have helped them along the way. Including all their employees who sacrificed." ```chapters 00:00:00 The Journey to Founding Landing 00:01:49 Building a Startup in Birmingham 00:03:24 Lessons Learned From Shipt to Landing 00:06:06 Defining the Target Market and Consistency 00:07:08 Inside the CEO's Daily Routine 00:08:41 How AI is Transforming Operations 00:11:22 Recruiting and Building an Entrepreneurial Culture 00:14:34 Navigating Competition in the Hospitality Space 00:17:24 Funding Strategies and the Role of Debt 00:20:11 Market Cycles and the AI Bubble 00:24:30 Creating a Seamless Customer Experience 00:26:20 Giving Back and Expressing Gratitude ``` ```vtt WEBVTT 00:00:06.729 --> 00:00:08.373 Bill,<00:00:06.908> thank<00:00:07.070> you<00:00:07.152> so<00:00:07.249> much<00:00:07.461> for<00:00:07.559> coming<00:00:07.868> on<00:00:07.966> the<00:00:08.047> show. 00:00:08.617 --> 00:00:09.479 It<00:00:08.714> means<00:00:08.958> a<00:00:09.007> lot<00:00:09.170> to<00:00:09.251> have<00:00:09.447> you. 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first,<00:00:24.554> and<00:00:24.635> then<00:00:24.748> I'll<00:00:24.958> jump<00:00:25.217> into<00:00:25.443> Landing. 00:00:25.864 --> 00:00:28.973 So<00:00:26.826> I<00:00:27.002> grew<00:00:27.243> up<00:00:27.627> in<00:00:27.707> an<00:00:27.787> entrepreneurial<00:00:28.524> family. 00:00:29.085 --> 00:00:34.806 My<00:00:29.246> father,<00:00:30.111> um,<00:00:30.688> had<00:00:30.928> multiple<00:00:31.329> businesses<00:00:31.889> growing<00:00:32.274> up,<00:00:32.610> and<00:00:32.755> I've<00:00:33.155> always<00:00:33.652> loved<00:00:34.437> business. 00:00:35.014 --> 00:00:39.437 So,<00:00:36.040> um,<00:00:36.440> I'm<00:00:36.536> not<00:00:36.777> into<00:00:37.001> sports,<00:00:37.962> I'm<00:00:38.058> not<00:00:38.283> into<00:00:38.523> any<00:00:38.683> of<00:00:38.715> that<00:00:38.796> kind<00:00:39.004> of<00:00:39.036> stuff. 00:00:39.501 --> 00:00:40.991 My<00:00:39.725> hobby<00:00:40.126> is<00:00:40.286> really<00:00:40.622> business. 00:00:41.103 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opportunity<00:01:43.757> to<00:01:43.902> create<00:01:44.239> a<00:01:44.255> new<00:01:44.559> way<00:01:44.800> for<00:01:44.993> people<00:01:45.185> to<00:01:45.217> live<00:01:45.426> flexibly. 00:01:46.164 --> 00:01:49.067 And<00:01:46.244> that's<00:01:46.468> what<00:01:46.645> led<00:01:46.982> to<00:01:47.351> the<00:01:47.527> ultimate,<00:01:48.072> uh,<00:01:48.329> founding<00:01:48.666> of<00:01:48.730> Landiq. 00:01:49.372 --> 00:01:50.431 Tell<00:01:49.484> me<00:01:49.677> about<00:01:49.934> Birmingham. 00:01:50.496 --> 00:01:52.470 It's<00:01:50.640> a<00:01:50.720> very<00:01:51.058> underrated<00:01:51.700> American<00:01:52.117> city. 00:01:52.663 --> 00:01:54.461 I<00:01:52.743> love,<00:01:52.984> and<00:01:53.129> I<00:01:53.289> love<00:01:53.546> that<00:01:53.690> you're<00:01:54.028> back<00:01:54.349> there. 00:01:54.894 --> 00:01:56.965 And<00:01:55.729> is<00:01:55.794> that<00:01:55.954> headquarters<00:01:56.580> Birmingham? 00:01:57.543 --> 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I<00:02:11.767> always<00:02:12.008> tell<00:02:12.249> people<00:02:12.795> it's,<00:02:13.196> uh,<00:02:13.758> you<00:02:13.790> know,<00:02:14.159> most<00:02:14.400> people<00:02:14.577> haven't<00:02:14.898> been<00:02:15.139> to<00:02:15.219> Birmingham. 00:02:16.022 --> 00:02:22.357 Um,<00:02:17.128> and<00:02:17.946> I<00:02:18.027> tell<00:02:18.267> people<00:02:18.668> that<00:02:19.630> they're,<00:02:20.096> uh,<00:02:20.577> it's<00:02:20.833> way<00:02:21.074> better<00:02:21.379> than<00:02:21.539> they<00:02:21.700> expect. 00:02:23.143 --> 00:02:24.827 We<00:02:23.303> live<00:02:23.496> a<00:02:23.560> fantastic<00:02:24.426> life. 00:02:25.068 --> 00:02:27.506 I<00:02:25.164> live<00:02:25.629> just<00:02:25.950> a<00:02:25.966> few<00:02:26.287> minutes<00:02:26.688> from<00:02:26.928> downtown. 00:02:27.650 --> 00:02:31.853 So<00:02:27.811> my<00:02:27.875> office<00:02:28.308> is<00:02:28.388> in<00:02:28.532> downtown<00:02:28.933> Birmingham,<00:02:29.495> 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cities,<00:02:46.588> as<00:02:46.750> we<00:02:46.912> have<00:02:47.267> kind<00:02:47.898> of<00:02:48.060> a<00:02:48.076> legacy<00:02:48.707> of<00:02:48.804> incredible<00:02:49.338> food. 00:02:50.891 --> 00:02:57.360 And<00:02:51.361> on<00:02:51.458> the<00:02:51.538> business<00:02:51.943> front,<00:02:53.180> there's<00:02:53.357> been<00:02:53.454> a<00:02:53.615> lot<00:02:54.083> of<00:02:54.810> successful<00:02:55.552> SaaS<00:02:56.182> businesses<00:02:56.844> built<00:02:57.166> here. 00:02:57.957 --> 00:03:05.312 I've<00:02:58.296> got<00:02:58.458> a<00:02:58.474> number<00:02:58.861> of<00:02:59.023> friends<00:02:59.329> that<00:02:59.410> have<00:02:59.507> sold<00:02:59.830> businesses<00:03:00.637> for<00:03:01.525> anywhere<00:03:01.912> from<00:03:02.106> a<00:03:02.170> few<00:03:02.300> hundred<00:03:02.563> million<00:03:03.073> to,<00:03:03.221> you<00:03:04.077> know,<00:03:04.226> well<00:03:04.456> over<00:03:04.719> a<00:03:04.802> billion. 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I<00:04:38.234> missed<00:04:39.196> and<00:04:39.356> I've<00:04:39.757> learned<00:04:40.014> it<00:04:40.238> the<00:04:40.319> hard<00:04:40.736> way,<00:04:41.762> is<00:04:42.725> the<00:04:42.821> original<00:04:43.382> business<00:04:43.783> model<00:04:44.024> we<00:04:44.184> had<00:04:44.489> for<00:04:44.666> landing<00:04:45.789> really<00:04:46.751> didn't<00:04:47.136> work. 00:04:48.018 --> 00:04:51.162 The<00:04:48.195> economics,<00:04:49.301> the<00:04:49.398> unit<00:04:49.574> economics<00:04:50.120> of<00:04:50.184> the<00:04:50.280> business<00:04:50.681> didn't<00:04:50.906> work. 00:04:51.242 --> 00:05:06.481 We<00:04:51.339> had<00:04:51.547> a<00:04:51.740> kind<00:04:51.900> of<00:04:52.044> a<00:04:52.766> bad<00:04:53.167> business<00:04:53.568> model,<00:04:54.771> but<00:04:54.916> we<00:04:54.996> had<00:04:55.156> so<00:04:55.349> much<00:04:55.654> growth<00:04:56.279> and<00:04:56.343> I<00:04:56.375> had<00:04:56.680> all<00:04:56.857> these<00:04:57.338> kind<00:04:57.482> of<00:04:57.514> smart<00:04:58.124> people,<00:04:59.006> finance<00:04:59.503> people,<00:05:00.065> and<00:05:00.289> everybody<00:05:00.851> could<00:05:01.027> show<00:05:01.332> me<00:05:01.492> a<00:05:01.509> model<00:05:02.054> how<00:05:02.487> it<00:05:02.631> was<00:05:02.792> going<00:05:03.032> to<00:05:03.177> work<00:05:03.658> and<00:05:03.754> it<00:05:03.899> was<00:05:04.396> going<00:05:04.620> to<00:05:04.701> the<00:05:04.781> moon<00:05:05.198> and<00:05:05.278> we<00:05:05.422> were<00:05:05.519> going<00:05:05.631> to<00:05:05.679> be<00:05:05.759> so<00:05:06.000> profitable. 00:05:07.507 --> 00:05:13.553 And,<00:05:08.005> you<00:05:08.069> know,<00:05:08.181> that<00:05:08.566> didn't<00:05:08.870> really<00:05:09.271> pan<00:05:09.528> out<00:05:09.833> and<00:05:09.929> it<00:05:10.009> became<00:05:10.394> really<00:05:10.650> clear<00:05:11.436> a<00:05:11.532> couple<00:05:11.869> years<00:05:12.094> then<00:05:12.318> in<00:05:12.478> early<00:05:12.655> 2022. 00:05:14.483 --> 00:05:17.193 And<00:05:14.723> we<00:05:14.819> had<00:05:14.980> to<00:05:15.204> pivot<00:05:15.621> our<00:05:15.942> business<00:05:16.263> model<00:05:16.583> pretty<00:05:16.888> hard. 00:05:17.289 --> 00:05:22.837 We<00:05:17.321> didn't<00:05:17.545> really<00:05:17.706> change<00:05:18.107> the<00:05:18.187> consumer<00:05:18.668> offering,<00:05:19.069> but<00:05:19.229> we<00:05:19.309> changed<00:05:20.592> the<00:05:20.897> underlying<00:05:21.458> business<00:05:21.795> model<00:05:22.115> completely. 00:05:23.783 --> 00:05:27.102 And<00:05:24.344> now<00:05:24.745> the<00:05:24.841> business<00:05:25.162> has<00:05:25.322> been<00:05:25.643> completely<00:05:26.269> transformed. 00:05:27.311 --> 00:05:30.165 It<00:05:27.551> is<00:05:27.792> a<00:05:27.888> very<00:05:28.129> profitable<00:05:28.834> model<00:05:29.331> and<00:05:29.411> it<00:05:29.492> works<00:05:29.796> very<00:05:30.037> well. 00:05:30.999 --> 00:05:39.413 But<00:05:31.095> the<00:05:31.239> thing<00:05:31.432> that<00:05:32.202> I<00:05:32.362> learned<00:05:33.164> is,<00:05:33.564> uh,<00:05:34.062> letting<00:05:35.990> a<00:05:36.070> business<00:05:36.456> grow<00:05:36.697> too<00:05:36.874> fast<00:05:37.275> on<00:05:37.356> the<00:05:37.500> wrong<00:05:37.822> model<00:05:38.223> can<00:05:38.384> create<00:05:38.706> a<00:05:38.722> lot<00:05:38.947> of<00:05:39.043> pain. 00:05:40.312 --> 00:05:46.242 And<00:05:41.196> usually<00:05:41.951> somebody<00:05:42.482> can<00:05:42.642> show<00:05:42.964> you<00:05:43.124> how<00:05:43.382> one<00:05:43.687> day<00:05:44.024> with<00:05:44.249> just<00:05:44.522> enough<00:05:44.747> scale,<00:05:45.245> it's<00:05:45.470> going<00:05:45.776> to<00:05:45.872> work. 00:05:46.740 --> 00:05:52.139 And<00:05:46.836> now<00:05:47.720> the<00:05:47.800> way<00:05:47.961> I<00:05:47.977> look<00:05:48.282> at<00:05:48.363> businesses<00:05:49.311> is<00:05:49.713> they<00:05:49.825> need<00:05:50.082> to<00:05:50.275> work<00:05:51.400> very<00:05:51.898> early. 00:05:52.605 --> 00:05:54.356 The<00:05:52.685> economics<00:05:53.264> have<00:05:53.521> to<00:05:53.649> work<00:05:53.810> from<00:05:53.971> the<00:05:54.051> beginning. 00:05:54.855 --> 00:05:55.835 They<00:05:55.031> did<00:05:55.272> it<00:05:55.321> at<00:05:55.417> Shipt. 00:05:56.237 --> 00:05:59.257 So<00:05:56.397> Shipt's<00:05:57.024> business<00:05:57.345> model<00:05:57.924> really<00:05:58.229> worked<00:05:58.550> from<00:05:58.711> the<00:05:58.808> beginning. 00:05:59.836 --> 00:06:03.475 And<00:05:59.932> at<00:06:00.092> Landing,<00:06:00.798> I<00:06:00.814> thought<00:06:01.150> it<00:06:01.294> was<00:06:01.599> going<00:06:01.856> to<00:06:01.920> be<00:06:02.016> different,<00:06:02.481> but<00:06:02.577> it's<00:06:02.801> never<00:06:03.122> different. 00:06:03.683 --> 00:06:06.360 And<00:06:04.004> the<00:06:04.164> unit<00:06:04.356> economics<00:06:05.062> always<00:06:05.382> need<00:06:05.478> to<00:06:05.623> work<00:06:05.799> from<00:06:05.959> the<00:06:06.023> beginning. 00:06:06.809 --> 00:06:08.396 Who<00:06:06.905> is<00:06:07.065> your<00:06:07.226> target<00:06:07.530> market<00:06:07.931> at<00:06:08.027> Landing? 00:06:08.909 --> 00:06:12.804 Today<00:06:09.294> we're<00:06:09.486> really<00:06:09.710> focused<00:06:10.255> on,<00:06:10.897> um,<00:06:11.698> all<00:06:11.875> types<00:06:12.147> of<00:06:12.275> consumers. 00:06:12.900 --> 00:06:15.449 I<00:06:12.916> mean,<00:06:13.381> there's<00:06:13.542> a<00:06:13.702> lot<00:06:13.942> of<00:06:14.039> use<00:06:14.279> cases<00:06:14.664> for<00:06:14.760> our<00:06:14.920> product. 00:06:15.786 --> 00:06:21.910 Uh,<00:06:16.123> when<00:06:16.283> we<00:06:16.363> started,<00:06:16.844> we<00:06:16.988> were<00:06:17.084> focused<00:06:17.565> fully<00:06:17.950> on<00:06:18.110> living,<00:06:18.864> so<00:06:19.794> you<00:06:19.890> 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a<00:06:37.747> hotel<00:06:39.270> and<00:06:39.366> the<00:06:39.463> space<00:06:39.992> of<00:06:40.024> an<00:06:40.104> apartment. 00:06:41.194 --> 00:06:45.330 And<00:06:41.755> that<00:06:41.931> consistency<00:06:42.829> and<00:06:42.973> trust<00:06:43.518> is<00:06:43.695> really<00:06:44.015> the<00:06:44.175> key<00:06:45.041> piece. 00:06:45.618 --> 00:06:55.717 Like<00:06:45.923> every<00:06:46.259> landing<00:06:46.644> you,<00:06:47.285> you<00:06:47.382> check<00:06:47.686> into,<00:06:48.728> the<00:06:48.824> Wi-Fi<00:06:49.225> password's<00:06:49.866> the<00:06:49.946> same,<00:06:50.507> the<00:06:50.588> check-in's<00:06:51.213> the<00:06:51.309> same,<00:06:51.790> the<00:06:51.870> furnishings,<00:06:52.752> everything<00:06:53.297> is<00:06:53.457> exactly<00:06:53.954> the<00:06:54.034> same<00:06:54.371> and<00:06:54.579> very<00:06:55.060> consistent. 00:06:56.358 --> 00:06:57.881 And<00:06:56.439> so<00:06:56.679> that<00:06:56.855> applies<00:06:57.240> to<00:06:57.320> a<00:06:57.384> lot<00:06:57.561> of<00:06:57.641> people. 00:06:58.026 --> 00:07:05.784 It's<00:06:58.154> families<00:06:58.442> that<00:06:58.603> are<00:06:58.683> traveling,<00:06:59.404> it's<00:06:59.564> people<00:06:59.869> that<00:06:59.981> are<00:07:00.109> going<00:07:00.350> somewhere<00:07:00.767> for<00:07:00.927> a<00:07:01.071> week,<00:07:01.552> it's<00:07:02.610> people<00:07:02.931> that<00:07:03.107> are<00:07:03.171> on<00:07:03.315> a<00:07:03.396> work<00:07:03.636> trip<00:07:03.909> for<00:07:04.053> 3<00:07:04.197> or<00:07:04.293> 4<00:07:04.470> months<00:07:04.935> or<00:07:05.079> relocating. 00:07:05.832 --> 00:07:07.868 So,<00:07:06.041> there's<00:07:06.217> a<00:07:06.297> lot<00:07:06.522> of<00:07:06.618> use<00:07:06.842> cases<00:07:07.243> for<00:07:07.323> the<00:07:07.419> product. 00:07:08.445 --> 00:07:08.766 Yeah. 00:07:08.958 --> 00:07:13.158 So,<00:07:09.327> give<00:07:09.439> me<00:07:09.599> a<00:07:09.663> sense<00:07:09.984> for<00:07:10.208> what<00:07:10.385> a<00:07:10.465> typical<00:07:10.946> day<00:07:11.170> looks<00:07:11.411> like<00:07:11.587> for<00:07:11.747> you<00:07:12.068> as<00:07:12.228> CEO<00:07:12.613> of<00:07:12.693> this<00:07:12.853> company. 00:07:13.735 --> 00:07:16.492 It's—<00:07:14.392> well,<00:07:14.617> every<00:07:14.793> day<00:07:15.017> is<00:07:15.114> different<00:07:15.595> and<00:07:15.691> that's<00:07:15.915> what<00:07:16.059> I<00:07:16.075> like. 00:07:17.823 --> 00:07:26.255 I'm<00:07:18.079> constantly<00:07:18.640> kind<00:07:18.945> of—<00:07:19.746> I<00:07:19.794> don't<00:07:20.179> like<00:07:20.404> to<00:07:20.724> just<00:07:22.071> let<00:07:22.247> it<00:07:22.472> go,<00:07:22.888> kind<00:07:23.289> of<00:07:23.594> let<00:07:23.834> business<00:07:24.091> just<00:07:24.315> happen<00:07:24.636> the<00:07:24.732> way<00:07:24.892> it<00:07:25.052> normally<00:07:25.373> does<00:07:25.629> every<00:07:25.790> single<00:07:26.094> day. 00:07:26.431 --> 00:07:29.845 So,<00:07:27.361> I'm<00:07:27.537> very<00:07:27.697> close<00:07:28.018> to<00:07:28.162> the<00:07:28.258> product<00:07:28.755> and<00:07:28.852> I'm<00:07:28.980> very<00:07:29.140> close<00:07:29.461> to<00:07:29.541> the<00:07:29.621> customer. 00:07:30.329 --> 00:07:32.297 And<00:07:30.490> that's<00:07:30.732> something<00:07:31.136> I've<00:07:31.297> done<00:07:31.539> consistently. 00:07:32.443 --> 00:07:37.460 I've<00:07:32.588> been<00:07:32.749> building<00:07:33.072> businesses<00:07:33.572> now<00:07:33.830> for<00:07:35.750> over<00:07:35.912> 25<00:07:36.460> years,<00:07:36.944> which<00:07:37.057> is<00:07:37.202> crazy. 00:07:37.525 --> 00:07:40.607 I<00:07:37.606> just<00:07:37.767> turned<00:07:38.009> 40<00:07:38.800> and<00:07:38.896> I've<00:07:38.977> been<00:07:39.122> doing<00:07:39.300> business<00:07:39.510> for<00:07:39.622> almost<00:07:39.848> 25<00:07:40.348> years. 00:07:41.171 --> 00:07:43.995 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important<00:07:56.109> to<00:07:56.222> our<00:07:56.319> business. 00:07:57.188 --> 00:07:59.465 It's<00:07:57.476> actually<00:07:57.733> something<00:07:58.198> that<00:07:58.310> we<00:07:58.391> took<00:07:58.679> from<00:07:58.920> Amazon. 00:07:59.513 --> 00:08:03.442 So<00:08:00.604> I<00:08:00.764> partnered<00:08:01.165> with<00:08:01.277> a<00:08:01.341> guy<00:08:02.624> named<00:08:02.865> Bill<00:08:03.105> Carr. 00:08:04.372 --> 00:08:10.931 He<00:08:04.693> wrote<00:08:04.869> a<00:08:04.950> book<00:08:05.110> called<00:08:05.415> Working<00:08:05.751> Backwards,<00:08:06.858> and<00:08:07.259> it<00:08:07.596> covers<00:08:07.997> a<00:08:08.061> lot<00:08:08.253> of<00:08:08.397> the<00:08:09.103> kind<00:08:09.247> of<00:08:09.424> Amazonian<00:08:10.081> processes. 00:08:11.027 --> 00:08:18.003 And<00:08:11.140> the<00:08:11.268> weekly<00:08:11.525> business<00:08:11.909> review<00:08:12.086> is<00:08:12.246> one<00:08:12.407> of<00:08:12.471> those<00:08:12.808> 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is<00:08:28.913> key<00:08:29.410> to<00:08:29.651> any<00:08:29.812> business. 00:08:30.357 --> 00:08:34.899 So,<00:08:30.710> I,<00:08:30.774> like,<00:08:31.047> I'm<00:08:31.176> going<00:08:31.336> to<00:08:31.416> New<00:08:31.561> York<00:08:31.737> tomorrow,<00:08:32.925> I'm<00:08:33.037> interviewing<00:08:33.744> 6<00:08:34.065> different<00:08:34.321> executives. 00:08:34.947 --> 00:08:40.532 So,<00:08:35.573> kind<00:08:35.653> of<00:08:35.894> all<00:08:35.990> over<00:08:36.151> the<00:08:36.295> place<00:08:37.595> and<00:08:37.740> like<00:08:37.932> to<00:08:38.253> kind<00:08:38.462> of<00:08:38.783> touch<00:08:39.040> a<00:08:39.104> lot<00:08:39.264> of<00:08:39.297> different<00:08:39.602> things<00:08:39.842> across<00:08:40.083> the<00:08:40.243> business. 00:08:41.206 --> 00:08:46.101 How<00:08:41.447> is<00:08:41.672> AI<00:08:42.009> changing<00:08:43.036> the<00:08:43.132> company,<00:08:43.774> changing<00:08:44.256> your<00:08:44.480> 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I'm,<00:09:20.815> I<00:09:20.895> know<00:09:21.056> Google<00:09:21.281> has<00:09:21.522> a<00:09:21.698> bright<00:09:21.939> future. 00:09:22.325 --> 00:09:26.276 I<00:09:22.421> think<00:09:22.582> they'll<00:09:22.807> actually<00:09:23.064> probably<00:09:23.626> be<00:09:23.851> one<00:09:23.963> of<00:09:24.027> the<00:09:24.108> big<00:09:24.268> winners<00:09:24.589> in<00:09:24.734> AI<00:09:24.991> because<00:09:25.296> they<00:09:25.328> already<00:09:25.537> have<00:09:25.714> all<00:09:25.794> the<00:09:25.891> data. 00:09:26.742 --> 00:09:33.906 Uh,<00:09:27.063> but<00:09:27.706> anyway,<00:09:27.979> so<00:09:28.188> I'm<00:09:28.284> using<00:09:28.525> Grok<00:09:28.750> a<00:09:28.910> ton<00:09:29.633> and,<00:09:29.906> uh,<00:09:30.035> I'm,<00:09:30.549> I'm<00:09:30.774> finding<00:09:31.175> the<00:09:31.256> array<00:09:31.818> of<00:09:32.444> information<00:09:32.862> I<00:09:32.926> can<00:09:33.006> get<00:09:33.103> to<00:09:33.263> so<00:09:33.569> 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country. 00:15:18.781 --> 00:15:26.206 It's<00:15:19.086> the<00:15:19.246> fastest<00:15:19.711> growing<00:15:19.904> segment<00:15:20.288> in<00:15:20.353> hospitality<00:15:21.876> because<00:15:22.117> when<00:15:22.213> people<00:15:22.518> travel<00:15:22.887> now,<00:15:24.041> they<00:15:24.218> want<00:15:24.394> a<00:15:24.458> kitchen,<00:15:25.084> they<00:15:25.244> want<00:15:25.420> a<00:15:25.485> little<00:15:25.661> more<00:15:25.821> space. 00:15:26.286 --> 00:15:28.676 So<00:15:26.944> that<00:15:27.281> segment's<00:15:27.826> grown<00:15:28.051> significantly. 00:15:29.334 --> 00:15:37.208 And<00:15:29.414> then<00:15:29.510> you<00:15:29.654> have<00:15:30.216> alternative<00:15:30.633> accommodations,<00:15:32.236> which<00:15:32.461> people<00:15:32.637> book<00:15:32.862> through<00:15:33.038> Airbnb<00:15:33.600> and<00:15:33.744> VRBO,<00:15:34.562> and<00:15:34.883> they<00:15:35.107> built<00:15:35.348> massive<00:15:35.765> businesses,<00:15:36.326> 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00:26:33.554 --> 00:26:36.219 Well,<00:26:34.260> um,<00:26:35.304> a<00:26:35.320> lot<00:26:35.737> of<00:26:35.801> people. 00:26:36.668 --> 00:26:42.319 Uh,<00:26:37.230> I<00:26:37.326> would,<00:26:37.728> I'd<00:26:38.129> start<00:26:38.450> by<00:26:38.611> saying<00:26:38.916> my<00:26:39.012> parents,<00:26:40.280> you<00:26:40.376> know,<00:26:40.457> I<00:26:40.762> have<00:26:41.339> amazing<00:26:41.821> parents. 00:26:42.383 --> 00:26:54.085 My<00:26:42.624> dad,<00:26:43.507> I<00:26:43.619> don't<00:26:43.988> think<00:26:44.149> he<00:26:44.293> even<00:26:44.470> knew<00:26:44.694> what<00:26:44.775> he<00:26:44.855> was<00:26:45.032> doing,<00:26:45.433> but<00:26:45.674> allowing<00:26:46.139> me<00:26:46.236> to<00:26:46.460> go<00:26:46.573> to<00:26:46.781> work<00:26:47.038> with<00:26:47.183> him<00:26:47.536> and<00:26:48.627> I<00:26:49.189> answer<00:26:49.767> the<00:26:49.928> thousand<00:26:50.313> questions<00:26:50.730> that<00:26:50.843> 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the,<00:27:23.818> uh,<00:27:24.299> the<00:27:24.379> executives<00:27:24.957> that<00:27:25.134> have<00:27:26.081> led<00:27:26.322> deals<00:27:26.659> to<00:27:26.803> buy<00:27:26.980> my<00:27:27.124> companies<00:27:27.751> that<00:27:28.007> put,<00:27:28.328> kind<00:27:28.585> of<00:27:28.633> put<00:27:28.730> their<00:27:28.890> career<00:27:29.195> on<00:27:29.227> the<00:27:29.292> line<00:27:29.613> to<00:27:29.693> buy<00:27:29.998> one<00:27:30.094> of<00:27:30.126> my<00:27:30.399> businesses. 00:27:31.202 --> 00:27:33.176 Um,<00:27:31.764> all<00:27:31.860> of<00:27:31.940> those<00:27:32.181> people<00:27:32.470> have<00:27:32.647> contributed. 00:27:33.289 --> 00:27:43.900 I,<00:27:33.449> I<00:27:33.465> think<00:27:34.413> anybody<00:27:34.910> that's<00:27:35.777> reached<00:27:36.114> a<00:27:36.194> level<00:27:36.516> of<00:27:36.596> success<00:27:38.024> has<00:27:38.346> had<00:27:38.683> hundreds<00:27:39.245> and<00:27:39.389> hundreds<00:27:39.806> of<00:27:39.887> people<00:27:40.192> that<00:27:40.272> have<00:27:40.384> helped<00:27:40.609> them<00:27:40.754> along<00:27:41.010> the<00:27:41.091> way,<00:27:41.588> including<00:27:42.054> all<00:27:42.134> their<00:27:42.295> employees<00:27:42.840> that<00:27:43.001> sacrificed. 00:27:43.964 --> 00:27:47.287 So<00:27:44.767> I,<00:27:45.088> I<00:27:45.200> am<00:27:45.345> thankful<00:27:45.682> for<00:27:45.826> a<00:27:45.891> lot<00:27:46.083> of<00:27:46.147> people<00:27:46.452> that<00:27:46.533> have<00:27:46.693> helped<00:27:46.854> me<00:27:46.950> get<00:27:47.175> here. 00:27:48.054 --> 00:27:49.346 Bill,<00:27:48.296> thanks<00:27:48.603> so<00:27:48.635> much<00:27:48.781> for<00:27:48.926> coming<00:27:49.168> on. 00:27:49.427 --> 00:27:50.040 Really<00:27:49.588> means<00:27:49.895> a<00:27:49.911> lot. 00:27:50.153 --> 00:27:51.655 Congratulations<00:27:50.961> on<00:27:51.025> everything<00:27:51.267> you're<00:27:51.348> building. 00:27:51.752 --> 00:27:52.462 I<00:27:51.913> love<00:27:52.155> landing. 00:27:52.575 --> 00:27:53.512 I<00:27:52.656> think<00:27:52.801> it's<00:27:53.060> genius. 00:27:54.255 --> 00:27:55.369 And<00:27:54.432> best<00:27:54.674> of<00:27:54.739> luck<00:27:54.917> with<00:27:55.062> everything. 00:27:55.960 --> 00:27:56.578 Thank<00:27:56.155> you<00:27:56.236> so<00:27:56.399> much. 00:27:56.643 --> 00:27:57.522 It<00:27:56.708> was<00:27:56.806> great<00:27:56.969> to<00:27:57.050> talk<00:27:57.229> to<00:27:57.376> you. 00:27:57.864 --> 00:27:58.239 Likewise. 00:27:58.369 --> 00:27:59.134 Appreciate<00:27:58.841> it,<00:27:58.890> man. ``` ### Tiger 21 Ceo Tim Daniels: The world's most exclusive peer group URL: https://www.ceo.com/episodes/tiger-21-president-ceo-tim-daniels/ Last updated: 2026-08-24T20:53:56.000Z # Advice without an agenda Tim Daniels almost turned the job down. He had spent 25 years running education companies, work he chose because the only way to make them valuable was to improve somebody's life. Then TIGER 21 came calling in 2019\. "I thought, where's the mission in helping rich people get richer?" he said on the CEO.com Podcast. "This is probably not the right thing for me." He was persuaded, as he put it, to turn over a few more cards. On the other side, he found people who had already won and refused to stop. "They're people who are just never going to be done learning, never be done having a positive impact, never be done improving themselves and their surroundings," he said. Six years later, he runs the place, though he rejects the framing that he built anything. "I didn't really build it. I'm the steward of it." The thing he stewards was [founded in 1999](https://tiger21.com/about-us/?ref=ceo.com) by Michael Sonnenfeldt, an entrepreneur who came into money early and discovered that everyone eager to advise him had an agenda. His answer was a single group of six New York entrepreneurs who had all just sold their companies and would advise each other instead. TIGER 21 now has [more than 1,900 members in 162 groups across 54 cities](https://tiger21.com/about-us/?ref=ceo.com), each member holding at least [$20 million in qualifying net worth](https://tiger21.com/membership-qualifications/?ref=ceo.com). The name is an acronym, The Investment Group for Enhanced Results in the 21st Century, and Daniels said the organization is weighing whether to keep it. The investment framing fit 20 years ago. The actual work, he said, is everything that happens to a whole person after a wealth creation event. Daniels spent his first decade in leveraged buyouts until his mentor, Norm Blake, asked him a question he still repeats: "Do you want to do deals for a living or do you want to get a real job?" He followed Blake to a troubled insurance company, where in his early 30s he was handed the restructuring of a billion-dollar operation and told that if he failed, Blake would have to fire him. He didn't fail. The education career came after, almost by accident, starting with a company that prepped people for state certifications. He ran Wall Street Institute International through a turnaround and a sale to Pearson, served as President of Apollo Global, and oversaw 34 Laureate Education universities in 15 countries from Singapore and then London before he was [named TIGER 21's new CEO in June 2019](https://tiger21.com/insights/forbes-new-ceo-timothy-f-daniels/?ref=ceo.com). Membership runs on five Cs: capital, character, conditions, capacity, and contribution. Capital is the one people fixate on, and the one Daniels talks about least. A group of 12 to 15 needs one real estate person, not twelve, and a member without time to show up leaves an empty chair that costs everyone else. His own test is shorter. Can you benefit from the community, and can you contribute to it? "And candidly, no jerks. It's as simple as that." The part of the job he treats as unfinished business is the network itself. Fifteen people in a group produce 105 possible connections. Seventeen hundred members produce 1.5 million, and Daniels considers most of them untapped. A member in Los Angeles evaluating a Singapore deal can reach a member with a relationship at Temasek. A member's son interning in Denver gets a local number to call if something goes wrong. Even his read on AI comes back to this: let the machines take the mundane work, and the hours people spend at a table together become worth more, not less. He feeds the operation through a habit he started four years ago, offering every first-year member a phone call. About 80 percent accept; the calls eat a quarter of his day, and he estimates 90 to 95 percent of what TIGER 21 invests in the member experience traces back to what he hears on them. He describes himself as an introvert. What members talk about most, more than any investment, is legacy. Some groups run an exercise in which members write their own obituaries and read them to the room. Daniels, 62, holds himself to the same standard and locates his own legacy in his two children, whether they can live purposeful lives outside the shadow of their parents' accomplishments. Asked who gave him a chance, he went back to Blake, who made him secretary of an executive credit committee at 26, judging deals recommended by men 30 years his senior. The committee never once voted against his recommendation. He has spent the years since trying to work the other side of that exchange. "Be the giver and not the recipient," he said. The instinct predates Blake. Daniels went to college at the same time his mother did. She had raised three kids alone on two jobs, enrolled in university in middle age, co-founded a company, and reached financial stability late in life. When people ask if he was the first in his family to go to college, he tells them it was between him and his mother. She was never done improving herself, he said. Neither, apparently, are the people he works for now. ```chapters 00:00:00 Introduction to Tiger 21 00:03:40 Tim's Career Before Tiger 21 00:05:46 The Profile of a Tiger 21 Member 00:09:46 The Five Cs of Membership 00:12:00 Pivotal Moments and Leadership Lessons 00:15:40 Core Values and Legacy 00:21:06 A Day in the Life of a CEO 00:23:34 The Power of the Network Effect 00:26:39 Human Connection in the Age of AI 00:29:16 Giving and Receiving Career Opportunities ``` ```vtt WEBVTT 00:00:06.233 --> 00:00:09.478 Man,<00:00:06.426> I'm<00:00:06.571> super<00:00:06.876> impressed<00:00:07.502> with<00:00:08.563> what<00:00:08.788> you've<00:00:08.964> built<00:00:09.270> here. 00:00:09.992 --> 00:00:11.149 It's<00:00:10.410> incredible,<00:00:10.908> man. 00:00:11.631 --> 00:00:14.121 So<00:00:11.936> let's<00:00:12.274> just<00:00:12.659> get<00:00:12.740> right<00:00:12.900> into<00:00:13.157> it,<00:00:13.382> if<00:00:13.623> that's<00:00:13.928> okay. 00:00:14.346 --> 00:00:16.407 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the<00:08:54.500> investment<00:08:55.046> group<00:08:55.544> was<00:08:55.768> much<00:08:56.089> more<00:08:56.250> applicable,<00:08:57.068> I<00:08:57.165> think,<00:08:57.454> 20<00:08:57.791> years<00:08:58.096> ago. 00:08:58.914 --> 00:09:16.623 What<00:08:59.075> we've<00:08:59.300> come<00:08:59.476> to<00:08:59.701> realize<00:09:00.584> is<00:09:00.825> that<00:09:01.386> You<00:09:01.466> know,<00:09:01.722> we<00:09:01.963> are<00:09:02.267> experts<00:09:02.860> in<00:09:03.068> understanding<00:09:04.286> every<00:09:04.751> aspect<00:09:05.472> of<00:09:05.664> a<00:09:05.728> fundamental<00:09:06.689> transition<00:09:07.330> point<00:09:07.474> in<00:09:07.554> somebody's<00:09:07.971> life<00:09:08.612> when<00:09:08.756> they<00:09:08.916> have<00:09:09.173> had<00:09:09.397> that<00:09:09.637> wealth<00:09:09.894> creation<00:09:10.374> event,<00:09:10.759> or<00:09:11.272> it's<00:09:11.416> accumulated<00:09:12.057> over<00:09:12.233> the<00:09:12.361> 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thing<00:09:53.107> that<00:09:53.203> people<00:09:53.910> most<00:09:54.311> often<00:09:54.809> orient<00:09:55.130> toward<00:09:55.933> Clint,<00:09:56.398> is<00:09:56.896> the,<00:09:57.201> the<00:09:57.795> sort<00:09:57.923> of<00:09:58.084> capital<00:09:58.646> requirement. 00:09:59.785 --> 00:10:02.610 And<00:09:59.865> there<00:10:00.026> is<00:10:00.170> a<00:10:00.203> capital<00:10:00.668> requirement<00:10:01.374> and<00:10:01.455> you<00:10:01.535> can<00:10:01.631> see<00:10:01.792> it<00:10:01.952> on<00:10:02.016> our<00:10:02.193> website. 00:10:02.659 --> 00:10:04.954 It's<00:10:02.835> sort<00:10:03.076> of<00:10:03.734> significant,<00:10:04.537> if<00:10:04.681> you<00:10:04.826> will. 00:10:05.628 --> 00:10:09.561 But<00:10:06.126> we<00:10:06.591> actually<00:10:07.025> orient<00:10:07.474> around<00:10:07.972> 5<00:10:08.437> C's<00:10:08.871> of<00:10:09.080> membership. 00:10:09.962 --> 00:10:14.056 And<00:10:10.075> so,<00:10:10.685> you<00:10:10.717> 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00:26:59.880 --> 00:27:00.874 It<00:26:59.960> affects<00:27:00.521> everybody. 00:27:01.114 --> 00:27:03.054 It<00:27:01.178> affects<00:27:01.435> every<00:27:01.643> person,<00:27:02.044> it<00:27:02.124> affects<00:27:02.381> every<00:27:02.605> business. 00:27:03.407 --> 00:27:23.686 And,<00:27:04.128> you<00:27:04.160> know,<00:27:04.449> I<00:27:04.481> think<00:27:05.010> you,<00:27:05.266> you<00:27:05.346> mentioned<00:27:05.699> something,<00:27:06.212> and<00:27:06.372> I<00:27:06.404> hope<00:27:06.548> you<00:27:06.629> don't<00:27:07.254> mind<00:27:07.430> me<00:27:07.815> quoting<00:27:08.135> you<00:27:08.232> back<00:27:08.472> to<00:27:08.632> you,<00:27:08.873> uh,<00:27:09.514> but<00:27:09.674> that<00:27:09.819> I,<00:27:10.011> I<00:27:10.219> really<00:27:10.396> agree<00:27:10.716> with,<00:27:10.845> especially<00:27:11.293> as<00:27:11.438> it<00:27:11.518> relates<00:27:11.983> to<00:27:12.143> today,<00:27:13.185> is,<00:27:13.682> you<00:27:13.762> 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impressed<00:32:29.828> with<00:32:29.988> you,<00:32:30.309> who<00:32:30.470> you<00:32:30.630> are<00:32:30.710> as<00:32:30.871> a<00:32:30.951> person,<00:32:31.352> the<00:32:31.512> leader<00:32:31.817> you<00:32:31.977> are,<00:32:32.860> and<00:32:32.956> Tiger<00:32:33.277> 21. 00:32:34.223 --> 00:32:35.009 Thank<00:32:34.400> you<00:32:34.480> so<00:32:34.736> much. 00:32:35.913 --> 00:32:36.818 Really,<00:32:36.139> it's<00:32:36.398> been<00:32:36.543> an<00:32:36.624> honor. 00:32:37.433 --> 00:32:39.697 It's<00:32:37.611> been<00:32:37.999> my<00:32:38.177> pleasure<00:32:38.581> and<00:32:38.727> honor<00:32:38.985> as<00:32:39.147> well,<00:32:39.390> Clint. 00:32:40.020 --> 00:32:41.702 I<00:32:40.101> hope<00:32:40.263> we<00:32:40.344> get<00:32:40.441> to<00:32:40.505> meet<00:32:40.667> in<00:32:40.699> person<00:32:41.071> before<00:32:41.330> too<00:32:41.492> long. 00:32:41.815 --> 00:32:43.675 I'd<00:32:41.977> love<00:32:42.300> to<00:32:42.381> sort<00:32:42.608> of<00:32:42.689> have<00:32:42.866> that<00:32:43.028> chat<00:32:43.271> with<00:32:43.432> you. 00:32:43.756 --> 00:32:44.404 Let's<00:32:44.225> do<00:32:44.322> it. 00:32:44.503 --> 00:32:44.815 Okay. 00:32:44.979 --> 00:32:45.766 Thanks,<00:32:45.225> my<00:32:45.389> friend. 00:32:46.111 --> 00:32:47.161 Really<00:32:46.373> appreciate<00:32:47.013> it. 00:32:51.610 --> 00:32:52.031 Bye-bye. ``` ### Mindgrub Technologies CEO Todd Marks: The tech company building AI for the world's biggest brands URL: https://www.ceo.com/episodes/mindgrub-technologies-founder-ceo-todd-marks/ Last updated: 2026-08-24T21:06:02.000Z # Todd Marks tells clients to bid against him Todd Marks tells clients to get two bids on the same project. One comes from Mindgrub Technologies, the digital agency he [founded in his basement in 2002](https://mindgrub.com/about/team/todd-marks/?ref=ceo.com). The other comes from the group he built inside Mindgrub to make the agency's old process unnecessary. "I started even competing against ourselves," Marks told the CEO.com Podcast. "For that commoditized work, get two bids." Clients can have the traditional route: discovery, wireframes, design, development, testing. Or the team sits down for a single requirements conversation, writes a prompt, and generates the product. Mindgrub guarantees the quality either way. Clients keep picking the faster one. Marks did not come up through agencies. He studied math at Loyola University Maryland and took a job teaching high school in 1998\. "I was a teacher because I wanted to be a kayaker and a climber and sleep in cars and live in the outdoors," he said. The school found out he had some computer science and asked him to teach that too. Then the dot-com boom pulled him all the way in. Two companies failed first. One started with a kayaking partner and dissolved after September 11\. A 2005 bet on Windows Mobile went nowhere. In 2008, he was consulting for a Deloitte subsidiary and traveling constantly when Apple shipped the iPhone. "That's when I finally said, 'Oh, that's it. I'm going to go make mobile apps,'" he said. "Steve Jobs probably will get it right. And lo and behold, he did." He hired a few of his University of Maryland students, quit the day job, and holed up in the basement. Mindgrub rode the mobile wave to [10 consecutive years on the Inc. 5000](https://www.einnews.com/pr%5Fnews/835559637/mindgrub-launches-ai-labs-cementing-its-role-as-a-leader-in-ai-powered-digital-transformation?ref=ceo.com), building for Wendy's, Yamaha, Geico, Exelon, Under Armour, and NASA. Along the way, Marks collected [three Most Admired CEO awards from The Daily Record and two EY Entrepreneur of the Year nominations](https://mindgrub.com/about/team/todd-marks/?ref=ceo.com), and chaired the [Maryland Tech Council and YPO Northeast One](https://mdtechcouncil.com/wp-content/uploads/2023/09/CRC-EmergingIndustries-TMarks.pdf?ref=ceo.com). He sorts the software market into four tiers. Enterprise teams running two-week sprints for years. Waterfall projects under a quarter million dollars. Smaller waterfall work. Turnkey jobs Mindgrub refers out for a fee. The third tier, he said, is getting commoditized out from under the market. Websites that once demanded real engineering are drag-and-drop on Wix. Tools like Lovable turn a prompt into a working light application. The enterprise tiers have a few years before the same thing reaches them. Maybe a couple. So in July 2025, Mindgrub [launched AI Labs](https://www.einnews.com/pr%5Fnews/835559637/mindgrub-launches-ai-labs-cementing-its-role-as-a-leader-in-ai-powered-digital-transformation?ref=ceo.com), the group now bidding against its parent. It has grown more than 300 percent annually. Company-wide, AI pair programming has made Mindgrub's teams around 35 percent more efficient; Marks wants 50\. Generated output gets 90 percent of the way there on small projects, 80 percent on big ones, with humans handling the integrations, the accessibility fixes, the last mile. The book he pushes on everyone is Clayton Christensen's The Innovator's Dilemma, and he reads it about himself. "It scares me," he said. "Even though we're an innovation agency, we have a lot of process in how we've done things for the last 10 years." His team loves making things from scratch. He keeps telling them there are some good templates out there. Much of the new work is custom agents, mostly for startups. A general-purpose model with an interface slapped on top hallucinates too much for any serious industry, so Mindgrub builds narrow ones. A client in veterinary care is automating triage, the judgment call a receptionist can't make, and a doctor shouldn't be interrupted for. "You say, 'Oh, my dog Buffy ate some chocolate.' We have to ask questions. How big's Buffy? How much chocolate was it?" A small dog and a big piece of chocolate means the emergency room. A pit bull and a Hershey's Kiss means Buffy will be fine. Marks sees the same shape everywhere people do repetitive work: call centers, permitting offices, chunks of healthcare and government. "That's all based on a 160-year-old model, factory work from the Industrial Revolution," he said. The humans should be doing "the humanities, the strategic thinking, the intelligent curiosity. That's what we need to be doing, not copy and paste." His advice to funded founders runs in the same direction. "These days, I really want to think twice about hiring a lot of human capital into any business," he said. Automate what you can, use contractors, iterate fast, and pull expertise in-house after the model is proven. The big CTO title and the big equity grant can wait. Marks describes himself as wildly ADHD. He runs Mindgrub, a restaurant started with his wife, a robotics studio, a coworking facility, and a venture practice, all on EOS, the Entrepreneurial Operating System. His personal version is two reserved hours every morning to groom a backlog and bold the week's priorities, because otherwise the meetings and email win and a week passes producing nothing "other than just digital thought." He works from home in Baltimore at a treadmill desk, chasing the step count on his Apple Watch. On the podcast, he apologized for the mess behind him. The company went fully remote in 2020, and Marks spent the margin on the people: bigger salaries, 100 percent of healthcare covered, more holidays. For a while the margin went negative. Turnover fell under five percent. The thinner economics pushed Mindgrub toward contractors and a global supply chain, which he thought the industry was headed toward anyway. Asked who gave him a chance, Marks named his mentors. John Benjamin, the outdoor guide who taught him to climb the next route and run the next river, still climbing today. Reg Hahn, the computer science department head who showed him how to be entrepreneurial inside a public school system. He now runs a foundation investing in STEM education for underserved kids. "Educators along the way, I think, have been my shepherds this whole time," he said. ```chapters 00:00:00 Introducing Mindgrub Technologies and Todd Marks 00:01:31 The Four Tiers of Software Development 00:04:02 Building Custom AI Agents for Startups 00:07:59 The Rise of One-Person Billion-Dollar Companies 00:12:26 Organizing Business and Life With EOS 00:18:59 Baltimore Tech and the Equitec Movement 00:24:31 Maintaining Culture in a Remote Agency 00:26:18 Transitioning From Traditional Dev to Prompt-to-Product 00:33:40 Mentorship and Investing in STEM Education ``` ```vtt WEBVTT 00:00:01.155 --> 00:00:07.893 Todd,<00:00:03.305> thank<00:00:06.610> you<00:00:06.754> so<00:00:06.834> much<00:00:07.011> for<00:00:07.091> coming<00:00:07.332> on<00:00:07.412> the<00:00:07.492> show. 00:00:08.198 --> 00:00:11.792 You<00:00:08.295> are<00:00:08.375> the<00:00:08.535> founder,<00:00:08.936> president,<00:00:09.418> and<00:00:09.514> CEO<00:00:10.300> of<00:00:10.445> Mindgrub<00:00:11.102> 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And<00:08:44.229> with<00:08:44.470> little<00:08:44.790> capital<00:08:45.351> even,<00:08:46.008> they'll,<00:08:46.409> they'll<00:08:46.569> blow<00:08:46.793> out<00:08:46.825> a<00:08:46.954> market. 00:08:47.370 --> 00:08:56.556 You<00:08:47.402> know,<00:08:47.755> it's,<00:08:48.107> it's<00:08:48.252> amazing<00:08:48.668> some<00:08:48.829> of<00:08:48.893> the<00:08:49.037> valuations<00:08:49.918> these<00:08:50.159> days<00:08:50.495> for<00:08:50.655> companies<00:08:51.200> that<00:08:51.360> have<00:08:52.482> a<00:08:52.803> really<00:08:53.364> automated<00:08:53.860> technical<00:08:54.726> core<00:08:55.850> of<00:08:55.962> the<00:08:56.107> business. 00:08:56.974 --> 00:08:57.086 Yeah. 00:08:57.151 --> 00:09:01.759 Does<00:08:57.295> that<00:08:57.392> make<00:08:57.552> you<00:08:57.632> feel<00:08:57.777> like<00:08:57.938> we<00:08:58.034> might<00:08:58.194> be<00:08:58.275> in<00:08:58.355> a<00:08:58.435> bubble,<00:08:58.756> or<00:08:58.917> 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this<00:09:37.197> efficiency<00:09:37.758> curve<00:09:37.998> that<00:09:38.143> eventually<00:09:38.704> moves<00:09:38.896> to<00:09:39.618> singularity<00:09:40.484> of<00:09:40.564> getting<00:09:40.805> stuff<00:09:41.126> done. 00:09:41.366 --> 00:09:43.964 So<00:09:42.232> product<00:09:42.505> cycles<00:09:42.970> are<00:09:43.130> getting<00:09:43.435> shorter. 00:09:44.333 --> 00:09:53.825 The<00:09:44.478> ability<00:09:44.734> to<00:09:44.959> penetrate<00:09:45.456> the<00:09:45.536> market,<00:09:46.322> one<00:09:46.498> statistic<00:09:47.043> he<00:09:47.204> looks<00:09:47.525> at<00:09:47.701> is<00:09:48.168> how<00:09:48.281> long<00:09:48.588> it<00:09:48.734> takes<00:09:48.992> companies<00:09:49.396> to<00:09:49.461> get<00:09:49.558> a<00:09:49.639> million<00:09:50.108> users,<00:09:51.013> and<00:09:51.061> they<00:09:51.174> used<00:09:51.401> to<00:09:51.498> be<00:09:51.966> years<00:09:52.289> apart<00:09:52.710> and<00:09:52.790> now<00:09:53.017> 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00:10:12.817 Yeah. 00:10:13.221 --> 00:10:13.545 Yeah. 00:10:14.146 --> 00:10:20.635 Go<00:10:14.386> deeper<00:10:14.707> on<00:10:15.508> AI<00:10:15.844> agents<00:10:16.229> for<00:10:16.405> us<00:10:16.565> and<00:10:16.710> how<00:10:16.966> you're<00:10:17.126> seeing<00:10:17.511> them<00:10:17.687> evolve<00:10:18.248> and<00:10:18.873> how<00:10:19.033> you're<00:10:19.209> building<00:10:19.530> them<00:10:19.690> and<00:10:19.754> how<00:10:19.930> you're<00:10:20.090> thinking<00:10:20.315> about<00:10:20.491> them. 00:10:21.292 --> 00:10:21.901 Yeah,<00:10:21.532> absolutely. 00:10:21.949 --> 00:10:31.034 So,<00:10:22.622> you<00:10:22.654> know,<00:10:23.519> I<00:10:23.680> tell<00:10:23.856> CFOs,<00:10:24.497> I'm<00:10:24.625> like,<00:10:24.737> where<00:10:24.961> do<00:10:25.041> you<00:10:25.138> have,<00:10:26.339> you<00:10:26.419> know,<00:10:27.044> a<00:10:27.076> number<00:10:27.365> of<00:10:27.461> humans<00:10:27.781> doing<00:10:28.006> 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these<00:15:57.562> opportunities? 00:15:58.524 --> 00:15:59.935 That's<00:15:58.765> a<00:15:58.829> great<00:15:59.166> explanation. 00:16:00.208 --> 00:16:01.747 Thanks<00:16:00.689> for<00:16:00.769> doing<00:16:01.009> that. 00:16:01.811 --> 00:16:03.350 So<00:16:01.987> you<00:16:02.068> mentioned<00:16:02.356> kind<00:16:02.517> of<00:16:02.549> how<00:16:02.677> your<00:16:02.773> mornings<00:16:03.318> are. 00:16:03.414 --> 00:16:06.156 Give<00:16:03.591> us<00:16:03.735> a<00:16:03.751> sense<00:16:04.056> for<00:16:04.136> what<00:16:04.232> a<00:16:04.360> typical<00:16:04.777> day<00:16:05.002> looks<00:16:05.242> like<00:16:05.434> for<00:16:05.563> you. 00:16:06.300 --> 00:16:11.078 Well,<00:16:07.262> so<00:16:07.968> I'm<00:16:08.064> in<00:16:08.144> a<00:16:08.208> lot<00:16:08.385> of<00:16:08.465> organizations<00:16:09.186> and<00:16:09.330> so<00:16:09.507> I'd<00:16:09.683> say<00:16:09.827> there's<00:16:10.132> two<00:16:10.308> typical<00:16:10.709> days. 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00:21:45.224 --> 00:21:46.139 Yeah,<00:21:45.481> that's<00:21:45.722> great. 00:21:46.203 --> 00:21:47.070 That's<00:21:46.604> very<00:21:46.925> cool. 00:21:47.166 --> 00:21:47.343 Yeah. 00:21:47.407 --> 00:21:53.794 And<00:21:47.503> then<00:21:47.648> the<00:21:47.744> tale<00:21:47.953> of<00:21:48.049> two<00:21:48.145> cities<00:21:48.450> with<00:21:48.611> Baltimore<00:21:49.076> is,<00:21:49.798> as<00:21:50.071> you've<00:21:50.199> probably<00:21:51.082> heard,<00:21:51.339> although<00:21:51.965> The<00:21:52.045> Wire<00:21:52.221> isn't<00:21:52.462> talked<00:21:52.671> about<00:21:52.847> as<00:21:52.944> much<00:21:53.184> anymore,<00:21:53.650> but—. 00:21:53.906 --> 00:21:55.222 I<00:21:53.955> was<00:21:54.067> going<00:21:54.179> to<00:21:54.243> say,<00:21:54.452> well,<00:21:54.613> I've<00:21:54.693> seen<00:21:54.869> The<00:21:55.014> Wire. 00:21:55.351 --> 00:21:56.089 That's<00:21:55.511> my<00:21:55.656> experience. 00:21:56.314 --> 00:21:56.956 Yeah. 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Congrats<00:35:29.405> on<00:35:29.469> everything<00:35:29.856> you've<00:35:29.952> built. 00:35:30.741 --> 00:35:33.092 Let's<00:35:30.854> have<00:35:30.983> you<00:35:31.063> back<00:35:31.305> on<00:35:31.402> again<00:35:31.595> because<00:35:31.788> I'd<00:35:31.885> love<00:35:31.965> to<00:35:32.062> go<00:35:32.142> deeper<00:35:32.448> on<00:35:32.593> AI<00:35:32.851> with<00:35:33.012> you. 00:35:33.720 --> 00:35:34.801 But<00:35:33.881> really<00:35:34.139> a<00:35:34.219> pleasure<00:35:34.541> to<00:35:34.590> have<00:35:34.704> you. 00:35:34.866 --> 00:35:35.404 Thank<00:35:35.029> you<00:35:35.111> so<00:35:35.241> much. 00:35:35.502 --> 00:35:36.675 Yeah,<00:35:35.925> thanks<00:35:36.153> for<00:35:36.219> having<00:35:36.398> me,<00:35:36.496> Clint. 00:35:36.724 --> 00:35:37.180 Nice<00:35:36.903> meeting<00:35:37.131> you. 00:35:37.799 --> 00:35:38.174 Likewise. 00:35:38.369 --> 00:35:38.776 Thanks,<00:35:38.548> Todd. 00:35:51.769 --> 00:35:55.640 Loving<00:35:52.334> you<00:35:52.576> makes<00:35:53.060> the<00:35:53.398> stars<00:35:53.914> shine<00:35:54.463> brighter. 00:35:55.801 --> 00:35:56.285 Yeah. ``` ### FullStory Founder & CEO Scott Voigt: How to build a breakthrough tech company URL: https://www.ceo.com/episodes/fullstory-founder-ceo-scott-voigt/ Last updated: 2026-08-24T21:19:22.000Z # Scott Voigt can see you struggling Scott Voigt has a test he runs on executives. Name the 10 customers you upset the most yesterday. Upset so badly that if you had watched it happen, you would have called them personally to apologize. Most executives can't, and Voigt knows what it feels like to be one of the 10\. He once chased a support ticket around the globe four or five times, handed from one of his telecom company's call centers to the next and the next and the next. The CEO of that company, he says, would never have tolerated it if he could have seen it. "Knowing you have a problem, you know it at a low brainstem level," he told us. "Seeing it helps you take action on that. Measuring it tells you which ones you should take action on first." [FullStory](https://www.fullstory.com/?ref=ceo.com), the company Voigt co-founded in 2014, exists to do the seeing and the measuring. The Atlanta company captures every click, mouse movement, and keystroke of a digital visit, structures the data, and serves it back to more than 3,000 customers in banking, travel, retail, and software. In March, the Technology Association of Georgia [announced Voigt as the newest inductee](https://www.tagonline.org/tagwire/the-technology-association-of-georgia-announces-2026-technology-hall-of-fame-honoree-scott-voigt-co-founder-ceo-of-fullstory/?ref=ceo.com) into the Technology Hall of Fame of Georgia, an award PwC has sponsored since its inception in 1993, with the induction ceremony held at TAG's Georgia Technology Summit in April. The founding story starts a decade earlier. In 2004, Voigt and his two eventual co-founders were running a startup out of Georgia Tech when Google acquired it. His partners stayed and built out Google's engineering office in Atlanta. Voigt went to [Silverpop](https://www.fullstory.com/about-us/scott-voigt/?ref=ceo.com), the Atlanta marketing software company later acquired by IBM, where he led marketing. Around 2012, the three quit their day jobs, pulled some Google colleagues along, and went looking for a problem. The one they found: companies were spending heavily on marketing and sales technology to drive visitors to their websites, then going blind the moment those visitors arrived. Web analytics at the time, the paradigm Voigt credits Omniture's Josh James with establishing, required a product manager to decide in advance which moments in a customer journey mattered, then have an engineer instrument each one by hand. Add to cart. Checkout. A tick mark in a database, a chart. What you got was whatever the product manager guessed was important, and nothing else, and you paid engineers to build it. The FullStory bet was to capture everything in a privacy-friendly way and figure out what mattered afterward. The first feature to fall out of that decision was high-fidelity session replay. A play button on every visit. "It turns out the world was just so pleased to have someone finally turn the lights on," Voigt said. A person can review about one session every few minutes. "AI can watch all the sessions all the time, summarize those, find anomalies, summarize the summaries of the anomaly," Voigt said. In June, FullStory [announced three products built on that idea](https://www.fullstory.com/fullstory-launches-new-solutions-to-power-intelligent-digital-experiences/?ref=ceo.com): FullStory MCP, which feeds behavioral data into the AI tools employees already use, StoryAI Agents, which proactively find and prioritize user experience problems, and Workflow Intelligence, which gives leaders visibility into internal processes. AI is also one of the company's internal strategic imperatives, and FullStory measures every organization on it. The company runs what Voigt calls a culture of demos. Teams show each other how they're using AI to get more done, and the accounting team recently demoed tools it built itself to close the books faster. "We think it's like an Iron Man super suit for everybody that works at FullStory," Voigt said. He keeps up the same way every morning, starting his day with reads that include [The Neuron](https://www.theneurondaily.com/?ref=ceo.com), a daily AI newsletter. At night he reads sci-fi on a Kindle, which he says has destroyed his ability to remember titles and authors. "Good sci-fi has provocative conceits in them that unlock the idea of future worlds." Ask him about remote work, and he doesn't pretend to have an answer. Before COVID, Fullstory had 400 people in a converted Kroger in Atlanta. Then everyone scattered, and today only about 100 of the company's roughly 450 employees are in the city. "We're struggling with it, if I'm honest," he said. "I miss having everybody together." The dispersal helps with hiring, since FullStory can recruit strong candidates who refuse the return-to-office mandates spreading elsewhere. But the company just held its mid-year meetup, a few days in an Atlanta hotel with every employee in one place, and watching everyone dissipate afterward left him with a hangover. "If I were starting a company tomorrow, everybody would be together." What holds the culture together in the meantime is saying the same things over and over. The early watchwords were empathy, clarity, and bionics. After COVID, those evolved into values built around winning. A longtime colleague gave him the principle behind both: "Repetition doesn't spoil the prayer." Voigt was born in Atlanta, went to Georgia Tech, and never considered building anywhere else. When FullStory was getting started, MailChimp gave the founders free office space and consulting work to pay the bills. Today, FullStory sublets space to a startup trying to find its footing. "But the real story is Atlanta," Voigt said in TAG's announcement of his Hall of Fame induction, crediting an ecosystem that values pragmatism over hype and long-term building over shortcuts. We end every conversation with the same question: who gave you a chance? For Voigt, it was Bill Nussey, his CEO at Silverpop. "I was a young and green executive that probably thought I was much greater than I actually was," Voigt said. "No, that's just true. I thought I was greater than I actually was, not even thought." Nussey promoted him anyway, let him make mistakes, and coached him through them. "It would've been very easy for him to say, 'You're junior. We're going to bring in somebody with more experience over you.' I've been guilty of doing that as a leader before, so I'm very thankful for the chance he let me have and the patience he had with me to make some mistakes on his time." ```chapters 00:00:00 Introduction 00:00:17 What is FullStory? 00:01:15 Founding FullStory 00:04:09 Product Evolution 00:05:49 AI Integration 00:09:52 Company Culture 00:14:17 Atlanta Tech Scene 00:16:37 Scott's Daily Routine 00:18:16 Reading Recommendations 00:20:14 Understanding Customers 00:22:40 Macroeconomic Environment 00:23:58 Who Gave Scott a Chance? ``` ```vtt WEBVTT 00:00:02.000 --> 00:00:10.400 Coffee<00:00:02.453> is<00:00:02.907> for<00:00:03.360> leaders.<00:00:03.813> [Music]<00:00:04.267> <00:00:04.720> I<00:00:05.173> do<00:00:05.627> have<00:00:06.080> two<00:00:06.533> children<00:00:06.987> um<00:00:07.440> that<00:00:07.893> are<00:00:08.347> coming<00:00:08.800> into<00:00:09.253> the<00:00:09.707> work<00:00:10.160> world 00:00:10.400 --> 00:00:12.960 soon,<00:00:10.719> a<00:00:10.960> 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say<00:00:26.640> with<00:00:26.880> confidence,<00:00:27.599> absolutely<00:00:28.240> yes. 00:00:28.560 --> 00:00:38.000 They're<00:00:28.720> going<00:00:28.800> to<00:00:28.880> be<00:00:28.960> a<00:00:29.119> ton.<00:00:29.679> So<00:00:29.920> I<00:00:30.080> think<00:00:30.160> there's<00:00:30.400> uncertainty<00:00:30.960> on<00:00:31.119> the<00:00:31.199> horizon. 00:00:38.000 --> 00:00:40.239 <00:00:38.399> Scott,<00:00:38.480> thank<00:00:38.640> you<00:00:38.719> so<00:00:38.800> much<00:00:39.040> for<00:00:39.360> coming<00:00:39.600> on<00:00:39.760> the<00:00:39.920> show. 00:00:40.239 --> 00:00:42.719 You're<00:00:40.533> the<00:00:40.826> co-founder<00:00:41.120> and<00:00:41.413> CEO<00:00:41.707> of<00:00:42.000> FullStory. 00:00:42.719 --> 00:00:46.320 Let's<00:00:42.965> start<00:00:43.211> right<00:00:43.458> there.<00:00:43.704> How<00:00:43.950> did<00:00:44.196> you<00:00:44.443> become<00:00:44.689> the<00:00:44.935> co-founder<00:00:45.181> 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where<00:01:56.720> the<00:01:56.960> three<00:01:57.680> eventual<00:01:58.240> founders<00:01:58.799> of 00:01:59.040 --> 00:02:07.759 FullStory<00:01:59.415> uh<00:01:59.789> were<00:02:00.164> working<00:02:00.538> down<00:02:00.913> on<00:02:01.287> a<00:02:01.662> startup<00:02:02.036> at<00:02:02.411> uh<00:02:02.785> Georgia<00:02:03.160> Tech<00:02:03.535> and<00:02:03.909> in<00:02:04.284> a<00:02:04.658> good<00:02:05.033> twist<00:02:05.407> of<00:02:05.782> luck<00:02:06.156> we<00:02:06.531> hit<00:02:06.905> Google's<00:02:07.280> radar 00:02:07.759 --> 00:02:11.840 and<00:02:08.080> Google<00:02:08.479> came<00:02:08.640> in<00:02:08.800> and<00:02:09.039> acquired<00:02:09.520> that<00:02:09.840> that<00:02:10.239> merry<00:02:10.640> band<00:02:10.879> of<00:02:11.039> three. 00:02:11.840 --> 00:02:20.160 My<00:02:12.160> two<00:02:12.560> partners,<00:02:13.200> very<00:02:13.520> smart<00:02:13.920> computer<00:02:14.319> scientists,<00:02:14.959> went<00:02:15.120> 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Google<00:02:30.800> colleagues<00:02:31.360> over<00:02:31.680> with<00:02:31.920> us. 00:02:32.400 --> 00:02:41.680 And<00:02:32.959> um<00:02:33.280> you<00:02:33.519> know<00:02:33.760> longish<00:02:34.480> story<00:02:34.879> short<00:02:35.840> we<00:02:36.319> saw<00:02:36.720> an<00:02:37.040> opportunity<00:02:37.519> in<00:02:37.760> the<00:02:37.920> market<00:02:38.160> where<00:02:38.720> companies<00:02:39.120> at<00:02:39.360> that<00:02:39.599> time<00:02:39.920> call<00:02:40.080> it<00:02:40.800> 2012 00:02:41.680 --> 00:02:50.480 2013<00:02:42.879> were<00:02:43.120> spending<00:02:43.440> a<00:02:43.599> ton<00:02:43.760> of<00:02:43.920> money<00:02:44.160> on<00:02:44.560> marketing<00:02:45.040> technology<00:02:45.519> and<00:02:45.840> sales<00:02:46.239> technology<00:02:47.200> to<00:02:47.519> get<00:02:48.080> visitors<00:02:49.040> or<00:02:49.360> customers<00:02:50.239> to 00:02:50.480 --> 00:02:54.879 a<00:02:50.720> site<00:02:50.959> and<00:02:51.120> then<00:02:51.280> they<00:02:51.519> lost<00:02:51.760> complete<00:02:52.160> visibility<00:02:52.959> into<00:02:53.280> what<00:02:53.519> was<00:02:53.680> going<00:02:53.840> on<00:02:54.000> in<00:02:54.160> the<00:02:54.319> site. 00:02:54.879 --> 00:03:01.840 And<00:02:55.280> um<00:02:55.440> as<00:02:55.680> we<00:02:55.840> looked<00:02:56.080> at<00:02:56.239> the<00:02:56.480> problem<00:02:57.440> what<00:02:57.680> was<00:02:58.000> happening<00:02:58.640> was<00:02:59.440> wasn't<00:02:59.840> that<00:03:00.000> companies<00:03:00.400> didn't<00:03:00.560> care<00:03:00.800> about<00:03:00.959> digital<00:03:01.360> experience. 00:03:01.840 --> 00:03:07.440 It<00:03:02.159> is<00:03:02.560> they<00:03:02.879> were<00:03:03.040> using<00:03:03.360> a<00:03:03.760> flawed<00:03:04.640> paradigm<00:03:05.360> to<00:03:05.599> try<00:03:05.840> to<00:03:06.080> understand<00:03:06.640> digital<00:03:07.040> experience. 00:03:07.440 --> 00:03:14.720 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journey.<00:03:24.560> I<00:03:24.959> think<00:03:25.440> that<00:03:25.760> add<00:03:26.080> to<00:03:26.319> cart<00:03:26.640> is<00:03:26.800> an<00:03:27.040> important<00:03:27.519> moment<00:03:27.920> as<00:03:28.159> a<00:03:28.319> product<00:03:28.560> manager. 00:03:29.040 --> 00:03:31.599 And<00:03:29.200> so<00:03:29.440> I'm<00:03:29.680> going<00:03:29.840> to<00:03:30.239> instrument<00:03:30.879> that<00:03:31.200> event. 00:03:31.599 --> 00:03:33.840 I'm<00:03:31.759> going<00:03:31.919> to<00:03:32.079> get<00:03:32.239> an<00:03:32.400> engineer<00:03:32.560> to<00:03:32.720> write<00:03:32.880> a<00:03:33.040> little<00:03:33.200> code. 00:03:33.840 --> 00:03:38.640 It's<00:03:34.000> going<00:03:34.080> to<00:03:34.159> put<00:03:34.319> a<00:03:34.480> tick<00:03:34.720> mark<00:03:34.959> in<00:03:35.120> a<00:03:35.200> database.<00:03:35.599> I<00:03:35.840> get<00:03:35.920> a<00:03:36.159> chart<00:03:36.480> on<00:03:36.720> how<00:03:36.959> 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product<00:04:38.941> evolved<00:04:39.188> since<00:04:39.434> the<00:04:39.680> founding? 00:04:40.400 --> 00:04:46.720 <00:04:40.720> Well,<00:04:41.040> um<00:04:41.360> so<00:04:41.680> the<00:04:42.000> the<00:04:42.320> essence<00:04:42.640> of<00:04:42.960> the<00:04:43.280> product<00:04:43.600> was<00:04:43.920> always<00:04:44.240> about<00:04:44.560> this<00:04:44.880> this<00:04:45.200> concept<00:04:45.520> of<00:04:45.840> data<00:04:46.160> capture. 00:04:46.720 --> 00:04:54.400 We<00:04:46.960> call<00:04:47.120> that<00:04:47.520> full<00:04:47.840> capture.<00:04:48.800> The<00:04:48.960> the<00:04:49.440> first<00:04:49.840> feature,<00:04:50.479> if<00:04:50.720> you<00:04:50.800> will,<00:04:51.040> that<00:04:51.280> fell<00:04:51.520> out<00:04:51.680> of<00:04:51.840> that<00:04:52.080> was<00:04:52.479> high-fidelity<00:04:53.360> session<00:04:53.840> replay. 00:04:54.400 --> 00:05:02.720 And<00:04:54.748> so<00:04:55.096> for<00:04:55.443> 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move<00:05:46.000> around. 00:05:46.560 --> 00:05:48.960 Product<00:05:47.039> analytics<00:05:47.919> fell<00:05:48.240> out<00:05:48.400> of<00:05:48.560> that. 00:05:48.960 --> 00:05:56.720 So<00:05:49.231> if<00:05:49.503> you<00:05:49.774> wanted<00:05:50.046> to<00:05:50.317> have<00:05:50.589> a<00:05:50.860> comprehensive<00:05:51.131> set<00:05:51.403> of<00:05:51.674> data<00:05:51.946> in<00:05:52.217> order<00:05:52.489> to<00:05:52.760> do<00:05:53.031> charts<00:05:53.303> and<00:05:53.574> graphs<00:05:53.846> and<00:05:54.117> funnels<00:05:54.389> and<00:05:54.660> all<00:05:54.931> that<00:05:55.203> good<00:05:55.474> stuff,<00:05:55.746> FullStory<00:05:56.017> was<00:05:56.289> a<00:05:56.560> great 00:05:56.720 --> 00:06:05.199 place<00:05:56.880> for<00:05:57.120> that.<00:05:57.759> And<00:05:57.919> then<00:05:58.400> of<00:05:58.639> course<00:05:59.039> as<00:05:59.199> as<00:05:59.520> we<00:05:59.680> step<00:05:59.840> into<00:06:00.080> this<00:06:00.320> new<00:06:00.479> world<00:06:01.199> uh<00:06:01.440> most<00:06:01.680> recently<00:06:02.160> we<00:06:02.400> are<00:06:02.560> spending<00:06:02.880> a<00:06:03.199> lot<00:06:03.360> of<00:06:03.520> time<00:06:04.400> thinking<00:06:04.880> about 00:06:05.199 --> 00:06:14.080 AI<00:06:05.600> and<00:06:05.840> how<00:06:06.080> that<00:06:06.240> can<00:06:06.400> unlock<00:06:06.800> value<00:06:07.120> for<00:06:07.360> our<00:06:07.600> existing<00:06:08.080> customers<00:06:08.880> and<00:06:09.759> um<00:06:10.080> you<00:06:10.319> know<00:06:10.639> and<00:06:11.039> improve<00:06:11.600> experience<00:06:12.560> for<00:06:12.960> their<00:06:13.280> visitors. 00:06:14.080 --> 00:06:20.240 <00:06:14.311> Yeah.<00:06:14.542> Give<00:06:14.772> me<00:06:15.003> a<00:06:15.234> sense<00:06:15.465> for<00:06:15.695> how<00:06:15.926> you're<00:06:16.157> thinking<00:06:16.388> about<00:06:16.618> AI,<00:06:16.849> how<00:06:17.080> you're<00:06:17.311> integrating<00:06:17.542> it<00:06:17.772> both<00:06:18.003> internally<00:06:18.234> and<00:06:18.465> in<00:06:18.695> the<00:06:18.926> product<00:06:19.157> and<00:06:19.388> where<00:06:19.618> do<00:06:19.849> you<00:06:20.080> think 00:06:20.240 --> 00:06:23.360 it's<00:06:20.480> going?<00:06:20.720> <00:06:20.960> Well,<00:06:21.200> yeah,<00:06:21.440> there's<00:06:21.680> a<00:06:21.920> there's<00:06:22.160> a<00:06:22.400> lot<00:06:22.640> to<00:06:22.880> unpack<00:06:23.120> there. 00:06:23.360 --> 00:06:28.800 So<00:06:23.520> let<00:06:23.759> let's<00:06:24.160> start<00:06:24.400> with<00:06:24.960> as<00:06:25.280> a<00:06:25.520> business<00:06:26.240> we<00:06:26.400> we<00:06:26.880> have<00:06:27.039> what<00:06:27.199> we<00:06:27.440> call<00:06:27.600> strategic<00:06:28.160> imperatives. 00:06:28.800 --> 00:06:34.240 These<00:06:28.880> are<00:06:29.039> kind<00:06:29.199> of<00:06:29.280> OKRs<00:06:30.639> and<00:06:30.960> one<00:06:31.120> 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AI<00:07:05.199> can<00:07:05.520> watch<00:07:06.319> all<00:07:06.560> the<00:07:06.800> sessions<00:07:07.759> all<00:07:08.080> the<00:07:08.319> time,<00:07:09.199> summarize<00:07:09.919> those,<00:07:11.039> find<00:07:11.520> anomalies,<00:07:12.400> summarize<00:07:12.880> the 00:07:13.120 --> 00:07:21.599 summaries<00:07:13.599> of<00:07:13.759> the<00:07:13.919> anomaly.<00:07:14.560> And<00:07:14.720> so<00:07:14.880> it's<00:07:15.199> really<00:07:15.440> just<00:07:15.680> changing<00:07:16.160> the<00:07:16.560> scalability<00:07:17.759> with<00:07:18.080> which<00:07:18.479> teams<00:07:18.960> can<00:07:19.360> understand<00:07:20.560> what<00:07:20.880> their<00:07:21.120> visitors 00:07:21.599 --> 00:07:30.000 are<00:07:21.759> doing.<00:07:22.000> And<00:07:22.160> so<00:07:22.319> we're<00:07:22.560> putting<00:07:22.880> a<00:07:23.199> ton<00:07:23.440> of<00:07:23.680> time<00:07:24.800> into<00:07:25.520> just<00:07:25.840> taking<00:07:26.160> 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it's<00:07:44.400> a<00:07:44.560> wide<00:07:44.800> world<00:07:45.039> right<00:07:45.280> now. 00:07:45.919 --> 00:07:49.599 And<00:07:46.240> of<00:07:46.479> course,<00:07:47.759> we're<00:07:48.000> a<00:07:48.240> software<00:07:48.560> as<00:07:48.720> a<00:07:48.960> service<00:07:49.199> tool. 00:07:49.599 --> 00:07:52.720 When<00:07:49.875> you<00:07:50.150> log<00:07:50.426> into<00:07:50.702> FullStory,<00:07:50.977> I<00:07:51.253> talked<00:07:51.529> about<00:07:51.804> product<00:07:52.080> analytics. 00:07:52.720 --> 00:07:57.919 Product<00:07:52.960> analytics<00:07:53.599> is,<00:07:54.879> you<00:07:55.039> know,<00:07:55.120> it's<00:07:55.440> a<00:07:55.599> tool<00:07:55.840> for<00:07:56.080> people<00:07:56.319> that<00:07:56.639> have<00:07:56.720> an<00:07:56.960> analytic<00:07:57.520> mind. 00:07:57.919 --> 00:08:02.479 They<00:07:58.160> come<00:07:58.240> in<00:07:58.479> and<00:07:58.639> they<00:07:58.879> think<00:07:59.039> about<00:07:59.280> 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how<00:08:35.207> they're<00:08:35.645> using<00:08:36.083> AI<00:08:36.521> to<00:08:36.959> increase 00:08:37.440 --> 00:08:45.519 their<00:08:37.763> their<00:08:38.087> throughput.<00:08:38.410> Basically,<00:08:38.733> we<00:08:39.057> think<00:08:39.380> it's<00:08:39.703> just<00:08:40.027> a<00:08:40.350> it's<00:08:40.673> like<00:08:40.997> an<00:08:41.320> Iron<00:08:41.643> Man<00:08:41.967> supersuit<00:08:42.290> for<00:08:42.613> everybody<00:08:42.937> that<00:08:43.260> works<00:08:43.583> at<00:08:43.907> at<00:08:44.230> FullStory<00:08:44.553> to<00:08:44.877> do<00:08:45.200> things 00:08:45.519 --> 00:08:54.399 faster.<00:08:46.720> So,<00:08:46.959> we<00:08:47.120> saw<00:08:47.200> a<00:08:47.360> demo<00:08:47.680> recently<00:08:48.160> of<00:08:48.720> our<00:08:49.120> accounting<00:08:49.600> team<00:08:49.920> and<00:08:50.240> how<00:08:50.560> they're<00:08:51.040> using<00:08:51.519> AI<00:08:52.320> building<00:08:52.720> their<00:08:52.959> 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And<00:09:09.200> you<00:09:09.400> don't<00:09:09.600> get<00:09:09.800> the<00:09:10.000> sense<00:09:10.200> that<00:09:10.400> it's<00:09:10.600> fluff,<00:09:10.800> right? 00:09:11.360 --> 00:09:16.880 Like<00:09:11.600> I<00:09:11.760> mean<00:09:12.399> we're<00:09:12.720> starting<00:09:12.959> to<00:09:13.120> get<00:09:13.200> to<00:09:13.360> the<00:09:13.519> point<00:09:13.600> of<00:09:13.760> AI<00:09:14.160> where<00:09:14.399> people<00:09:14.560> are<00:09:14.720> like<00:09:14.880> oh<00:09:15.120> it's<00:09:15.360> maybe<00:09:15.519> it's<00:09:15.680> plateaued. 00:09:16.880 --> 00:09:21.839 Maybe<00:09:17.200> it's<00:09:17.519> not<00:09:17.760> helping<00:09:18.640> as<00:09:18.959> much<00:09:19.120> as<00:09:19.600> you<00:09:19.680> know<00:09:19.839> these<00:09:20.080> these<00:09:20.399> major<00:09:20.640> AI<00:09:21.040> companies<00:09:21.279> are<00:09:21.519> saying. 00:09:21.839 --> 00:09:24.880 Um<00:09:22.080> but<00:09:22.240> but<00:09:22.640> real<00:09:22.959> world<00:09:23.200> experience<00:09:23.680> it's<00:09:23.920> helping<00:09:24.160> you<00:09:24.320> guys. 00:09:24.880 --> 00:09:28.480 <00:09:25.270> It's<00:09:25.660> it's<00:09:26.050> definitely<00:09:26.440> been<00:09:26.830> it<00:09:27.220> very<00:09:27.610> very<00:09:28.000> helpful. 00:09:28.480 --> 00:09:32.000 I<00:09:28.800> can't<00:09:29.120> So<00:09:29.360> you<00:09:29.600> asked<00:09:29.839> me<00:09:30.240> where<00:09:30.399> are<00:09:30.560> we<00:09:30.720> going<00:09:30.959> from<00:09:31.120> here? 00:09:32.000 --> 00:09:38.320 I'm<00:09:32.480> I<00:09:32.959> tend<00:09:33.360> to<00:09:33.680> believe<00:09:34.399> that<00:09:35.519> that<00:09:36.080> things<00:09:36.320> are<00:09:36.640> going<00:09:36.800> to<00:09:37.120> continue<00:09:37.519> to<00:09:37.760> progress. 00:09:38.320 --> 00:09:46.480 I<00:09:38.560> I<00:09:38.959> don't<00:09:39.200> see<00:09:39.600> I<00:09:39.839> mean<00:09:40.240> 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is<00:25:50.639> so<00:25:50.959> awesome.<00:25:51.279> Uh,<00:25:51.599> love<00:25:51.919> Atlanta. 00:25:52.640 --> 00:25:54.640 Always<00:25:52.960> love<00:25:53.120> going<00:25:53.279> to<00:25:53.440> a<00:25:53.600> Braves<00:25:53.840> game<00:25:54.000> or<00:25:54.159> two<00:25:54.320> every<00:25:54.480> year. 00:25:54.640 --> 00:25:57.679 It's<00:25:54.799> an<00:25:54.880> incredible<00:25:55.200> experience.<00:25:55.520> Come<00:25:55.600> on.<00:25:55.760> You<00:25:55.919> let<00:25:56.080> me<00:25:56.159> know<00:25:56.320> next<00:25:56.480> time<00:25:56.559> you're<00:25:56.720> in<00:25:56.880> town,<00:25:57.120> Clint. 00:25:57.679 --> 00:26:04.660 Okay.<00:25:58.080> Thanks,<00:25:58.400> brother. 00:26:04.660 --> 00:26:13.279 [Music] 00:26:13.279 --> 00:26:17.679 Shine<00:26:13.679> bright<00:26:14.240> up.<00:26:15.679> Yeah. ``` ### Smartling CEO Bryan Murphy: How AI is disrupting the $50 billion translation industry URL: https://www.ceo.com/episodes/smartling-ceo-bryan-murphy/ Last updated: 2026-08-24T21:29:56.000Z # The Saturday morning Bryan Murphy saw it coming Smartling had been doing machine translation for more than a decade before ChatGPT existed. Cloud-native from the start, built on neural machine translation before most of its customers knew the term. Bryan Murphy jokes that the company could always do translation faster and cheaper than a human. Just not better. Then OpenAI released its chatbot on a Saturday morning, Murphy started playing with it, and his leadership team spent the rest of the weekend on Slack saying holy smokes. The models solved linguistic problems the old technology couldn't touch. "Now we're able to produce translation that's faster, cheaper, and now better than human translation standalone," he told CEO.com. The industry Smartling operates in is worth $50 billion and, until recently, ran on 20 cents a word and multi-week turnarounds. Companies rationed what they translated because they had to. That's ending. Smartling's translators now produce roughly eight times more output for the same budget, and Murphy expects that number to double within a year. The company reported [218% year-over-year growth in AI translation](https://www.smartling.com/company-news/smartling-wins-2026-ai-breakthrough-award?ref=ceo.com), and Fast Company put it at [No. 3 in business services](https://www.fastcompany.com/91497089/business-services-most-innovative-companies-2026?ref=ceo.com) on its 2026 Most Innovative Companies list. Murphy is not the founder. Jack Welde started Smartling in 2009 and stayed on as president when Murphy [took over as CEO in 2022](https://www.smartling.com/company-news/smartling-appoints-ceo?ref=ceo.com), a few months after Battery Ventures put in $160 million. Murphy kept every one of Welde's values. Good today, better tomorrow. Constraint breeds creativity. Take care of your people. "They're great," he said. "They matter a lot to people, and so we try and live by them." He'd done this kind of thing before. He co-founded WHI Solutions, sold it to eBay in 2012, ran vertical markets there, then ran Breather and digital for Serta Simmons. He likes markets that are, in his words, a little fat and a little slow. His favorite lesson came from a failure. At eBay, he was handed a goal of $2.6 billion in incremental sales volume, and he brought the board a plan with 100 initiatives. His boss sent him back to the drawing board, ordering him to get it under six. Murphy was mortified. He reworked the plan with his teams around the world, came back with six things, and finished the year at 106% of goal. "You can't do everything, you can only do a few things in an organization," he said. Smartling now runs on an operating plan with five pillars, and every all-hands opens with the mission: help customers grow globally faster. Not build the best translation software. He borrowed Bezos's empty chair and starts sales conversations by asking customers what their own KPIs are. On AI generally, he doesn't hedge. "I think it's going to be the most significant productivity enhancement mankind has created to date." We end every episode with the same question: who gave you a chance? Murphy's answer is Terry Varsinger, who listened to a 25-year-old pitch a company on sweat equity and could have shown him the door. "I don't know what sweat equity is, but I know what equity in capital is, so I'll match you dollar for dollar." ```chapters 00:00:00 Journey to Becoming Smartling CEO 00:01:18 Disrupting the Translation Market 00:03:54 The Future of AI Productivity 00:06:44 Daily Routines and Operating Pillars 00:08:04 Building Culture in Remote Teams 00:09:21 Expanding Into International Markets 00:11:31 Mission and Values at Smartling 00:13:47 Leadership Lessons Learned at eBay 00:15:20 Economic Outlook and Global Growth 00:16:37 The Power of Giving Someone a Chance ``` ```vtt WEBVTT 00:00:06.649 --> 00:00:08.282 Ryan,<00:00:06.910> thank<00:00:07.074> you<00:00:07.155> so<00:00:07.253> much<00:00:07.466> for<00:00:07.547> coming<00:00:07.727> on<00:00:07.874> the<00:00:07.955> show. 00:00:08.364 --> 00:00:09.817 You're<00:00:08.462> the<00:00:08.543> CEO<00:00:08.935> of<00:00:09.017> Smartling. 00:00:09.996 --> 00:00:11.466 You've<00:00:10.111> had<00:00:10.258> an<00:00:10.356> 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like<00:06:07.221> in,<00:06:07.622> you<00:06:07.782> know,<00:06:07.878> 12<00:06:08.230> months,<00:06:08.455> I'd<00:06:08.583> probably<00:06:08.775> say<00:06:08.984> it's<00:06:09.144> probably<00:06:09.464> going<00:06:09.528> to<00:06:09.576> at<00:06:09.624> least<00:06:09.801> double,<00:06:10.666> uh,<00:06:11.082> that. 00:06:11.739 --> 00:06:24.798 So<00:06:13.550> typically<00:06:14.031> what<00:06:14.127> I<00:06:14.287> see<00:06:14.511> happening,<00:06:14.992> and,<00:06:15.312> and<00:06:15.489> when<00:06:15.633> you<00:06:15.729> have<00:06:15.889> these<00:06:16.049> transitions,<00:06:16.674> right,<00:06:17.011> it's<00:06:17.171> the,<00:06:18.837> um,<00:06:19.062> it's<00:06:19.815> this<00:06:19.975> principle<00:06:20.360> where<00:06:20.696> as,<00:06:21.081> as<00:06:21.241> cost<00:06:21.641> and<00:06:21.721> utility<00:06:22.218> improve,<00:06:23.083> utilization<00:06:24.445> goes<00:06:24.702> up. 00:06:24.862 --> 00:06:26.096 Jevons<00:06:25.182> paradox,<00:06:25.967> right? 00:06:26.208 --> 00:06:26.336 Right. 00:06:26.640 --> 00:06:29.845 So<00:06:27.025> we<00:06:27.121> saw<00:06:27.345> this<00:06:27.570> with<00:06:27.746> data<00:06:28.002> storage,<00:06:29.028> cloud<00:06:29.348> services. 00:06:29.909 --> 00:06:32.956 As<00:06:30.069> that<00:06:30.374> price<00:06:30.694> comes<00:06:31.031> down,<00:06:31.977> utilization<00:06:32.619> goes<00:06:32.860> up. 00:06:33.438 --> 00:06:37.712 I<00:06:33.599> think<00:06:33.760> we're<00:06:33.904> seeing<00:06:34.467> that<00:06:35.029> in<00:06:35.527> our—<00:06:35.848> not<00:06:36.073> think,<00:06:36.314> we<00:06:36.426> are<00:06:36.507> seeing<00:06:36.876> that<00:06:37.133> in<00:06:37.198> our<00:06:37.358> industry. 00:06:37.920 --> 00:06:44.330 As<00:06:38.097> we<00:06:38.258> bring<00:06:38.499> the<00:06:38.643> cost<00:06:38.981> down,<00:06:39.238> the<00:06:39.302> efficiency<00:06:39.928> up,<00:06:40.491> our<00:06:40.587> customers<00:06:41.069> 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customers<00:06:56.555> all<00:06:56.652> around<00:06:56.893> the<00:06:56.973> world,<00:06:57.310> starting<00:06:57.696> in<00:06:57.776> the,<00:06:58.419> in<00:06:58.563> the,<00:06:58.804> um,<00:06:59.366> in<00:06:59.446> the<00:06:59.526> fall,<00:07:00.423> which<00:07:00.648> I<00:07:00.680> enjoy. 00:07:01.145 --> 00:07:03.676 But<00:07:01.305> now,<00:07:01.625> you<00:07:01.737> know,<00:07:01.930> I<00:07:01.946> like<00:07:02.106> to<00:07:02.250> get<00:07:02.362> up—<00:07:02.667> I<00:07:02.747> get<00:07:02.843> up<00:07:02.987> early<00:07:03.148> in<00:07:03.228> the<00:07:03.388> morning. 00:07:03.933 --> 00:07:10.166 I<00:07:04.430> read<00:07:05.471> a<00:07:05.535> lot,<00:07:05.808> so<00:07:06.112> kind<00:07:06.240> of<00:07:06.272> like<00:07:06.433> general<00:07:06.833> news,<00:07:07.154> business<00:07:07.554> news,<00:07:08.420> and<00:07:08.820> obviously<00:07:09.477> industry<00:07:09.878> news. 00:07:10.583 --> 00:07:15.887 You<00:07:10.615> know,<00:07:10.759> try<00:07:10.983> and<00:07:11.080> get<00:07:11.464> a<00:07:11.480> little<00:07:11.640> bit<00:07:11.785> of<00:07:11.817> a<00:07:11.881> workout<00:07:12.442> in,<00:07:12.826> and<00:07:13.387> that<00:07:13.884> kind<00:07:14.044> of<00:07:14.124> gets<00:07:14.365> me<00:07:15.070> going<00:07:15.390> for<00:07:15.486> the<00:07:15.630> day. 00:07:16.448 --> 00:07:32.795 And<00:07:16.528> then<00:07:17.249> I<00:07:17.489> try<00:07:17.730> and,<00:07:18.050> you<00:07:18.162> know,<00:07:18.515> our—<00:07:19.572> I<00:07:19.652> try<00:07:19.893> and<00:07:19.973> run<00:07:20.133> the<00:07:20.213> business,<00:07:21.015> and<00:07:21.111> I<00:07:21.175> learned<00:07:21.399> this<00:07:21.720> a<00:07:21.736> while<00:07:22.040> back<00:07:22.296> ago,<00:07:23.162> using<00:07:23.659> an<00:07:23.739> operating<00:07:24.203> plan,<00:07:24.860> which<00:07:25.630> The<00:07:25.742> pillars<00:07:26.223> are<00:07:27.489> go-to-market,<00:07:29.092> customer<00:07:29.413> experience,<00:07:30.310> building<00:07:30.855> product,<00:07:31.352> finance,<00:07:32.090> and<00:07:32.218> people,<00:07:32.555> right? 00:07:33.035 --> 00:07:35.296 And<00:07:33.116> so<00:07:33.212> that's<00:07:33.500> sort<00:07:33.596> of<00:07:33.741> like<00:07:34.077> the<00:07:34.222> pillars<00:07:34.558> of<00:07:34.622> our<00:07:34.719> operating<00:07:35.119> plan. 00:07:35.360 --> 00:07:43.359 I<00:07:35.376> sort<00:07:35.520> of<00:07:35.841> orient<00:07:36.241> my<00:07:36.402> day<00:07:36.626> and<00:07:36.706> my<00:07:36.883> week<00:07:37.364> around<00:07:38.229> moving<00:07:38.646> that<00:07:39.447> forward<00:07:39.912> and<00:07:40.073> focusing<00:07:40.489> on<00:07:40.634> that<00:07:40.826> with<00:07:40.970> the<00:07:41.051> teams<00:07:41.515> that<00:07:41.612> are<00:07:41.756> mostly<00:07:42.092> responsible<00:07:42.734> for<00:07:42.878> doing<00:07:43.134> that. 00:07:43.776 --> 00:07:48.793 And<00:07:44.241> that<00:07:44.577> to<00:07:44.673> me<00:07:44.818> has<00:07:44.978> been<00:07:45.138> a<00:07:45.218> formula<00:07:45.844> that's<00:07:46.405> really<00:07:47.222> worked<00:07:47.463> for<00:07:47.591> me<00:07:47.767> over<00:07:47.927> the<00:07:47.960> last<00:07:48.248> several<00:07:48.569> years. 00:07:49.370 --> 00:07:50.204 What<00:07:49.546> books<00:07:49.787> do<00:07:49.851> you<00:07:49.947> read? 00:07:50.701 --> 00:07:52.432 Do<00:07:50.973> you<00:07:51.053> have<00:07:51.149> any<00:07:51.374> recommendations<00:07:52.095> for<00:07:52.272> us? 00:07:52.977 --> 00:07:54.852 Well,<00:07:53.859> I<00:07:54.019> have<00:07:54.452> a<00:07:54.580> couple. 00:07:55.029 --> 00:08:00.748 So<00:07:55.077> like,<00:07:55.381> you<00:07:55.558> know,<00:07:55.782> One<00:07:55.943> to<00:07:55.975> Zero,<00:07:57.001> Lessons<00:07:57.321> from<00:07:57.465> the<00:07:58.085> James<00:07:58.246> Citroën<00:07:58.649> did<00:07:58.827> a<00:07:58.875> really<00:07:59.053> 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internally. 00:08:34.306 --> 00:08:35.364 And<00:08:34.562> I<00:08:34.643> think<00:08:34.803> we<00:08:34.963> do<00:08:35.123> that. 00:08:35.524 --> 00:08:47.435 I<00:08:35.604> think<00:08:35.749> it's<00:08:35.909> also<00:08:36.149> really<00:08:36.310> important<00:08:36.727> that<00:08:37.592> each<00:08:38.634> person<00:08:38.955> has<00:08:39.083> to<00:08:39.131> have<00:08:39.372> a<00:08:39.516> really<00:08:39.756> clear<00:08:40.013> KPI<00:08:41.360> and<00:08:41.536> be<00:08:41.632> measured<00:08:42.001> against<00:08:42.321> that<00:08:42.979> so<00:08:43.139> that<00:08:43.620> you<00:08:43.780> know<00:08:44.181> and<00:08:44.582> management<00:08:45.047> knows,<00:08:45.303> hey,<00:08:45.464> is<00:08:45.544> this<00:08:45.704> person—<00:08:46.425> are<00:08:46.490> they<00:08:46.810> being<00:08:46.987> productive? 00:08:47.612 --> 00:08:47.884 Right? 00:08:48.013 --> 00:08:49.311 Because<00:08:48.750> you<00:08:48.782> can't<00:08:48.894> see<00:08:49.071> them. 00:08:49.520 --> 00:08:50.060 Right? 00:08:50.060 --> 00:08:54.640 So<00:08:50.061> we<00:08:50.320> have<00:08:50.940> really<00:08:51.740> good<00:08:51.920> KPIs<00:08:52.520> and<00:08:52.660> measurement<00:08:52.980> systems<00:08:53.300> across<00:08:53.600> the<00:08:53.840> company. 00:08:54.640 --> 00:08:59.880 And<00:08:54.720> so<00:08:54.860> from<00:08:54.940> a<00:08:55.120> culture<00:08:55.360> perspective,<00:08:56.000> we<00:08:56.120> don't<00:08:56.300> make<00:08:56.560> up<00:08:56.740> things<00:08:57.000> like,<00:08:57.380> hey,<00:08:57.700> we're<00:08:57.840> going<00:08:57.980> to<00:08:57.981> do<00:08:58.100> a<00:08:58.160> virtual<00:08:58.380> happy<00:08:58.680> hour,<00:08:59.060> any<00:08:59.320> of<00:08:59.500> that<00:08:59.540> kind<00:08:59.620> of<00:08:59.800> stuff. 00:08:59.880 --> 00:09:03.590 We<00:09:00.040> try<00:09:00.300> and<00:09:00.480> build<00:09:00.900> it<00:09:01.020> authentically<00:09:01.500> through<00:09:01.780> 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relationships. 00:09:17.460 --> 00:09:18.900 And<00:09:17.700> that<00:09:18.000> works<00:09:18.200> out<00:09:18.460> pretty<00:09:18.620> well. 00:09:19.366 --> 00:09:20.152 Oh,<00:09:19.526> that's<00:09:19.703> very<00:09:20.024> cool. 00:09:20.409 --> 00:09:21.034 Yeah,<00:09:20.585> that's<00:09:20.826> fun. 00:09:21.548 --> 00:09:27.740 What<00:09:21.949> recommendations<00:09:22.526> would<00:09:22.606> you<00:09:22.735> have<00:09:22.911> for<00:09:22.991> CEOs<00:09:23.713> and<00:09:23.874> leaders<00:09:24.259> who<00:09:24.371> are<00:09:24.499> trying<00:09:24.740> to<00:09:24.836> expand<00:09:25.638> into<00:09:26.841> international<00:09:27.355> markets? 00:09:27.788 --> 00:09:29.200 You've<00:09:27.884> done<00:09:28.045> that<00:09:28.189> a<00:09:28.205> lot<00:09:28.446> throughout<00:09:28.670> your<00:09:28.847> career. 00:09:29.889 --> 00:09:31.510 What<00:09:29.986> should<00:09:30.146> they<00:09:30.291> be<00:09:30.451> thinking<00:09:30.852> about? 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00:11:05.076 --> 00:11:08.525 Otherwise,<00:11:05.397> you're<00:11:05.558> just,<00:11:05.798> you're<00:11:05.943> going<00:11:06.071> to<00:11:06.119> face<00:11:06.376> a<00:11:06.504> really<00:11:06.680> tough<00:11:08.505> slog. 00:11:08.525 --> 00:11:10.036 And,<00:11:08.655> you<00:11:08.688> know,<00:11:08.769> once<00:11:08.931> again,<00:11:09.078> we've<00:11:09.224> kind<00:11:09.305> of<00:11:09.402> talked<00:11:09.581> about<00:11:09.743> it<00:11:09.808> before. 00:11:10.117 --> 00:11:14.339 It<00:11:10.214> used<00:11:10.442> to<00:11:10.523> be<00:11:10.945> like<00:11:11.254> really<00:11:11.497> expensive<00:11:12.244> and<00:11:12.407> really<00:11:12.813> like<00:11:13.121> just<00:11:13.300> a<00:11:13.316> big<00:11:13.544> time<00:11:13.950> suck. 00:11:14.762 --> 00:11:29.534 Now<00:11:15.151> with,<00:11:15.882> you<00:11:15.963> know,<00:11:16.383> with<00:11:16.545> cloud-based<00:11:17.060> software,<00:11:18.221> AI<00:11:18.946> 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00:15:18.834 That<00:15:16.811> was<00:15:17.068> one<00:15:17.148> of<00:15:17.244> the<00:15:17.373> big<00:15:17.533> takeaways<00:15:18.095> for<00:15:18.272> me<00:15:18.513> at<00:15:18.818> eBay. 00:15:18.898 --> 00:15:20.086 It<00:15:19.235> was<00:15:19.396> an<00:15:19.460> important<00:15:19.862> learning. 00:15:20.520 --> 00:15:22.832 What's<00:15:20.761> the<00:15:21.307> economic<00:15:21.788> outlook<00:15:22.126> been<00:15:22.350> like<00:15:22.591> for<00:15:22.752> you? 00:15:22.945 --> 00:15:32.402 I<00:15:23.009> mean,<00:15:23.250> given<00:15:23.474> that<00:15:23.635> you're<00:15:23.812> in,<00:15:24.679> you<00:15:24.775> know,<00:15:25.016> all<00:15:25.096> these,<00:15:25.401> all<00:15:25.433> these<00:15:25.642> various<00:15:25.979> countries<00:15:26.541> and<00:15:26.605> we<00:15:26.702> have<00:15:26.862> weird<00:15:27.103> trade<00:15:27.489> deals<00:15:27.810> all<00:15:27.842> the<00:15:27.970> time<00:15:28.324> and<00:15:28.452> 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entrepreneurial<00:17:40.502> career. 00:17:40.967 --> 00:17:44.837 And<00:17:41.545> I,<00:17:42.493> you<00:17:42.894> know,<00:17:43.215> I<00:17:43.231> don't<00:17:43.376> think<00:17:43.488> I<00:17:44.098> could<00:17:44.211> have<00:17:44.291> done<00:17:44.435> it<00:17:44.516> without<00:17:44.757> him. 00:17:45.543 --> 00:17:46.218 That's<00:17:45.720> incredible. 00:17:46.683 --> 00:17:48.144 Brian,<00:17:46.924> thank<00:17:47.149> you<00:17:47.181> so<00:17:47.310> much<00:17:47.470> for<00:17:47.550> joining<00:17:47.872> us,<00:17:48.032> man. 00:17:48.193 --> 00:17:49.317 You've<00:17:48.305> had<00:17:48.450> an<00:17:48.530> incredible<00:17:48.931> career. 00:17:49.413 --> 00:17:50.890 What<00:17:49.574> an<00:17:49.638> incredible<00:17:50.055> company<00:17:50.441> you're<00:17:50.601> running. 00:17:51.404 --> 00:17:52.239 Thanks<00:17:51.629> for<00:17:51.677> everything<00:17:52.046> you<00:17:52.127> do. 00:17:52.608 --> 00:17:53.539 Seriously,<00:17:52.945> thanks<00:17:53.186> for<00:17:53.267> coming<00:17:53.491> on. 00:17:53.845 --> 00:17:54.744 It's<00:17:54.390> my<00:17:54.551> pleasure. 00:17:54.792 --> 00:17:55.771 It<00:17:54.856> was<00:17:54.952> great<00:17:55.113> talking<00:17:55.354> with<00:17:55.498> you,<00:17:55.579> Clint. 00:17:55.932 --> 00:17:56.687 Appreciate<00:17:56.414> it,<00:17:56.478> man. 00:18:09.407 --> 00:18:13.356 Loving<00:18:09.973> you<00:18:10.362> makes<00:18:10.702> the<00:18:11.106> stars<00:18:11.576> shine<00:18:13.049> brighter. 00:18:13.664 --> 00:18:14.036 Yeah. ``` ### The Designers Group CEO Blima Ehrentreu: Building a purpose-driven interior design empire URL: https://www.ceo.com/episodes/the-designers-group-founder-ceo-blima-ehrentreu/ Last updated: 2026-08-24T21:44:41.000Z # The nursing home room that built a design firm In high school, Blima Ehrentreu needed community service hours to graduate. She was assigned to visit a nursing home, where she got close to an older woman and kept coming back for three years. Over that stretch, she watched the woman decline the way people do. Then the facility opened a new building and moved her into it. "I saw how she seemed to be two years younger. I couldn't get over it," Ehrentreu said on the CEO.com Podcast. "I had known her, and from the time I met her, she was increasingly getting older and declining. And all of a sudden, she had this new life. Her room was sunny and airy, and her furniture was new, and she literally was a different person. And I remember thinking then like, wow, it's literally just the building, but the effect is on her." Everything Ehrentreu has built since runs on that observation. She [founded The Designers Group in Toronto in 2009](https://builtworlds.com/news/designing-smart-buildings-qa-designers-group-founder-ceo-blima-ehrentreu/?ref=ceo.com), and it started as two women working together. [She still runs it](https://www.thedesignersgroup.com/our-team?ref=ceo.com). The firm employs [more than 40 people](https://www.connectcre.com/awards/2024-women-in-real-estate-awards/new-york-tri-state/blima-ehrentreu/?ref=ceo.com) and, by its own count, has [completed over 500 projects and four studios](https://www.thedesignersgroup.com/contact?ref=ceo.com): New York, Miami, Toronto, and Los Angeles. It has a construction management arm, TDG Build. In September 2025, it [acquired Interior Images](https://businessofhome.com/articles/compass-acquires-rival-in-1-6-billion-deal-the-laguna-design-center-is-changing-hands-and-more?ref=ceo.com), a Los Angeles firm founded in 1990 specializing in healthcare and senior living, and Interior Images founder Cheryl Sanders came with the deal as senior vice president of healthcare. Senior living was the sector Ehrentreu wanted from the beginning, and she is blunt about why. "People have lived these amazing lives; they're getting older. Why should they decline rapidly?" she said. "Let's try to give them the best possible end-of-life experience, or even that it shouldn't be the end of life. We want them to be able to continue living, socializing, and being happy." Which is why she bristles at the word decorator. Decorating is paint, wallpaper, and furniture. Her firm arrives at the initial concept and asks what a space is meant to be and how it is supposed to function, and before anyone draws anything, the team interviews the people who will use the building. That includes the cleaning crews. "Understanding even that part of the interior has brought us so many ideas," she said. "There are people who see this space from a completely different direction than, let's say, an employee in this space or a resident of this space." Ehrentreu says mental wellness is now a standing item on every project. "I always say if our clients are not the ones keeping it at the forefront of the conversation, we are." Her own schedule is a different matter. There is no typical day. Some mornings she starts at 6:30\. Some days she is on a plane. She says people are forever telling her to book a trainer for 8:30 every morning, and she cannot explain to them why that will not work. Asked about work-life balance, she gave an answer most CEOs would not give on tape. "That aspect I would say I'm probably not the best at because I love what I'm doing, so I don't even necessarily want to balance it," she said. "I want to think about design anywhere I travel, anywhere I go." On the current economy, she was equally direct. "I was just talking about this to a friend the other day, and I was saying if I had anxiety, it would be through the roof right now." Supply chains, then tariffs. Her response to tariffs is procedural. Find local materials and applications. Call the vendors. Learn which goods are actually taxed, because some are not. The gap between what she designs for other people and what she allows herself shows up elsewhere too. She believes strongly that teams should be in the same room, because employees learn from leaders through what nobody says out loud, and none of that survives a video call. The Designers Group runs a hybrid culture anyway, with some employees fully remote, because that is what her people want. She takes the same posture on AI, which she talks about constantly and only partially trusts. Her firm's [press page](https://www.thedesignersgroup.com/press?ref=ceo.com) lists her at BuiltWorlds' 2025 Buildings Conference on a panel about AI in the built environment, plus Ai4, the AI Summit New York, and IMN's AI in Real Estate conference. When consumer tools started generating renderings, roughly 15 people called her in one day asking whether she was about to lay off her team. "We're just as excited as you are with all the technology that's coming out there. The more we can leverage it, the more we can offer it to our clients," she said. "But at the same time, anyone who's worked with ChatGPT on their rendering capabilities knows it's not very accurate, and it's very hard to make any modifications to the rendering." The clearest expression of her thinking is a charity that started as a logistics problem. Ehrentreu was moving apartments and had furniture she did not need. She built a program that matches people giving furniture away with people who need it. She [launched the TDG Furniture Exchange in September 2020 and partnered with Dumbo Movers](https://commercialobserver.com/2022/08/blima-ehrentreu-tdg-design/?ref=ceo.com), which hauls the furniture free in New York. It now operates in [nine cities](https://www.thedesignersgroup.com/furniture-exchange?ref=ceo.com) across three countries. Ask her how a CEO stays healthy, and she does not talk about sleep or boundaries. She asks a question back. "I always ask them, what drives you?" she said. "Because I believe that that is at the root of how we can stay healthy, and how we can stay motivated, and how we can want to get up every day and continue doing what we're doing." It answers the 6:30 mornings and the refusal to schedule the trainer. Ehrentreu has decided that purpose is the wellness strategy. The nursing home resident got a sunny room. Ehrentreu got the work. ```chapters 00:00:00 The Journey to Founding The Designers Group 00:02:14 The Importance of Physical Workspaces 00:05:29 A Day in the Life of a CEO 00:06:56 Designing Collaborative and Engaging Environments 00:09:12 Leveraging AI in the Design Process 00:11:11 The TDG Furniture Exchange and Giving Back 00:13:30 Creating Impact-Driven and Inclusive Spaces 00:16:55 Debunking Misconceptions About Interior Design 00:19:11 Prioritizing Mental Health and Wellness 00:22:03 Navigating Economic Challenges and Tariffs 00:24:33 The Power of Client Opportunities ``` ```vtt WEBVTT 00:00:06.844 --> 00:00:08.528 Lima,<00:00:07.149> thank<00:00:07.309> you<00:00:07.389> so<00:00:07.502> much<00:00:07.726> for<00:00:07.806> coming<00:00:08.127> on<00:00:08.207> the<00:00:08.303> show. 00:00:08.928 --> 00:00:13.176 Give<00:00:09.089> us<00:00:09.249> a<00:00:09.265> sense<00:00:09.634> for<00:00:09.730> how<00:00:09.874> you<00:00:09.970> became<00:00:10.355> 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who<00:25:40.065> you<00:25:40.289> are<00:25:40.450> in<00:25:40.530> the<00:25:40.626> world<00:25:41.092> and<00:25:41.188> your<00:25:41.348> leadership. 00:25:41.910 --> 00:25:44.573 What<00:25:42.054> you've<00:25:42.231> built<00:25:42.455> at<00:25:42.616> The<00:25:42.664> Designers<00:25:43.193> Group<00:25:43.450> is<00:25:43.915> unbelievable. 00:25:44.637 --> 00:25:45.969 Congratulations<00:25:45.503> on<00:25:45.584> everything. 00:25:46.482 --> 00:25:50.252 Would<00:25:46.642> love<00:25:46.867> to<00:25:46.899> have<00:25:47.108> you<00:25:47.204> back,<00:25:47.444> but<00:25:47.605> thank<00:25:47.829> you<00:25:47.910> for<00:25:48.567> sharing<00:25:48.969> your<00:25:49.113> wisdom<00:25:49.450> and<00:25:49.530> time<00:25:49.771> with<00:25:49.931> us<00:25:50.075> today. 00:25:50.797 --> 00:25:51.792 Thank<00:25:50.974> you<00:25:51.134> for<00:25:51.263> having<00:25:51.600> me. 00:25:52.257 --> 00:25:52.995 Really<00:25:52.498> appreciate<00:25:52.915> it. 00:25:53.043 --> 00:25:53.685 Thanks<00:25:53.220> so<00:25:53.316> much. 00:26:06.305 --> 00:26:10.239 Loving<00:26:06.934> you<00:26:07.256> makes<00:26:07.659> the<00:26:07.998> stars<00:26:09.046> shine<00:26:09.933> brighter. 00:26:10.400 --> 00:26:10.964 Yeah. ``` ### What does a CEO do? The responsibilities behind the title URL: https://www.ceo.com/blog/what-does-a-ceo-do-the-responsibilities-behind-the-title/ Last updated: 2026-08-29T22:31:08.000Z The title **CEO** — short for **Chief Executive Officer** — often conjures images of corner offices, high-stakes decisions, and power suits. But beyond the symbolism, you might be wondering: **What does a CEO actually do?** Whether you’re a student, an entry-level employee, or a future business leader, understanding the role of a CEO is essential to grasping how organizations operate from the top down. In this article, we’ll break down: - What the CEO is responsible for - Their day-to-day tasks - The difference between CEO and other executive roles - How their decisions impact the entire company --- ### **The CEO’s Core Role: Strategy and Leadership** At the highest level, the **CEO is responsible for setting the company’s direction and ensuring it gets there.** They oversee everything from long-term strategy to short-term execution, acting as the **visionary** and **decision-maker** who ties together the company’s moving parts. **TF-IDF Integration:** Phrases like “CEO responsibilities,” “what a CEO does,” “Chief Executive Officer,” “strategic direction,” and “business leadership” help reinforce relevance around the core phrase **“what does a CEO do”**. --- ### **Responsibilities of a CEO** While the specifics can vary depending on the size and nature of the business, here are the primary duties shared by most Chief Executive Officers: **1\. Set Company Vision and Strategy** The CEO defines the long-term goals of the company and maps out the strategy to achieve them. This includes deciding which markets to enter, products to launch, and how to stay competitive. **2\. Build and Lead the Executive Team** The CEO hires, manages, and evaluates other C-suite executives — like the CFO (Chief Financial Officer), COO (Chief Operating Officer), and CTO (Chief Technology Officer). Together, they turn strategy into execution. **3\. Make Major Corporate Decisions** From mergers and acquisitions to restructures and pivots, the CEO makes the final call on high-impact decisions that affect the entire organization. **4\. Serve as the Public Face of the Company** CEOs often represent the company in media interviews, investor meetings, and board presentations. Their words can influence stock prices, public opinion, and brand reputation. **5\. Align Culture with Vision** Company culture begins at the top. A strong CEO inspires teams, sets behavioral standards, and reinforces core values across the organization. --- ### **What Does a CEO Do Day-to-Day?** No two days are the same for a CEO, but here’s a typical breakdown: - **Morning strategy calls** with department heads - **Investor updates or board meetings** - **Analyzing performance reports** - **Making hiring or budget decisions** - **Speaking at events or media interviews** - **Reviewing key initiatives and market trends** In small companies, the CEO might be involved in everything from product design to marketing. In large corporations, they’re focused on high-level leadership and communication. ### **CEO vs. Other Executive Roles** Let’s clear up some common confusion: CEO, Chief Executive Officer: Big-picture strategy and decision-making COO, Chief Operating Officer: Internal operations and logistics CFO, Chief Financial Officer: Financial planning and risk management CTO, Chief Technology Officer: Tech innovation and infrastructure While all are critical, the **CEO has final accountability** for company performance and direction. --- ### **How Does a CEO Impact a Company?** A CEO’s influence goes far beyond meetings and memos. They impact: - **Stock performance** (especially in public companies) - **Employee morale and retention** - **Brand reputation** - **Customer trust** - **Revenue growth and innovation** Poor leadership at the CEO level can sink even the most promising companies. Great leadership can drive exponential growth. --- ### **Skills That Make a Great CEO** To truly understand **what a CEO does**, you need to look beyond tasks and focus on skills. The best CEOs consistently demonstrate: - **Visionary thinking** - **Resilience and adaptability** - **Clear communication** - **Emotional intelligence** - **Strategic decision-making** These traits enable them to guide teams, handle crises, and lead organizations through growth and change. --- ### **Examples of High-Impact CEOs** If you’re wondering **what a CEO does** in the real world, look no further than: - **Satya Nadella** – Transformed Microsoft’s culture and cloud business - **Mary Barra** – Driving General Motors into an electric future - **Elon Musk** – Leading innovation at Tesla and SpaceX - **Tim Cook** – Sustaining Apple’s dominance after Steve Jobs These leaders show that CEOs shape more than companies — they shape industries. --- ### **Final Thoughts: What Does a CEO Do?** To answer the question once and for all: **A CEO leads, decides, inspires, and drives.** The job is part strategist, part diplomat, part visionary — and all accountability. If you’re aiming for the role one day, start thinking like a CEO now: - Learn how all parts of a business function - Take ownership of your work - Build the skills to lead people and make tough decisions Because when you finally land that corner office, **what a CEO does**… will be what *you* do. --- ### **FAQs: What Does a CEO Do?** **Q: Is a CEO responsible for day-to-day operations?** A: Not always. In larger companies, operations are typically handled by the COO, while the CEO focuses on strategy and leadership. **Q: Do all companies have CEOs?** A: Most corporations do, but small businesses and startups may use titles like founder or president instead. **Q: Can a CEO be fired?** A: Yes. The board of directors has the authority to remove the CEO if performance expectations aren’t met. **Q: Who reports to the CEO?** A: Typically, the C-suite executives (CFO, COO, etc.) report directly to the CEO. _Truncated after 5 MiB. Use `/sitemap.xml` for the complete archive of public content._