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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 experimentPsychological safety gives people room to admit what they don’t know, try something new, and risk looking incompetent.How leaders make people feel mattersHenrik 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 workThe “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…The Practice: bethepractice.comAlex's LinkedIn: LinkedIn/AlexKuilmanImmunity to Change by Robert Kegan & Lisa LaskowAmy Edmondson on Psychological Safety: Psychological Safety 00:00 Intro: The Problem of Corporate Numbing00:23 Meet Alexander Kuilman04:45 Why Aren’t People Using AI More?06:49 The Hidden Assumptions Blocking Change08:08 Jeremy’s Travel Problem14:12 What Are People Really Afraid of With AI?16:02 Stop Making Time to Experiment22:25 Psychological Safety and AI Adoption32:56 How to Hold Yourself38:57 The Leaders Who Make People Feel Safe40:33 What If AI Helps Us Think Less?44:13 The AI Vampire46:10 Corporate Numbing54:08 Your Humanity Is the Advantage58:05 The Debrief 📜 Read the transcript for this episode: Here! For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin: Henrik: https://www.linkedin.com/in/werdelin Jeremy: https://www.linkedin.com/in/jeremyutley Show edited by Emma Cecilie Jensen.

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.Jim's new book: Simplify: Do 50% more with 50% less“Confessions of an AI Lab Rat”: Read here!Axios: Axios.comJim's LinkedIn: LinkedIn.com/JimVandeHeiKey Takeaways Leaders need to become AI lab ratsLeaders 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.Delete before you automateBefore using AI to make existing work faster, ask which meetings, processes, and activities shouldn’t exist at all.AI needs a better story about what goes rightThe 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 future00:46 Meet Jim VandeHei01:06 Becoming an AI Lab Rat04:21 How Axios Got Everyone Using AI05:46 Who Gets the Most Out of AI?08:27 The AI Understanding Gap11:04 How Jim Keeps Up With AI14:20 Building Axios for an AI Future20:47 The CEO’s AI “SEAL Team”23:52 Writing for Humans and LLMs26:49 Delete Before You Automate30:46 The Monthly Mentality35:58 AI-Assisted Writing and Authenticity41:47 The Coming Political Backlash47:42 A Better Story for AI55:25 The Debrief 📜 Read the transcript for this episode: Here! For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin: Henrik: https://www.linkedin.com/in/werdelin Jeremy: https://www.linkedin.com/in/jeremyutley Show edited by Emma Cecilie Jensen.

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: linkedin.com/in/bricechallamel/ Website: powerofwhy.ai 00:00 Intro: From Knowledge Worker to Intelligence Worker00:30 Meet Brice Chalamel01:18 From Moderna to OpenAI04:50 The Mission: 1,000 AI Success Stories07:45 How Work Happens at OpenAI08:59 When Agents Talk to Agents10:56 Trust Has to Be Earned15:22 Brice’s Principles for Change16:45 Nine Steps Is Halfway There25:21 The Mind Game30:24 Why Leaders Resist AI35:28 The Human Side of AI37:37 When ChatGPT Became a Lifeline41:56 From Knowledge Worker to Intelligence Worker43:37 Agency in the AI Era46:31 Who Gets to Benefit From AI?51:39 What Our Fear of AI Reveals56:18 Listen Before You Think01:03:07 The Debrief 📜 Read the transcript for this episode: Here! For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin: Henrik: https://www.linkedin.com/in/werdelin Jeremy: https://www.linkedin.com/in/jeremyutley Show edited by Emma Cecilie Jensen.

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? Eric's website: porres.com/ Eric's LinkedIn: linkedin.com/eporres/ Logitech: www.logitech.com/ 00:00 Embedding AI Into the Workflow00:52 Meet Eric Porres01:15 The Cambrian Explosion of AI06:20 Measuring the Value of AI11:16 The Build Advisor16:12 Keeping Up With AI19:43 Making AI Part of the Culture21:37 The AI Board Advisor25:51 Building an AI Champions Network29:15 Eric’s Personal AI Stack32:17 The AI Vampire Problem40:59 Building a Deep Memory46:49 What Can AI Help You Delete?55:19 The Debrief 📜 Read the transcript for this episode: Here! For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin: Henrik: https://www.linkedin.com/in/werdelin Jeremy: https://www.linkedin.com/in/jeremyutley Show edited by Emma Cecilie Jensen.

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. Charles' Stanford profile: stanford.edu/faculty/charles-oreilly00:00 Intro: Why Companies Die Fast00:36 Meet Charles O'Reilly02:01 Explore Versus Exploit03:50 AI Substitute Or Complement06:51 Adaptability As Culture09:19 Resistance To Change12:32 Microsoft Culture Turnaround15:25 Ambidexterity And Lifespans18:20 Ideate Incubate Scale20:10 Scaling Needs Separation24:44 Amazon PRFAQ Machine34:33 Rituals And Failure Signals38:05 The Debrief 📜 Read the transcript for this episode: here! For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin: Henrik: https://www.linkedin.com/in/werdelin Jeremy: https://www.linkedin.com/in/jeremyutley Show edited by Emma Cecilie Jensen.

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. Daniel's website: danpink.com LinkedIn: linkedin.com/danielpink AI Self-Reflection Prompts: danpink.com/ai-guide/ 00:00 AI as a Brutally Honest Advisor00:32 Meet Daniel Pink00:47 AI for Self-Knowledge01:40 A Brutally Honest AI06:10 What Do People Say Behind Your Back?07:45 Should You Trust AI's Advice?13:28 The Fear of Irrelevance17:44 Intellectual Humility20:04 AI as a Sparring Partner24:35 Teaching AI to Think Like You27:38 Why Taste Matters29:59 Agency Starts with Context37:08 A Future That's a Little Better41:49 Nostalgia vs. Reality45:18 The Debrief 📜 Read the transcript for this episode: Here! For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin: Henrik: https://www.linkedin.com/in/werdelin Jeremy: https://www.linkedin.com/in/jeremyutley Show edited by Emma Cecilie Jensen.

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. The AI-Driven Leader: aileadership.com Geoff's LinkedIn: linkedin/geoff-woods00:00 Are You Qualified to Lead on AI?00:35 Meet Geoff Woods00:54 The AI Slop Dilemma05:48 Putting Your Stamp of Approval09:19 What Changed in 18 Months12:13 Access Isn't Adoption15:50 Why Leaders Can't Delegate AI20:09 Strategy Before Use Cases22:02 BarkBox's AI Strategy26:23 Reinventing Strategy with AI33:11 Compressing Months into Hours37:22 Human Skills as Superpowers42:46 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/transcript For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin: Henrik: https://www.linkedin.com/in/werdelin Jeremy: https://www.linkedin.com/in/jeremyutley Show edited by Emma Cecilie Jensen.

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. Christian's LinkedIn: linkedin.com/ccatalini/ Christian's X: x.com/ccatalini Christian's website: catalini.com Economics of AGI: full paper Jeremy's Persona File Template: YouTube/The8Files 00:00 Non-Measurable Frontiers00:32 Meet Christian Catalini01:08 The Economics of AGI03:09 Why Verification Matters06:37 Can Everything Be Measured?10:32 The Rise of the Verifier14:35 When Intelligence Gets Cheap21:46 Building Your Verification Harness24:08 Human + AI Augmentation30:18 Persona Files and Privacy33:12 Reasons for Optimism36:00 Career Switching in the AI Era39:31 The Debrief 📜 Read the transcript for this episode: the-unexpected-economics-of-agi-with-christian-catalini-tech-founder-and-co-creator-of-libra/transcript For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin: Henrik: https://www.linkedin.com/in/werdelin Jeremy: https://www.linkedin.com/in/jeremyutley Show edited by Emma Cecilie Jensen.

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. Chantel Prat: linktr.ee/chantelprat The Neuroscience of You: The-Neuroscience-of-you/book 00:00 Curiosity Versus Threat00:31 Meet Chantel Prat01:02 Why Input Shapes Brains04:08 The Output Pressure Trap05:52 Exploration Versus Exploitation10:05 Average Brains And Teams15:35 Theory Of Mind Defined22:12 Practicing With AI Feedback24:31 Offloading Thinking To AI29:50 Humans In The Loop35:16 Age And Tech Reactions42:15 Why Curiosity Requires Safety48:15 Personal Codex And AI50:54 Becoming More Yourself54:34 The Debrief 📜 Read the transcript for this episode: why-fear-kills-curiosity-and-what-that-means-for-ai-with-chantel-prat-cognitive-neuroscientist/transcript For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin: Henrik: https://www.linkedin.com/in/werdelin Jeremy: https://www.linkedin.com/in/jeremyutley Show edited by Emma Cecilie Jensen.

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.   Eric's new book: Amazon: Incorruptible Website: incorruptible.coSocials: X: x.com/ericries LinkedIn: linkedin.com/ericries The Lean Startup: theleanstartup.com 00:00 Mission vs Shareholder Value00:32 Meet Eric Ries01:37 Why Anthropic Needed Governance06:47 The Long-Term Benefit Trust10:00 Why Great Companies Drift13:47 From Lean Startup to Incorruptible18:14 Is It Too Late To Fix?23:06 Governance As A Superpower25:48 The Lies Founders Tell Themselves28:49 The Rise Of Shareholder Primacy33:09 The Unaccountability Machine35:51 Profit vs Human Flourishing37:24 The ROI Trap38:26 The H-E-B Loyalty Story41:14 Principles Beyond Metrics42:54 AI, Thick Data, And Human Judgment46:43 The Debrief  📜 Read the transcript for this episode: why-your-favorite-brand-stopped-caring-about-you-eric-ries-author-of-the-lean-startup/transcript For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin: Henrik: https://www.linkedin.com/in/werdelin Jeremy: https://www.linkedin.com/in/jeremyutley Show edited by Emma Cecilie Jensen.

Ryan Holiday argues that while AI can generate outputs, it cannot generate wisdom. Drawing on a story from Seneca about a Roman who used educated slaves to sound intelligent, he compares outsourcing thinking to outsourcing exercise: the value comes from becoming the kind of person who can do the work, not simply producing the answer. The conversation explores the difference between useful cognitive offloading and surrendering judgment entirely. Ryan explains that while tools like GPS may replace navigation skills without much consequence, writing, decision-making, and critical thinking shape the person on the other side of the process. AI, he argues, tends to amplify existing tendencies. People satisfied with mediocre work will settle faster, while people pushing for exceptional work can use AI to refine and challenge their thinking. Throughout the episode, Stoicism serves as a counterweight to both panic and hype. Change and uncertainty are constants throughout history, not exceptions. Ryan reflects on leadership, family, adaptability, and skepticism, arguing that in a world where AI can confidently produce both insight and nonsense, the ability to question, verify, and think independently becomes increasingly valuable.Key Takeaways:  You cannot outsource wisdom AI can generate answers, but judgment and understanding still come from doing the work yourself. AI amplifies who you already are People who settle for mediocre work will do so faster with AI. People who push for better work can use it to deepen and refine their thinking. B******t detection is becoming a core skill As AI produces increasingly convincing answers, skepticism and verification become essential. Change is not new The Stoics viewed uncertainty and disruption as constants of human life. AI may feel unprecedented, but humans have always had to adapt to major change. Agency matters more than ever You cannot control technological change, but you can control how you respond to it and how you choose to use it.   Ryan's website: ryanholiday.net Daily Stoic: dailystoic.com/podcast/ 00:00 Intro: You Can’t Outsource Wisdom00:29 Meet Ryan Holiday02:03 The Dream Was To Work Less03:07 Who Actually Gets The Time?06:32 Leadership, Culture, And Family First08:38 How Will You Measure Your Life?10:11 The Stoic View Of Change14:44 AI Hallucinations And Shameless Confidence17:21 You Cannot Outsource Wisdom19:08 Cognitive Offloading Vs Real Understanding20:22 Ego, Flattery, And AI22:52 AI As Editor And Thought Partner24:59 Mediocre Vs Exceptional Work31:15 Why B******t Detection Matters38:06 Stoicism, Agency, And Adapting To Change43:31 The Debrief 📜 Read the transcript for this episode: you-cant-outsource-wisdom-bestselling-author-ryan-holiday-on-what-the-stoics-have-to-say-about-ai/transcript For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin: Henrik: https://www.linkedin.com/in/werdelin Jeremy: https://www.linkedin.com/in/jeremyutley Show edited by Emma Cecilie Jensen.

Laura Jones explains that generative AI is raising the bar for creativity. When everyone can produce “pretty good” content, the real challenge is creating something that actually stands out. The risk is not poor output, but settling too quickly for what already works. She argues that as products become more similar, brand becomes a signal of trust. Not in a visual sense, but in the experience behind it. At Instacart, that shows up in details like how a banana is selected. With over a billion bananas delivered and millions of orders including notes on ripeness, customers are expressing very specific preferences. That behavior led to both new product features and the creative idea behind their Super Bowl campaign. The conversation also explores how teams should work with AI. While it can automate repetitive tasks and speed up iteration, it can also create a tendency to agree with what’s generated, especially when working alone. Laura emphasizes that the best ideas still come from people challenging each other, building on different perspectives, and pushing beyond the first acceptable answer.Key takeaways:  Mediocre is easier than ever, which raises the bar for originality When AI gets everyone to “pretty good,” the work that stands out has to go further. The bar is not lower. It is higher. Brand becomes trust when products converge As functionality becomes easier to replicate, the question becomes who you trust to get it right. Brand is the answer to that. Only do what only you can do Use AI to take on repetitive work, then spend your time on judgment, insight, and decisions that require a human point of view. Need-finding still requires real people Synthetic research can help, but it cannot replace observing real behavior. The banana insight came from what customers actually did. Human plus bot plus human Working only with AI makes it easy to agree and move on. The best ideas come from people challenging each other, with AI in the middle, not as the whole process. Instacart: instacart.com Super Bowl ad: Super Bowl (Instacart ad) Laura LinkedIn: linkedin/laurajones ro's post: ro.co/perspectives/super-bowl-economics   00:00 Intro: Originality vs AI Complacency00:27 Meet Laura Jones01:23 Brand as trust when products converge03:50 Personalization and reducing mental load06:24 What still matters in marketing10:33 Why need-finding cannot be shortcut14:09 Using AI without losing judgment16:33 New channels and where customers actually are21:35 Why “dopey ideas” matter25:42 Human plus bot plus human28:44 Inside the Super Bowl ad31:47 From banana insight to product34:49 Taking creative risks at scale37:34 Fear, pressure, and team chemistry46:24 AI and faster prototyping53:26 The debrief 📜 Read the transcript for this episode proof-of-craft-what-it-takes-to-stand-out-when-everything-looks-good-with-laura-jones-cmo-of-instacart/transcript For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin: Henrik: https://www.linkedin.com/in/werdelin Jeremy: https://www.linkedin.com/in/jeremyutley Show edited by Emma Cecilie Jensen.

Dan Klein, professor at UC Berkeley and CTO at Scaled Cognition, explains that AI systems generate answers based on patterns in language rather than verified knowledge. This makes them highly capable across many tasks, but also means they can produce confident answers even when they are not fully accurate. He introduces the “jagged frontier,” where AI performs very well in some areas and less reliably in others. Because responses are fluent and convincing, it is often hard to see where those limits are, which makes it important to stay engaged when using these systems. The conversation also explores hallucinations as a natural part of generative systems. In some cases, this is what makes them valuable, especially for creative or open-ended tasks, while in other cases reliability becomes more important. Finally, Dan highlights that working effectively with AI is a skill. As more people start using these systems in their daily work, knowing how to guide them, evaluate outputs, and apply them in the right contexts becomes increasingly important. He also shares how his team at Scaled Cognition is tackling this challenge by building AI systems with fundamentally different architectures, focused on determinism and reliability — aiming to ensure systems follow rules, reflect underlying data accurately, and behave predictably in high-stakes, policy-driven use cases. Key Takeaways: AI is designed to sound right, not to know it’s right Models generate fluent answers without knowing whether they are correct, which means users need to actively evaluate outputs You have to learn where AI works and where it doesn’t Capabilities are uneven, and understanding those limits is key to using AI effectively Working with AI shifts your role from creator to editor Instead of starting from scratch, you are reviewing, refining, and validating what the model produces Most people are using AI without knowing how to manage it Skills like delegation, verification, and judgment are becoming essential, but are not widely taught Dan's LinkedIn: linkedin/dan-klein/ Scaled Cognition Website: scaledcognition.com Scaled Cognition LinkedIn: linkedin/company/scaledcognition/ Scaled Cognition X: x.com/ScaledCognition 00:00 Intro: Fluency vs Truth00:34 Meet Dan Klein02:53 Why Fluency Misleads05:11 How LLMs Guess07:30 What Is Hallucination08:54 Deception and Alignment11:22 Why Agents Break12:48 Chaining and Determinism16:01 When Hallucination Helps22:33 Beyond Scale for Reliability30:40 Synthetic Data Training31:10 Enterprise Agent Use Cases33:44 Healthcare Risks39:13 Enterprise Literacy Gap41:27 Delegation and AI Management54:37 The Debrief 📜 Read the transcript for this episode: nobody-is-getting-new-manager-training-for-their-ai-team-with-dan-klein-uc-berkeley/transcript For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin: Henrik: https://www.linkedin.com/in/werdelin Jeremy: https://www.linkedin.com/in/jeremyutley Show edited by Emma Cecilie Jensen.

Melissa Cheals leads Smartly, a payroll and people management platform serving 24,000 small and medium businesses in New Zealand. In this conversation, she shares how AI is reshaping product development, leadership, and how organizations operate. A key moment comes when her team estimates new features will take 12 months and $1M to build. Instead of accepting it, Melissa pushes back, using AI to better understand her team’s perspective and communicate the need for change more effectively. This becomes a broader shift in how she approaches leadership, using AI to think more clearly and navigate conversations with less friction. The discussion expands into strategy. Companies now face a fundamental choice: become AI-native or continue building on existing systems. As AI adoption increases, it also exposes silos and bottlenecks. Melissa shares why cross-functional collaboration—and leaders actively engaging with AI themselves—is critical to navigating this shift. Key Takeaways:  Becoming AI-native is a defining decision It’s not just a technology shift. Leaders need to decide whether to rebuild around AI or continue layering it onto existing systems, and that choice shapes how the company operates. AI shifts us from scarcity to abundance Many organizations still think in terms of limited time and resources, but AI changes what’s possible and forces leaders to rethink how big they can think and what they can achieve. AI is a leadership amplifier Beyond productivity, AI helps leaders think more clearly, reframe conversations, and communicate change in a way that is both effective and respectful. Leaders can’t delegate AI Without hands-on experience, it becomes difficult to challenge assumptions, guide teams, or make informed decisions about what’s possible. Smartly: smartly.co.nz LinkedIn Melissa: linkedin.com/melissa-cheals LinkedIn Smartly: linkedin.com/company/smartlynz/ 00:00 Intro: Challenging AI Assumptions00:28 Meet Melissa Cheals01:17 The Spark For Change02:36 Vision And Early Signals03:48 Hiring For Transformation06:12 Unlocking Data With AI08:27 Breaking Silos Across Teams10:39 Why Leaders Must Learn AI13:42 Leading With AI And Clarity17:05 The AI-Native Decision21:45 Thinking Bigger With AI25:23 Less Meetings More Writing26:33 The Self-Disruption Imperative29:11 Breaking Silos With Value Streams31:28 Managing Fear And Change32:50 Learning And Shipping Faster34:58 Debrief 📜 Read the transcript for this episode: ai-native-or-not-the-defining-choice-for-companies-right-now-with-melissa-cheals-ceo-of-smartly/transcript For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin: Henrik: https://www.linkedin.com/in/werdelin Jeremy: https://www.linkedin.com/in/jeremyutley Show edited by Emma Cecilie Jensen.

Greg Shove describes a growing gap between individual and organizational AI adoption. A small group of employees are already using AI effectively, while most companies are still early. AI is generating real productivity gains, but those gains are not being captured at the company level. Instead, they are absorbed by individuals who use AI to work faster, often without changing team outputs or structures — raising a central question: if AI creates time, where does that time go? The conversation explores why enterprise AI adoption remains uneven. Many organizations lack a clear point of view on AI, and workflows take time to adapt, making it difficult to turn individual gains into coordinated results. At the same time, AI is breaking capability boundaries, allowing people to take on work across roles while companies remain structured around existing ways of operating. From a leadership perspective, Greg emphasizes that the challenge is not just efficiency. AI creates capacity, but without clear direction on how to use it, that capacity disappears. Leaders must decide how to reinvest the time AI creates if they want to capture real business value.Key Takeaways:  AI’s ROI is leaking, not missing Companies are generating value from AI, but it’s being captured by employees rather than the organization. A small group drives most of the impact Roughly 10–15% of employees adopt AI early and use it effectively, creating an uneven distribution of gains. AI is breaking capability boundaries Individuals can now take on work across roles, but organizations are still structured around fixed responsibilities. Most companies lack a clear point of view on AI Without direction from leadership, adoption becomes fragmented and employees are left to figure it out themselves. Leaders must decide what to do with the time AI creates Efficiency gains alone don’t create value. Organizations need to define new, higher-value work or the gains disappear. Greg's LinkedIn: linkedin/gregshove Section LinkedIn: linkedin/company/sectionai Section AI: sectionai.com Prof AI: prof.ai 00:00 Intro: Entering the Era of AI Chaos00:31 Meet Greg Shove01:32 Enterprise AI Is a C Minus01:51 AI’s ROI Is “Leaking” to Employees03:04 When Individuals Outrun the Organization05:44 When AI Breaks Workflows06:47 Disposable Software and New Ways of Building09:10 Cut vs Create12:01 Using the Calendar as a Lever16:24 Why Enterprises Don’t Move17:32 When Customers Force Change21:31 AI Breaks Capability Boundaries25:44 The Productivity Firehose27:49 Who Actually Captures the Value28:45 Why Everyone Needs Good AI32:00 Adoption Beats Buying More Tools40:17 Teaching the 90 Percent43:48 Where Humans Still Matter48:09 The Debrief 📜 Read the transcript for this episode: greg-shove-on-why-most-companies-are-not-seeing-roi-on-ai-yet/transcript For more prompts, tips, and AI tools. Check out our website: https://www.beyondtheprompt.ai/ or follow Jeremy or Henrik on Linkedin: Henrik: https://www.linkedin.com/in/werdelin Jeremy: https://www.linkedin.com/in/jeremyutley Show edited by Emma Cecilie Jensen.