Beyond the Prompt dives deep into the world of AI and its expanding impact on business and daily work. Hosted by Jeremy Utley of Stanford's d.school, alongside Henrik Werdelin, an entrepreneur known for starting BarkBox, prehype and other startups, each episode features conversations with innovators and leaders to uncover pragmatic stories of how organizations leverage AI to accelerate success. Learn creative strategies and actionable tactics you can apply right away as AI capabilities advance exponentially.
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Données mises à jour le 01/10/2026
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What Will You Do With the Time AI Gives Back to You? - with Alex Kuilman, Founder of The Practice
Épisode 81
mercredi 30 septembre 2026 • Durée 01:04:20
Alexander Kuilman works with CEOs and executive teams to bring more humanity into how they lead. He joins Henrik and Jeremy to explore why, if leaders know AI matters, getting people to actually use it can still be so difficult.
Using Bob Kegan and Lisa Lahey’s Immunity to Change framework, Alex argues that “I don’t have time” can mask deeper fears about competence, relevance, and what happens when AI can do work you previously thought made you valuable. They also explore why psychological safety matters if people are going to admit what they don’t know and actually experiment.
The conversation ends with the “AI vampire” and Alex’s idea of “corporate numbing”: AI makes us more productive, but instead of taking the time back, we often fill it with more work. Which leaves a bigger question: when AI gives us time back, what do we actually want to do with it?
Key Takeaways:
AI resistance may be about fear, not time “I don’t have time” can mask deeper fears about competence, relevance, and what happens when AI can do work you thought made you valuable.
People need to feel safe enough to experiment Psychological safety gives people room to admit what they don’t know, try something new, and risk looking incompetent.
How leaders make people feel matters Henrik and Jeremy realize that some of the AI leaders they admire don’t just have good tactics. They make people around them feel safe enough to try.
Don’t let AI give you more work The “AI vampire” turns productivity gains into more work. Alex’s idea of “corporate numbing” asks whether staying busy is sometimes easier than deciding what we actually want to do with the time AI gives back. Alex Kuilman (transcript - fina…
00:00 Intro: The Problem of Corporate Numbing 00:23 Meet Alexander Kuilman 04:45 Why Aren’t People Using AI More? 06:49 The Hidden Assumptions Blocking Change 08:08 Jeremy’s Travel Problem 14:12 What Are People Really Afraid of With AI? 16:02 Stop Making Time to Experiment 22:25 Psychological Safety and AI Adoption 32:56 How to Hold Yourself 38:57 The Leaders Who Make People Feel Safe 40:33 What If AI Helps Us Think Less? 44:13 The AI Vampire 46:10 Corporate Numbing 54:08 Your Humanity Is the Advantage 58:05 The Debrief
How Do You Run a Company When You Can’t See Six Months Ahead? - with Axios CEO Jim VandeHei
Épisode 80
mercredi 16 septembre 2026 • Durée 01:02:24
Jim VandeHei joins Henrik and Jeremy around the launch of his new book, Simplify: Do 50% More With 50% Less, co-authored with Mike Allen and Roy Schwartz. In the conversation, Jim shares how he’s leading Axios through AI, from turning himself into an “AI lab rat” to rethinking how the company works.
At Axios, Jim gave everyone access to ChatGPT, brought in training, and invited employees who took naturally to the technology to help others across the company. He also shares how AI fellows working directly with him prototype new ideas, why companies should delete unnecessary work before automating it, and how Axios is preparing for a world where more information moves from the open web into social platforms and personalized LLMs.
The conversation ends with a bigger question: what story are we telling people about an AI-enabled future? Jim worries that the negative case for AI is vivid and easy to understand, while the positive case often amounts to curing cancer or eliminating work. He makes the case for something more tangible: using AI to make people’s work and lives better while preserving human connection and the feeling that what people do still matters.
Leaders need to become AI lab rats Leaders need firsthand experience with AI to understand what it can do and give others permission to experiment.
Give the CEO an AI “SEAL team” Jim’s AI fellows help him prototype ideas quickly, stay current, and experiment outside the normal company processes.
Before using AI to make existing work faster, ask which meetings, processes, and activities shouldn’t exist at all.
From Knowledge Worker to Intelligence Worker: Why Human Judgment Matters More With AI - with OpenAI’s Brice Challamel
Épisode 79
mercredi 2 septembre 2026 • Durée 01:13:00
After helping lead AI adoption at Moderna, Brice Chalamel has a new goal at OpenAI: help create 1,000 AI adoption success stories across large organizations.
Brice takes Henrik and Jeremy inside how work happens at OpenAI, where Slack has largely replaced internal email, agents help process information and draft responses, and some workflows are already moving agent to agent. But as AI takes on more responsibility, Brice argues that trust can’t be mandated. It has to be earned.
The conversation goes beyond tools into what it actually takes to lead people through change. Brice explains why, in a ten-step journey, nine steps may only be halfway, why our existing mental models shape how we respond to AI, and why leaders need to listen before trying to change someone’s mind.
They also explore Brice’s idea that AI could move us from “knowledge workers” to “intelligence workers,” a personal story about his mother using ChatGPT while caring for his father with Alzheimer’s, and why the benefits of AI need to extend beyond the people already living in abundance.
Key Takeaways
Trust in AI has to be earned
As agents take on more responsibility, people need experience with them before they’re willing to hand over judgment and communication.
AI adoption is a mind game and a heart game
Successful change depends not just on what people know about AI, but on what they believe, fear, and care about.
Nine steps can be only halfway there
The final stage of transformation is often where the hardest work begins and assumptions need to be questioned.
We’re moving from knowledge workers to intelligence workers
As AI handles more information processing, human value shifts toward judgment, perspective, influence, and decision-making.
Listen before you think
Changing minds starts with understanding the experiences and mental models behind someone’s point of view, not simply making a better argument.
Brice's LinkedIn:
Website:
What Happens When AI Adoption Actually Works? - with Eric Porres, Chief AI Officer of Logitech
Épisode 78
mercredi 19 août 2026 • Durée 01:05:14
A year ago, Logitech had people experimenting with AI. Today, Eric says he can’t think of a single part of the company that isn’t building, exploring, or creating something with it.
Eric shares what helped make that happen. There’s a Build Advisor that helps employees figure out what to build and connects them with people who may have already worked on something similar. AI in Action moments are now part of company and leadership meetings. And before leadership presents to the board, there’s an expectation that their work goes through an AI Board Advisor first.
Henrik, Jeremy, and Eric also get into what comes next: how to measure whether all this AI activity actually creates value, why Eric built AI systems to manage his own information overload and sleep, and why creating something new should come with another question: what old report, process, or way of working can now disappear?
Key Takeaways
Embed AI into how work gets done
AI becomes more valuable when it’s built into existing workflows and expectations, rather than simply made available for people to use.
Make AI adoption visible and repeatable
Logitech keeps AI present through AI in Action moments, leadership routines, office hours, shared Gems, and a 175-person volunteer Champions Network.
Build resources that help people help themselves
Tools like the Build Advisor give employees a place to start, surface work that already exists, and connect them with colleagues who have tackled similar problems.
Ask what you can stop doing
Eric argues that every new AI-enabled artifact should come with another question: what old report, process, or way of working can now disappear?
Why Companies That Are Great at Innovation Still Fail - with Stanford Professor Charles O'Reilly
Épisode 77
mercredi 5 août 2026 • Durée 43:30
Most companies know how to innovate. Far fewer know how to scale innovation.
Charles introduces the explore versus exploit framework, explaining why the same systems that help organizations succeed today can make them resistant to change tomorrow. As companies mature, they become better at serving existing customers, improving existing products, and optimizing existing processes. The harder question is how to create space for experimentation without undermining the business that already exists.
Henrik, Jeremy, and Charles explore what this means in the age of AI. They discuss whether AI should be viewed as a substitute or a complement, why Microsoft's transformation under Satya Nadella succeeded, how Amazon has built exploration into its operating system, and why leaders don't create adaptable organizations through vision alone. They do it by shaping culture through incentives, systems, and the behaviors they reward.
Key Takeaways:
The biggest challenge isn't generating ideas. It's scaling them.
Many organizations are good at innovation. The difficult part is giving promising ideas the support they need to grow.
Great companies become trapped by what made them successful.
The metrics, incentives, and culture that optimize today's business can make it harder to adapt to tomorrow's.
Culture is built through systems.
Leadership principles only matter when they're reflected in hiring, incentives, performance reviews, and everyday behavior.
The goal isn't to predict the future. It's to discover it.
The most adaptable organizations build processes that help them experiment, learn, and uncover new opportunities as the world changes.
00:00 Intro: Why Companies Die Fast 00:36 Meet Charles O'Reilly Explore Versus Exploit AI Substitute Or Complement Adaptability As Culture Resistance To Change Microsoft Culture Turnaround Ambidexterity And Lifespans Ideate Incubate Scale Scaling Needs Separation Amazon PRFAQ Machine Rituals And Failure Signals The Debrief
What You Can Learn From Asking AI for Brutal Honesty About Yourself - with Bestselling Author Daniel Pink
Épisode 76
mercredi 22 juillet 2026 • Durée 50:50
The conversation begins with an experiment that caught Jeremy's attention. Dan asked ChatGPT to tell him what his friends wouldn't. From questions about his blind spots to what people might say behind his back, some responses felt completely wrong, while others landed with surprising force. Rather than accepting every answer, Dan explains why the real value comes from wrestling with AI's perspective, not simply believing it.
From there, Henrik, Jeremy, and Dan explore what it takes to use AI well. They discuss intellectual humility, prompting models to challenge rather than flatter us, and why AI works best as a sparring partner that exposes weaknesses in our thinking. The conversation also touches on taste, agency, and why, in a world where execution is becoming easier, discernment and original thinking become even more valuable.
Key Takeaways:
Use AI to make your thinking visible
The best AI conversations don't just generate answers. They help you understand your own assumptions, reactions, and ideas more clearly.
Treat AI as a sparring partner
Challenge AI's responses, ask it to critique your work, and use it to strengthen your thinking rather than replace it.
Taste is developed by creating
As AI makes execution easier, judgment and discernment become more valuable. The best way to develop both is by creating, not just consuming.
Agency depends on context
People don't become more agentic through willpower alone. The right environment, with autonomy and room to take risks, makes initiative possible.
00:00 AI as a Brutally Honest Advisor Meet Daniel Pink AI for Self-Knowledge A Brutally Honest AI What Do People Say Behind Your Back? Should You Trust AI's Advice? The Fear of Irrelevance Intellectual Humility AI as a Sparring Partner Teaching AI to Think Like You Why Taste Matters Agency Starts with Context A Future That's a Little Better Nostalgia vs. Reality The Debrief
📜 Read the transcript for this episode:
Are You Qualified to Challenge Your Team on AI? - with Geoff Woods, Author of The AI-Driven Leader
Épisode 75
mercredi 8 juillet 2026 • Durée 53:03
Geoff Woods returns to Beyond the Prompt to discuss the updated edition of The AI-Driven Leader and what has changed over the past 18 months. Rather than focusing on the latest AI models, Geoff argues that leaders need to use AI themselves before asking others to, using it to think more clearly, shape strategy, and make better decisions.
The conversation explores why many organizations confuse access with adoption, why strategy should come before use cases, and how AI can change the way leaders approach everything from business strategy to organizational design. Along the way, Henrik and Jeremy challenge Geoff's ideas on authorship, judgment, and whether understanding AI changes what leaders believe is possible.
Key Takeaways:
Leaders need to use AI themselves
Using AI personally is what qualifies leaders to shape strategy and lead others from practice rather than theory.
Use AI to improve your thinking
The biggest opportunity isn't automating work. It's using AI to think better, solve better problems, and imagine new possibilities.
Start with problems, not use cases
Begin with the biggest challenges facing the business, then use AI to rethink how to solve them.
AI still needs human judgment
AI can generate ideas, but people are still responsible for reviewing the output and standing behind it.
Focus AI on your highest-value work
Use AI to amplify the small set of activities where your human strengths create the greatest impact.
00:00 Are You Qualified to Lead on AI? 00:35 Meet Geoff Woods 00:54 The AI Slop Dilemma 05:48 Putting Your Stamp of Approval What Changed in 18 Months Access Isn't Adoption Why Leaders Can't Delegate AI Strategy Before Use Cases BarkBox's AI Strategy Reinventing Strategy with AI Compressing Months into Hours Human Skills as Superpowers The Debrief
The Unexpected Economics of AGI - with Christian Catalini, Tech Founder and Co-Creator of Libra
Épisode 74
mercredi 24 juin 2026 • Durée 53:34
Christian believes the AI era will be defined less by generating outputs and more by evaluating them. As intelligence becomes cheaper and more accessible, the people who create the most value may be those who can distinguish good work from exceptional work and help guide increasingly capable systems.
The conversation explores verification, judgment, and why expertise still matters in a world where AI can perform many tasks at a high level. Christian explains why today's experts are both highly valuable and simultaneously training the systems that may eventually replace parts of their work.
Jeremy and Henrik also explore what this means at a personal level. They discuss building AI agents that reflect your own preferences, creating personal verification systems, and why AI may make it easier to learn new skills, switch careers, and pursue more ambitious ideas.
Key Takeaways:
Verification becomes more valuable as intelligence gets cheaper
As AI makes generating outputs easier, the ability to recognize what is actually good becomes increasingly important.
Experts are training their own replacements
The people best positioned to verify AI outputs are also helping codify the expertise that trains future systems.
Human value shifts from doing to directing
As AI handles more execution, people create value through judgment, direction, and orchestration.
Build your own verification system
The best AI users are developing agents, workflows, and tools that reflect their own preferences and standards.
Why Fear Kills Curiosity and What That Means for AI - with Chantel Prat, Cognitive Neuroscientist
Épisode 73
mercredi 10 juin 2026 • Durée 01:01:39
Chantel Prat studies how different brains make sense of the world. Her work starts from a simple idea: every experience leaves a mark. The inputs we consume shape how we think, what we notice, and ultimately who we become.
The conversation explores why people often choose familiar rewards over uncertain opportunities to learn. Chantel explains the tension between exploration and exploitation, why curiosity is essential for growth, and how fear can prevent us from engaging with new technologies like AI.
They also discuss theory of mind, cognitive offloading, and what happens when we increasingly rely on AI for thinking. The goal is not simply to do better work, but to use AI in ways that help us become better versions of ourselves.
Key Takeaways:
Curiosity requires safety
When people feel threatened, they become defensive rather than exploratory. Fear gets in the way of learning.
Better inputs create better outputs
Every experience leaves a footprint on the brain. The ideas, conversations, and information we consume shape how we think and who we become.
We naturally favor certainty over exploration
Our brains are biased toward familiar rewards, even when something new may offer greater long-term value.
Curiosity starts with admitting you might be wrong
Learning requires recognizing that you do not already have the answer. Without that openness, exploration never begins.
Use AI to become better, not just produce more
The most important question is not what AI can do for you, but what you still want to get better at yourself.
00:00 Curiosity Versus Threat Meet Chantel Prat Why Input Shapes Brains The Output Pressure Trap Exploration Versus Exploitation Average Brains And Teams Theory Of Mind Defined Practicing With AI Feedback Offloading Thinking To AI Humans In The Loop Age And Tech Reactions Why Curiosity Requires Safety Personal Codex And AI Becoming More Yourself The Debrief
Why Your Favorite Brand Stopped Caring About You - Eric Ries, Author of The Lean Startup
Épisode 72
mercredi 27 mai 2026 • Durée 56:24
Eric Ries, author of The Lean Startup and the newly released Incorruptible, joins Beyond the Prompt to explore why most companies drift from their original mission over time. The conversation dives into governance, shareholder primacy, Anthropic’s unusual structure, and why AI makes these questions more important than ever.
Eric Ries argues that most companies are built on a contradiction. Founders say they care about customers and impact, but legally, the company is structured to serve shareholders first. Over time, that mismatch tends to win.
The conversation explores what that looks like in practice, why it is so hard to fix, and how a small number of companies have tried to design around it from the beginning. Eric reflects on advising Anthropic in its earliest days and what it actually takes to protect a mission as a company scales.
A big part of the discussion is how governance gets treated as a legal formality when it is really a design problem. In the age of AI, Eric argues that the principles baked into a company’s structure early on may determine whether it stays true to its mission or slowly drifts away from it.
Key Takeaways:
Mission drift is often built in from day one
Founders may say they care about customers and impact, but legally the company is structured to serve shareholders first. Over time, that mismatch tends to win.
Governance is one of the highest leverage founder decisions
If the structure is misaligned early on, founders can lose control of the company and its mission no matter how strong the original vision was.
The system is stacked against mission-driven founders
Even well-intentioned founders operate inside structures designed to prioritize short-term shareholder returns. Most do not realize it until it is too late.
“Why not try?” is more powerful than it sounds
Eric’s argument is not that fixing governance is easy. It is that most founders never even ask the question.
AI makes this more urgent than ever
As AI systems act more autonomously, the principles built into a company early on will shape whether it stays true to its mission or drifts away from it.
Delete before you automate
AI needs a better story about what goes right The negative future of AI is easy to picture. Jim argues we need a more tangible vision of how AI can improve people’s lives without losing purpose and human connection.
00:00 Intro: Predictions for the future 00:46 Meet Jim VandeHei 01:06 Becoming an AI Lab Rat 04:21 How Axios Got Everyone Using AI 05:46 Who Gets the Most Out of AI? 08:27 The AI Understanding Gap 11:04 How Jim Keeps Up With AI 14:20 Building Axios for an AI Future 20:47 The CEO’s AI “SEAL Team” 23:52 Writing for Humans and LLMs 26:49 Delete Before You Automate 30:46 The Monthly Mentality 35:58 AI-Assisted Writing and Authenticity 41:47 The Coming Political Backlash 47:42 A Better Story for AI 55:25 The Debrief
00:00 Intro: From Knowledge Worker to Intelligence Worker 00:30 Meet Brice Chalamel 01:18 From Moderna to OpenAI 04:50 The Mission: 1,000 AI Success Stories 07:45 How Work Happens at OpenAI 08:59 When Agents Talk to Agents 10:56 Trust Has to Be Earned 15:22 Brice’s Principles for Change 16:45 Nine Steps Is Halfway There 25:21 The Mind Game 30:24 Why Leaders Resist AI 35:28 The Human Side of AI 37:37 When ChatGPT Became a Lifeline 41:56 From Knowledge Worker to Intelligence Worker 43:37 Agency in the AI Era 46:31 Who Gets to Benefit From AI? 51:39 What Our Fear of AI Reveals 56:18 Listen Before You Think 01:03:07 The Debrief
00:00 Embedding AI Into the Workflow 00:52 Meet Eric Porres 01:15 The Cambrian Explosion of AI 06:20 Measuring the Value of AI 11:16 The Build Advisor 16:12 Keeping Up With AI 19:43 Making AI Part of the Culture 21:37 The AI Board Advisor 25:51 Building an AI Champions Network 29:15 Eric’s Personal AI Stack 32:17 The AI Vampire Problem 40:59 Building a Deep Memory 46:49 What Can AI Help You Delete? 55:19 The Debrief
00:00 Non-Measurable Frontiers 00:32 Meet Christian Catalini 01:08 The Economics of AGI 03:09 Why Verification Matters 06:37 Can Everything Be Measured? 10:32 The Rise of the Verifier 14:35 When Intelligence Gets Cheap 21:46 Building Your Verification Harness 24:08 Human + AI Augmentation 30:18 Persona Files and Privacy 33:12 Reasons for Optimism 36:00 Career Switching in the AI Era 39:31 The Debrief
00:00 Mission vs Shareholder Value 00:32 Meet Eric Ries 01:37 Why Anthropic Needed Governance 06:47 The Long-Term Benefit Trust 10:00 Why Great Companies Drift 13:47 From Lean Startup to Incorruptible 18:14 Is It Too Late To Fix? 23:06 Governance As A Superpower 25:48 The Lies Founders Tell Themselves 28:49 The Rise Of Shareholder Primacy 33:09 The Unaccountability Machine 35:51 Profit vs Human Flourishing 37:24 The ROI Trap 38:26 The H-E-B Loyalty Story 41:14 Principles Beyond Metrics 42:54 AI, Thick Data, And Human Judgment 46:43 The Debrief
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