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By Jeremy Utley & Henrik Werdelin
4.7
5959 ratings
The podcast currently has 74 episodes available.
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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 Advisor 00:32 Meet Daniel Pink 00:47 AI for Self-Knowledge 01:40 A Brutally Honest AI 06:10 What Do People Say Behind Your Back? 07:45 Should You Trust AI's Advice? 13:28 The Fear of Irrelevance 17:44 Intellectual Humility 20:04 AI as a Sparring Partner 24:35 Teaching AI to Think Like You 27:38 Why Taste Matters 29:59 Agency Starts with Context 37:08 A Future That's a Little Better 41:49 Nostalgia vs. Reality 45:18 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/werdelinJeremy: 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 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 📜 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/werdelinJeremy: 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-oreilly 00:00 Intro: Why Companies Die Fast 00:36 Meet Charles O'Reilly 02:01 Explore Versus Exploit 03:50 AI Substitute Or Complement 06:51 Adaptability As Culture 09:19 Resistance To Change 12:32 Microsoft Culture Turnaround 15:25 Ambidexterity And Lifespans 18:20 Ideate Incubate Scale 20:10 Scaling Needs Separation 24:44 Amazon PRFAQ Machine 34:33 Rituals And Failure Signals 38:05 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/werdelinJeremy: 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 Complacency 00:27 Meet Laura Jones 01:23 Brand as trust when products converge 03:50 Personalization and reducing mental load 06:24 What still matters in marketing 10:33 Why need-finding cannot be shortcut 14:09 Using AI without losing judgment 16:33 New channels and where customers actually are 21:35 Why “dopey ideas” matter 25:42 Human plus bot plus human 28:44 Inside the Super Bowl ad 31:47 From banana insight to product 34:49 Taking creative risks at scale 37:34 Fear, pressure, and team chemistry 46:24 AI and faster prototyping 53:26 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/werdelinJeremy: 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 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 📜 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/werdelinJeremy: https://www.linkedin.com/in/jeremyutley Show edited by Emma Cecilie Jensen.
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