Podcast
The CTO Compass
Hosted by Mark Wormgoor · EN
The CTO Compass is a podcast about CTO, CIO, and tech leadership - on strategy, scaling, teams & bringing clarity to technology leadership for real boardroom impact.
Hosted by Mark Wormgoor, each episode features candid conversations with experienced CTOs, CIOs, and senior tech leaders from startups through to large enterprises.
The focus is on the real work of leading in tech:
– Setting clear tech strategy that aligns with business goals
– Scaling teams and culture
– Making high-stakes decisions under pressure
– Navigating the transition from hands-on engineer to executive leader
This is not a hype show, nor a theoretical leadership podcast. Guests share hard-won lessons, mistakes, and practical insights from the moments that mattered most - when clarity was missing, heavy decisions needed to be made, and leadership was tested.
If you’re a CTO, CIO, or tech leader looking to sharpen your thinking, increase your influence, and create real impact in the boardroom, The CTO Compass is built for you.
17episodes
Episodes
Newest firstAll episodes
3 Critical Career Mistakes Engineering Leaders Make ft. Limor Bergman Gross
1w ago00:42:43Tap to summarizeThis episode focuses on the transition from technical execution to organizational impact. Limor Bergman Gross shares how many engineering managers get stuck because they focus solely on being good at their jobs. She explains that promotion to director or VP levels requires a shift in focus. It is no longer about how well you code or manage a sprint, but about how well the organization knows your impact.The conversation explores the "trust gap," where leaders mistakenly believe their direct manager is the only one who needs to see their value. Limor and Mark discuss the necessity of building strategic relationships across the company. They provide a framework for stakeholder management that relies on curiosity and solving business problems rather than internal politics. This approach helps technical leaders gain the visibility needed for executive roles.Finally, the discussion covers the practicalities of leadership like delegating effectively and giving direct feedback. Limor highlights the "busy trap" where leaders fill their schedules with low-impact tasks to feel productive. She offers strategies for pushing back on non-essential requests to create space for strategy. The episode concludes with advice on using the Radical Candor framework to build high-performing teams through clear, empathetic communication.About LimorLimor Bergman Gross is a former Director of Engineering with over 20 years of experience across software engineering, engineering management, and organizational leadership. She has led teams through growth, scaling pressure, and complex delivery environments, working closely with CTOs and senior executives to align technology, people, and business priorities.Known early in her career as the “reliable leader” and escalation point, Limor learned firsthand how high-performing leaders can unintentionally become bottlenecks at scale. Today, she works as an executive leadership coach with senior engineering leaders and CTO-adjacent roles, helping them transition from hands-on decision-makers to strategic leaders who build teams that think, decide, and execute independently.Her work focuses on decision-making, ownership, leadership culture, and the real trade-offs tech leaders face as they move from execution to executive impact.Chapters00:00 Software Engineer to Leadership06:33 Getting Promoted14:39 Ad15:11 What are You Busy With?20:26 How to Give Feedback22:53 Female Engineers!24:50 Coaching The Executives29:08 Ad29:19 Getting Unstuck36:54 Working with Different People40:45 What is Your Impact?Where to find Limor• Website: https://limorbergman.com/podcast/• LinkedIn: https://www.linkedin.com/in/limorbergman/• Instagram: https://instagram.com/limorbergman• YouTube: https://www.youtube.com/@LimorBergman
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Your AI Strategy Will Fail for the Same Reason Your Last ERP Did ft. Abhijit Verekar
2w ago00:36:06Tap to summarizeMost large-scale technology projects don't fail because the software is broken; they fail because the incentives are misaligned long before the first line of code is written. AV, founder of Avira Advisors and author of Start at Zero, joins Mark Wormgoor to discuss why massive ERP implementations, like the Birmingham City Council’s £200 million disaster spiral out of control and how tech leaders can prevent the same history from repeating itself with AI.AV argues that the "abusive" nature of traditional consulting often stems from a lack of "Phase Zero" preparation. Organizations frequently jump into software selection and vendor RFPs without understanding their own internal processes, political buy-in, or desired outcomes. By the time an implementation partner is on-site, the customer has already lost their leverage, leading to endless change orders and "fluffy" risk registers where every red flag is painted green.As we move into the age of AI, AV sees enterprises making the exact same mistakes: chasing shiny "agentic" products before they have established data sovereignty or governance. This conversation serves as a pressure-test for any leader about to sign off on a major digital transformation. AV shares how to reclaim ownership of your data, align consultant incentives with business value, and why the future of consulting belongs to those who can bridge the gap between AI-native thinking and human judgment.Key Takeaways• Success in high-stakes projects is determined before the RFP; spend time documenting processes and securing political buy-in before talking to vendors.• Traditional consulting can become "abusive" when vendors dictate timelines and products based on their own sales targets rather than the client's actual needs.• In the AI era, leaders must ensure they own their data and can move it between third-party tools rather than being locked into a single SaaS provider's ecosystem.• Like ERP, AI adoption fails when it is treated as a product-first purchase instead of a business-process transformation requiring clean data and human oversight.• The traditional billable-hour model is collapsing; value now lies in senior-level judgment, "blameability," and the ability to integrate AI "Lego bricks" into delivery.• While AI can automate the "grunt work" of deliverables, final accountability must always rest with a seasoned human expert who carries the risk of the decision.About AVAV is the CEO of Avero Advisors, a government consulting firm he built from zero to $7.5 million over the last ten years. He's spent two decades helping state and local agencies navigate ERP implementations, AI strategy, and digital transformation, and he's been in the room for a majority of these engagements. He's currently writing a book called Start at Zero and rebuilding his firm around AI agents that handle everything from business development to content production and delivery.Before Avero, AV spent a decade inside the traditional consulting world learning how the machine worked before deciding to build something different. Avero operates as the buyer's agent for government agencies, sitting on their side of the table instead of the vendor's. The firm has grown to a team of around 40 to 50 people, including a Global Innovations Center.Outside of consulting, AV is an active investor. He's invested in BSG Hospitality and Market Square Ventures, applying the same builder's mindset to opportunities outside of govtech.When he's not running the firm or writing, you'll probably find him on a motorcycle. He's an avid rider who uses long rides the same way some people use meditation: to think, decompress, and come back with clarity.AV brings a rare combination to any conversation: deep technical credibility in government technology, real experience bootstrapping and scaling a services business, and an honest willingness to talk about what he got wrong along the way. He's not going to give your listeners a sales pitch. He's going to give them something useful.Chapters00:00 When Consulting Becomes Abusive08:46 Laying Down the Foundation!11:43 Ad12:14 Private Companies vs Private Sectors16:51 Excited AI Implementation20:26 AI's Impact27:09 Ad27:20 How do You see the Future?32:29 Starting Out Today!Where to find AV• Website: www.averoadvisors.com• LinkedIn: https://linkedin.com/in/verekar/• Instagram: https://www.instagram.com/verekar/• Twitter: https://x.com/AbhijitVerekarAV’s Bookhttps://www.amazon.com/Start-Zero-Leading-Stakes-Modernization/dp/B0GZFQLDJ3
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Why Organizational Change Fails: The Hidden Politics and Self-Interest Killing Your Transformation ft. Bud Caddell
3w ago00:51:11Tap to summarizeMark Wormgoor sits down with Bud Caddell, founder of NOBL, to explore the human friction that often stalls massive technology initiatives. Bud shares his transition from a software developer to a change management expert, triggered by witnessing "shiny" innovation projects collapse under the weight of organizational politics and conflicting incentives. The conversation dives deep into why many digital transformations are dead on arrival, often due to manufactured urgency and a lack of focus that spreads leadership teams too thin.The discussion shifts toward practical strategies for overcoming these barriers, with Bud advocating for a "piecemeal" approach to organizational change. Rather than following a rigid, 200-slide consultant deck, he suggests using "safe to fail" experiments to surface hidden politics and resistance early in the process. They also tackle the evolving role of the CTO in the age of AI, discussing how tech leaders are gaining unprecedented power but risking their internal relationships by failing to build empathy with the teams impacted by these rapid shifts.Finally, Bud addresses the growing issue of organizational cynicism and the "trust gap" between leaders and employees. He argues that the antidote to mass change fatigue isn't better technology, but radical honesty and transparency regarding what an organization can and cannot control. The episode concludes with a look at how leaders can build resilience by moving away from purely visionary "Steve Jobs" personas toward a more grounded, transactional, and honest theory of leadership.Key Takeaways• Many projects fail not because of the tech, but because "manufactured urgency" exhausts the organization’s attention span before the change can take root.• Avoid "rip the band-aid off" transitions; instead, use small, iterative experiments to discover where political resistance and sabotage actually live.• Apply agile experimentation to cultural rituals and habits, but use traditional stakeholder mapping and steering committees for high-risk reorgs or core system implementations.• Recognize that most "sabotage" is actually people protecting their teams or resources; breaking through requires negotiating power and resources rather than just fighting for a meritocracy.• As AI pushes more power toward the CTO, be careful not to burn bridges with other executives; success depends on building a coalition, not just wielding technical influence.• To reduce change fatigue, stop over-promising; be transparent with employees about layoffs, market pressures, and the specific limitations of your control.About BudBud Caddell is the Founder and CEO of NOBL, a global transformation consultancy reshaping how organizations adapt to change. Since 2014, he has led more than 120 engagements across five continents, helping companies in more than 20 industries, including Nike, Ford, CNN, and HBO, navigate disruption, repair dysfunctional cultures, and build resilient teams.Recognized by The Guardian as one of the “strategists to watch” and named one of Business Insider’s “most creative people under 30,” Bud’s work has been featured in The New York Times, The Wall Street Journal, Forbes, and AdAge. Before launching NOBL, he was a Partner at Undercurrent and served as SVP of Digital Strategy and Innovation at Deutsch LA.Bud Caddell is a distinguished speaker and guest, having delivered keynote addresses at SXSW, TEDx, and the Reuters Strategic Marketing Conference. His core message emphasizes that organizational failures rarely result from a lack of ideas. Instead, they stem from cultural, political, and psychological barriers that prevent those ideas from succeeding.He is available to provide expert commentary on leadership and organizational change, including how executives can sustain trust and momentum during crises, why workplace cultures often falter in execution, and how to foster environments where innovation thrives. He also addresses the evolving expectations of employees in the future of work, explains why the majority of brand and business transformations fail, and offers strategies to design change that lasts.Chapters00:00 Getting Into Change Management07:26 What Kills Great Ideas?14:05 Aligning Individual Self-Interests17:25 Ad17:56 The Reality of Reorganization27:35 Unexpected Transformation31:02 Looking for Change!34:50 Ad35:00 Team Capacity vs Company Demand40:30 CTOs Have Power!47:06 Organizational CynicismWhere to find Bud• Website: https://nobl.io• LinkedIn: https://www.linkedin.com/in/budcaddell
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We Sacrifice People for Performance. AI Is About to Make That Impossible ft. Margôt van Brakel
Apr 2400:47:31Tap to summarizeThis episode challenges a core assumption most tech leaders still operate under: that intelligence is our primary advantage. As AI systems begin to outperform humans in reasoning and decision-making, this conversation reframes AI not as another step in the industrial revolution, but as the start of an intelligence revolution. For CTOs and business leaders, this shift forces a deeper question. If machines can think, what is left for humans to lead?You’ll learn why performance-driven organizations are hitting a ceiling and why continuing to optimize for efficiency alone will limit long-term value. The discussion explores a transition already underway, from purely economic thinking toward purpose, connection, and responsibility. It also highlights how board-level conversations are evolving, moving from short-term business cases to broader value-based decisions that shape the future of the organization and society.The episode also brings this down to action. It outlines how leaders and teams can respond today through experimentation, curiosity, and intentional time spent on change rather than just execution. You’ll walk away with a clearer perspective on how to position your organization in a world where AI handles more of the thinking, and where leadership is defined by the ability to rethink strategy, culture, and human contribution at a fundamental level.Key Takeaways• AI is replacing not just manual work but cognitive work, forcing leaders to redefine human value beyond intelligence• Performance-driven cultures are reaching their limits; future organizations must prioritize meaning, connection, and long-term value• Strategy must shift from pure business cases to value cases, balancing today’s results with tomorrow’s impact• Leaders should foster experimentation by allocating time for learning, not just execution, to unlock AI’s real potential• Organizations that combine human strengths with AI effectively will outpace slower, legacy-driven competitors• The most critical leadership skill ahead is not control, but curiosity, responsibility, and the ability to rethink assumptionsAbout MargôtMargôt van Brakel is a keynote speaker, author, and advisor with more than 20 years of experience guiding organizations through complex change. She works with boards and executive teams on the human side of AI — exploring how organizations can use technology as a means, not an end, and find the right balance between people and machines. Her work focuses on what it means to keep human value at the center of organizational transformation. Because this is not the next wave in the industrial revolution — it is a new one. And that changes everything about the questions leaders need to ask.Chapters00:00 Margôt Journey05:42 Treating People as Machines12:38 AI's Societal Impact12:06 Ad20:32 What is Your Responsibility?26:00 What is Homo Conexus?39:01 Ad38:12 The Ugly Phase of Transformation42:25 A Hopeful Perspective!Where to find Margôt• Website: https://margotvanbrakel.com• LinkedIn: https://www.linkedin.com/in/margotvanbrakel/• Instagram: https://www.instagram.com/margotvanbrakel/
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How User Psychology Grew a Dating App to 17 Million Users With Almost No Marketing Budget ft. Colin Hodge
Apr 1700:36:40Tap to summarizeColin shares the raw, behind-the-scenes reality of moving from a cushy engineering role at Microsoft to the high-stakes environment of a Silicon Valley accelerator. He discusses the pivotal "moment of liberation" when he admitted his initial startup idea was failing, a realization that cleared the path for him to co-found a viral sensation overnight.The conversation dives deep into the intersection of technology and user psychology. Colin explains how understanding human behavior allowed him to scale a product to 17 million users and later lead growth for a live-streaming giant in Asia with over 100 million users. He breaks down why technical leaders must look beyond the code to understand the "psychological levers" of their customers, whether they are building B2C dating apps or complex B2B platforms.Mark and Colin also explore the evolving role of the CTO in the age of AI. Colin argues that as AI makes the digital landscape noisier and more automated, the competitive advantage shifts to leaders who can empathize and connect with people. This episode is a masterclass in growth strategy, the psychology of negotiation, and why "judgment" is the most valuable asset a tech leader can bring to the boardroom.Key TakeawaysThe Power of Admitting Failure: Admitting a product is failing is often the necessary liberation to clear the path for a high-growth idea.Psychology Over Code: Growth is driven by understanding the psychological levers of acquisition and retention rather than just adding features.The AI Human Advantage: As AI automates digital noise, the primary competitive edge for leaders shifts toward human empathy and judgment.Strategic Friction: Real growth involves framing user choices and occasionally adding "good friction" to nudge people toward higher-value actions.Team Empathy as a Lever: Success requires framing technical decisions with the team's emotions in mind to ensure smooth execution.Pricing Strategy as Growth: Behavioral triggers, like the "second cheapest bottle" effect, can be applied to tech products to increase revenue.Chapters00:00 The 14 Year-old Company Owner05:47 Launching DOWN12:54 Ad13:26 The Controversial "Bang With Friends"17:42 "Outrageous Startup Growth"24:18 Ad24:29 Psychology as a Foundation!28:14 Standing Out Through The AI Noise30:10 Past Advice and Future Plans!33:22 Behavioral Improvement and Empathetic ApproachAbout ColinColin Hodge is a seasoned entrepreneur and growth expert with over 17 years of experience scaling businesses to over 100 million users. His expertise lies in organic growth, user psychology, and disruptive marketing. Colin co-founded and grew 'Bang with Friends' (later DOWN) to over 6 million users organically before selling it, and later re-acquired and grew it into a top 5 US dating app. He has also served on the board of a Silicon Valley social media company, contributing to over $200 million in annual revenue, and acted as Chief Growth Officer for 17Live, Asia's leading live-streaming app, where he led its US launch. Colin's approach is rooted in understanding user psychology to drive authentic, sustainable growth, and he is passionate about sharing his lessons with fellow founders and marketers.Where to find ColinWebsite: https://colinhodge.com/LinkedIn: https://linkedin.com/in/ckbhodgeInstagram: https://instagram.com/ckbhodgeColin's Book: Outrageous Startup Growth: Uncovering the Secrets of User Psychology to Scale Your Success: https://www.amazon.com/Outrageous-Startup-Growth-Uncovering-Psychology/dp/1394387334
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Why 95% of AI Pilots Deliver Zero Business Impact and How to Fix Your Foundation ft. Matt Soltau
Apr 1000:53:29Tap to summarizeMost AI projects don’t fail because of bad models. They fail because the data underneath is broken.Matt Soltau breaks down why “AI readiness” is really a data problem and why most organizations are building on fragile, disconnected systems that can’t survive outside a demo. From hidden data silos to untraceable pipelines and compliance risks, this conversation exposes the real reason AI initiatives stall and what CTOs must fix before scaling anything to production.You’ll learn how to move from spaghetti architecture to controlled, traceable data flows, why integration strategy matters more than the latest AI tool, and how to build a foundation that actually supports long-term AI value. If your board is pushing for AI but your systems feel messy underneath, this episode will show you where to start and what to avoid.Key TakeawaysWhy most AI pilots fail to deliver business impact despite working in sandbox environmentsThe hidden risk of disconnected data pipelines and how they break AI in productionEarly warning signs your data foundation is not ready for AIWhy point-to-point integrations create long-term complexity and technical debtHow to design scalable data architecture using integration layers instead of “spaghetti systems”A practical starting point: how to move from one controlled use case to enterprise-wide AI adoptionAbout MattMatt Soltau is a Global Director of Strategy & Operations at IntelliPaaS, an AI‑ready data integration and workflow automation platform for enterprises and regulated organizations. With nearly a decade spent connecting siloed systems, automating complex processes and making data trustworthy for AI. He helps leaders turn fragile tech stacks into secure, compliant workflows that actually scale and drive real business results.Chapters00:00 Dangerous AI Assumption09:37 Why Pragmatic Solutions aren't Enough15:08 Ad15:40 How Important is Compliance?22:29 When Does the Problem Start?28:59 Working with Enterprise Organizations34:17 Dealing with Compliance Complexity39:07 Ad39:19 Expensive Integration Mistakes46:26 Controlling Your Data Foundation!Where to find MattWebsite: https://www.intellipaas.io/LinkedIn: https://www.linkedin.com/in/soltaumatt/YouTube: https://www.youtube.com/@IntelliPaaS
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The Software That Can’t Be Wrong: Building Fintech for Millions in Africa ft. Erioluwa Asiru
Apr 300:33:25Tap to summarizeWhat happens when you take a trust-based, offline financial system and turn it into software that people depend on with their money? In this episode, Erioluwa shares the real pressure behind building a fintech startup in Nigeria, where every product decision, line of code, and feature trade-off directly impacts user trust and financial safety.For startup founders, this conversation goes beyond fintech. It reveals what it actually takes to move users from familiar, manual systems into digital products, how to balance growth with risk, and why sometimes the best product decision is not building a feature at all. From early traction challenges to scaling a lean engineering team, this episode breaks down the realities of building something people rely on financially, not just functionally.You’ll also hear how trust becomes the real product, why simplifying solutions often beats complex engineering, and what changes when your users’ money, not just their attention, is on the line.Key TakeawaysWhy fintech changes engineering standards completely and why “good enough” code is never acceptableHow to balance product growth with fraud prevention and system riskA practical approach to deciding which features to build or reject based on risk vs returnHow to scale a lean engineering team without introducing unnecessary process overheadWhy raising the bar for users can be more effective than building complex safeguardsThe shift from writing code to leading people, making trade-offs, and owning outcomesAbout ErioluwaErioluwa Asiru is a software engineer, technology leader, and mentor, serving as CTO and Cofounder of Circle Funds. She leads the company’s technical vision, building scalable financial infrastructure and products that expand access to funding and wealth-building opportunities. Her work combines hands-on engineering with strategic leadership, ensuring reliable systems and strong product execution.Alongside her role as a founder, Erioluwa is a lead mentor at Data Epic, where she guides cohorts through intensive six-month programs in data and software engineering. She is passionate about developing practical skills, fostering confidence, and helping aspiring professionals transition into successful tech careers.Erioluwa has delivered a wide range of impactful solutions, including digital savings platforms, creator financing systems, admin portals, and automated data analysis tools. Driven by innovation, education, and economic empowerment, she is committed to building technology that creates real opportunities while mentoring the next generation of tech talent.Chapters00:00 What is Ajo?06:56 Ad07:28 Working in Nigerian Financial Technology13:35 Fraud, Features, and Leadership22:51 Ad23:03 Complicated Solutions and Inspiration26:38 The Future of Circle Funds29:46 Mentorship Experience31:05 You Need a Community!Where to find ErioluwaWebsite: https://circlefunds.ioLinkedIn: https://www.linkedin.com/in/asiru-erioluwa/
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3 Ways to Build AI Systems That Survive the Real World ft. Sairam Sundaresan
Mar 2700:42:43Tap to summarizeMost AI initiatives don’t fail because of weak models. They fail because they collapse under real-world complexity. This episode breaks down how CTOs and business leaders can design AI systems that survive messy data, unpredictable users, and production reality.You’ll learn how to shift from “build a model” thinking to system-level strategy, manage AI as a high-risk investment, and align business expectations with technical uncertainty.Key Takeaways• Why AI success depends more on system design than model performance• How to build guardrails, monitoring, and rollback into AI from day one• The “VC mindset” for AI investments and why most initiatives will fail before one works• How to align CEOs and boards around uncertainty, cost, and probabilistic outcomes• The real reason AI breaks in production and how to anticipate failure modes early• What skills modern AI teams need as roles shift from building models to orchestrating systemsAbout SairamSairam Sundaresan is an AI Engineering Leader with over 15 years of R&D experience. Currently leading autonomous driving research at Valeo, he has a history of innovation at Intel Labs and Qualcomm, backed by a portfolio of patents and publications.Beyond his technical roles, Sairam is deeply invested in the growth of the AI ecosystem. He has mentored countless engineers, served as a Lead at the Frontier Development Lab (FDL) applying AI to space science, and actively advises business leaders on AI adoption.He is also the author of the book 'AI for the Rest of Us' (Bloomsbury) and writes Gradient Ascent, an illustrated newsletter read by over 25,000 subscribers. Through these channels and his LinkedIn following of over 100,000, he is one of the industry's most trusted voices for making AI accessible.Chapters00:00 Industry Real World Failures05:26 Reliability of AI Models11:24 Ad11:57 "AI for the Rest of Us"16:28 Starting With AI24:54 Explaining AI to the Board27:37 Ad27:48 AI Unrealistic Expectations32:42 What kind of People does AI Demand?36:49 Keeping Up with AI39:15 AI PredictionsWhere to find Sairam• Website: https://newsletter.artofsaience.com• LinkedIn: https://www.linkedin.com/in/sairam-sundaresan/• Instagram: https://www.instagram.com/artofsaience/• YouTube: https://www.youtube.com/@artofsaience• His Book: https://www.amazon.com/AI-Rest-Us-Illustrated-Introduction/dp/B0F29THNLT/
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AI Risk Is a Design Problem: 3 Questions Every CTO Should Ask Before Their Next AI Release ft. Jill Stover Heinze
Mar 2000:41:43Tap to summarizeMost AI strategies fail before anything ships, not because of the tech, but because leaders never test assumptions against reality. In this episode, CTOs will learn how to ground AI strategy in real user behavior, reduce risk early, and avoid costly AI failures before they scale.Jill Stover-Heinze breaks down how generative AI changes the risk model, why non-deterministic systems demand new leadership thinking, and how CTOs can turn governance, user research, and risk into a competitive advantage instead of a bottleneck.Key TakeawaysWhy most AI strategies fail before build and how to validate ideas against real user behaviorHow generative AI changes risk and why non-deterministic systems require new leadership thinkingHow to use risk and governance as a design tool instead of a compliance exerciseWhy product-market fit still kills AI initiatives and how to avoid building the wrong thingWhat to ask your board and teams to move fast without falling into AI hype and costly mistakesAbout JillJill Heinze helps product leaders make smarter AI decisions through strategic intelligence and ground truth research. As founder of Saddle-Stitch Consulting, she brings 20 years of user research and competitive intelligence experience to help organizations navigate AI uncertainty, revealing what competitors miss and avoiding expensive mistakes before they happen. She serves as Responsible AI Program Director for The American College of Financial Services and hosts Responsible Tech Talks on LinkedIn Live.Chapters00:00 The Ground Truth04:38 AI's Hidden Consequences (NIST)12:47 Ad13:19 Approaching AI as a CTO18:45 FOMO in the Corporate World22:57 Keeping Up with AI28:42 Ad28:53 Effectively Using AI37:27 Talk to Your People!Where to find JillWebsite: https://www.saddlestitchconsulting.comLinkedIn: https://www.linkedin.com/in/jill-stover-heinze/Instagram: https://www.instagram.com/jill_saddlestitchconsult/YouTube: https://www.youtube.com/@JillHeinze-SaddleStitchConsultFacebook: https://www.facebook.com/profile.php?id=61581363390571TikTok: https://www.tiktok.com/@jill_saddlestitchconsult
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AGENTS.md Won’t Save You: Design AI Systems You Can Actually Control ft. Craig Kaplan
Mar 1300:52:27Tap to summarizeAI is moving from copilots to autonomous agents, and most tech leaders are not prepared for what that shift means. Craig walks through the real risks behind superintelligence, why AI checking AI is becoming inevitable, and how CTOs and CIOs can design safer, more resilient systems before autonomy outpaces human oversightRather than focusing on hype, this episode dives into the alignment problem, the limits of guardrails, and why monolithic black box models may be the wrong long term architecture.You will hear a practical path forward for tech leaders who are already overwhelmed by AI generated code, agent frameworks, and rapidly evolving modelsIf you are leading engineering, AI, or technology strategy, this episode will challenge how you think about safety, governance, autonomy, and the future role of the CTO in an AI driven world.Key TakeawaysWhy AI checking AI is not optional as code generation and autonomy scaleWhat the alignment problem really means for enterprise technology leadersThe limits of guardrails and why prevention at design stage beats patching at deploymentHow democratic architectures of multiple agents can reduce systemic riskWhy vendor agnostic, multi model strategies increase resilience and strategic controlHow to embed company values into AI systems through training, memory, and architectureWhat P(doom) represents and why many leading researchers assign it far higher risk than most executives assumeAbout CraigDr. Craig A. Kaplan is a renowned expert in artificial intelligence, artificial general intelligence, and superintelligence, with a focus on collective intelligence and quantitative modeling. He is the Founder of Superintellligence.com and CEO and founder of iQ Company, a consulting firm dedicated to advanced AGI and SI systems. Previously, he founded PredictWallStreet, a financial services firm that powered top hedge fund performance by leveraging the collective intelligence of retail investors. Dr. Kaplan has authored a book, published extensively in scientific journals, and holds numerous patents on AI-related technologies.Chapters00:00 How far is AGI?06:55 What is P(doom)?16:43 AI Reviewing AI Output20:54 Dealing with Bad Actors (Human or AI)25:36 Approaching AI as a Small Scale CTO30:43 Democracy of AI Agents35:15 AI Safety Conferences40:03 AI Models, Open-Source or Big Company?45:05 Is AI Adoption Keeping Up?Where to find CraigLinkedIn: https://www.linkedin.com/in/craigakaplanWebsite: https://www.superintelligence.comWebsite: https://iqco.comYouTube: https://www.youtube.com/@iqstudios1
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