Explore every episode of the podcast Beyond The Prompt - How to use AI in your company
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Whatever You Might Think About AI, You Must Feel Awe: Pulitzer Finalist Robert Wright on “The God Test”
11 Nov 2026
00:51:31
Robert Wright believes that whether you're excited about AI or terrified of it, you should be feeling some awe. He sees AI as a turning point in the history of life on Earth and explores the possibility of a “global brain” that could become far more intelligent than us. But if we build something that powerful, how do we make sure it works in humanity's favor?
Robert explains why managing AI may require international cooperation, and why our own tribal instincts could get in the way. Henrik and Jeremy also explore what happens if things go right, from breakthroughs in science to a world where people might no longer need to work. But what would life actually look like in that future?
The conversation turns to the AI companions we choose, and why having one that tells us the truth might matter more than having one that agrees with us. Afterward, Henrik and Jeremy wonder whether AI could help us reconnect with the physical world, and why having more free time doesn't necessarily mean we'll use it well.
Key Takeaways:
AI deserves our awe, whether we're excited or afraid. Robert Wright explains why AI could mark a turning point in the history of life on Earth.
Managing AI requires more than better technology. Robert argues that global cooperation is essential, but human tribalism could stand in the way.
Choose an AI that tells you the truth. Robert warns against AI companions that simply agree with us, and encourages people to actually try the technology.
More free time doesn't guarantee a better life. Henrik and Jeremy explore whether AI could help us reconnect with the physical world, and why being present still takes effort.
00:00 Intro: Could AI Become a God? 00:40 Meet Robert Wright 01:16 Why AI Deserves Our Awe 03:02 Are We Underestimating AI? 05:44 The Everyday Miracles of AI 07:07 How AI Learns Without Understanding the Brain 09:20 AI and the History of Life on Earth 13:13 Are Humans Really Less Flawed Than AI? 16:41 What Is the God Test? 18:12 Why AI Needs Global Cooperation 21:36 What Would AI Heaven Look Like? 25:12 Would Life Without Work Be Fulfilling? 28:55 Why the Future Is Hard to Imagine 32:48 AI Alignment vs. What the Market Wants 35:07 Choosing an AI That Tells You the Truth 37:52 Why You Should Actually Try AI 41:47 The Debrief
Henrik will be interviewing Jeremy about his new book, The Human Advantage: What AI Can't Do Without You, followed by a 45-minute AMA. Got questions about AI, entrepreneurship, writing, or anything we've talked about on the pod? Come join us!
Here's how to join: Pre-order Jeremy's book and send your receipt to preorders@jeremyutley.com to get your Zoom access code.
What Happens When the Jobs Stay but the Work Changes? Refounding Zapier with CEO Wade Foster
28 Oct 2026
00:54:40
After 15 years of building Zapier, Wade Foster is inviting his team to rethink almost everything. What started as a “code red” response to AI has become an opportunity to rediscover what the company could be. Wade describes the feeling as “10 out of 10 anxiety, but 10 out of 10 fun.” The challenge is getting an entire organization to see the possibilities, especially when change can feel threatening.
Wade shares what this looks like inside Zapier, including an experiment to let AI agents handle customer support emails. It turns out that handing work over to AI is much harder than simply adding an assistant to an existing process. The team has spent months figuring out how to make it work, with humans still playing an important role.
Henrik, Jeremy, and Wade also explore what it takes to thrive when the old rules no longer apply. They discuss curiosity, resourcefulness, and the instinct to act instead of waiting for instructions. And while Wade is giving his team permission to question everything, the conversation raises a harder question: how do you get people to challenge the way things have always been done when that's exactly what they've been taught to follow?
Key Takeaways
The work is changing, even when the jobs aren't disappearing. Henrik and Jeremy reflect on Wade's point that AI doesn't necessarily make a role obsolete, but it can fundamentally change what people do in that role.
Resourcefulness is becoming a superpower. Henrik and Jeremy discuss why curiosity, adaptability, and the willingness to act without all the answers are increasingly valuable. Sometimes the most important step is realizing you can just build something.
Question everything, but bring a better idea. Henrik points out that challenging the way things have always been done is only useful if you're willing to suggest or try something different.
You can't refound a company by announcement alone. Jeremy wonders how leaders can make questioning old assumptions part of everyday work. He and Henrik explore why established habits, defaults, and organizational structures can be harder to change than the rules themselves.
00:00 Intro: The Work Is Changing 00:48 Meet Wade Foster 04:49 Is Your Strategy Too Small for AI? 06:14 From Code Red to Refounding Zapier 07:31 10/10 Anxiety, 10/10 Fun 08:50 How Much Has AI Actually Changed? 10:41 Getting People Excited About AI 13:56 Why Jobs Are Changing 15:34 Rethinking How Work Gets Done 16:39 Inside Zapier's AI Support Experiment 20:14 When Existing Workflows Break 21:45 Identity, Curiosity, and Adaptability 25:36 The Instinct to Act Without All the Answers 29:39 Stop Waiting for an Assignment 33:28 You Can Just Build Something 34:43 What Does Refounding Actually Mean? 36:40 Giving People Direction Without All the Rules 38:36 The Future of Automation at Zapier 39:18 Wade's Advice for Refounding a Company 41:45 What Would a New CEO Do? 43:23 The Debrief
Do You Know Yourself Well Enough to Let AI Make Decisions for You? - with Nicholas Skytland Former NASA chief technologist
14 Oct 2026
01:07:49
Nicholas Skytland spent 25 years at NASA, where he helped bring people from around the world together through hackathons. He joins Henrik and Jeremy to share what makes hackathons work, why different perspectives matter, and how to help people through the moment they want to give up.
Nick is now bringing that approach to kids. When his wife wanted to run an AI hackathon at her school, restrictions on AI tools led Nick and his team to build Launch.Kids. At one event, 36 teams created 500 applications in a single day.
Try Launch.Kids: If you're a student, parent, or teacher interested in learning how to build with AI, we'd love for you to try out Launch.Kids, mentioned on the show. The first 100 listeners can sign up at https://launch.kids/welcome/beyondtheprompt for a free month of credit.
The conversation then turns to a bigger question: how well do we really know our own values? Nick, Henrik and Jeremy explore how to communicate what matters to us when working with AI, and why we shouldn't hand over our judgment just because technology makes it easy.
Key Takeaways
Hackathons are an underused tool Henrik and Jeremy reflect on how hackathons bring different people together, encourage experimentation, and create value even when they don't lead to a finished product.
Expect the moment of despair Getting stuck is part of building something new. Nick explains why good hackathons need mentors, encouragement, and a bit of fun to help people push through it.
The better you know yourself, the better you can use AI Henrik and Jeremy discuss why understanding your own values, preferences, and ways of thinking helps you give AI better direction and recognize when its answers don't fit.
Don't let AI do all the thinking for you AI can make decisions easier, but that doesn't mean we should stop questioning its answers. Henrik and Jeremy reflect on the importance of bringing our own judgment to the conversation, especially when we're dealing with something we don't know much about.
00:00 Intro: Don't Outsource Your Judgment to AI 00:20 Meet Nicholas Skytland 00:46 How NASA Opened Up Innovation 03:45 Measuring the ROI of Hackathons 05:04 Getting Past the Barriers to Open Innovation 07:51 Bringing Hackathons to Kids 09:19 Building Launch.Kids 14:44 Why “Just Play With AI” Isn't Enough 18:19 The Moment of Despair 21:36 How to Run a Hackathon 23:39 The Process, Not the Product 25:56 Inside Anthropic's Gathering of Faith Leaders 31:33 Be an Active Shaper of AI 34:36 Can AI learn good judgement? 39:00 Who Gets to Decide What's Good? 42:40 Communicating Your Values to AI 44:25 Don't Outsource Your Judgment 46:42 Henrik's Personal AI Playbook 51:10 The Debrief
What Will You Do With the Time AI Gives Back to You? - with Alex Kuilman, Founder of The Practice
30 Sep 2026
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
16 Sep 2026
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.
Delete before you automate Before 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 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
From Knowledge Worker to Intelligence Worker: Why Human Judgment Matters More With AI - with OpenAI’s Brice Challamel
02 Sep 2026
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.
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
What Happens When AI Adoption Actually Works? - with Eric Porres, Chief AI Officer of Logitech
19 Aug 2026
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?
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
Why Companies That Are Great at Innovation Still Fail - with Stanford Professor Charles O'Reilly
05 Aug 2026
00:43:30
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 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
What You Can Learn From Asking AI for Brutal Honesty About Yourself - with Bestselling Author Daniel Pink
22 Jul 2026
00:50:50
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 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
Are You Qualified to Challenge Your Team on AI? - with Geoff Woods, Author of The AI-Driven Leader
08 Jul 2026
00:53:03
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 09:19 What Changed in 18 Months 12:13 Access Isn't Adoption 15:50 Why Leaders Can't Delegate AI 20:09 Strategy Before Use Cases 22:02 BarkBox's AI Strategy 26:23 Reinventing Strategy with AI 33:11 Compressing Months into Hours 37:22 Human Skills as Superpowers 42:46 The Debrief
The Unexpected Economics of AGI - with Christian Catalini, Tech Founder and Co-Creator of Libra
24 Jun 2026
00:53:34
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.
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
Why Fear Kills Curiosity and What That Means for AI - with Chantel Prat, Cognitive Neuroscientist
10 Jun 2026
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 00:31 Meet Chantel Prat 01:02 Why Input Shapes Brains 04:08 The Output Pressure Trap 05:52 Exploration Versus Exploitation 10:05 Average Brains And Teams 15:35 Theory Of Mind Defined 22:12 Practicing With AI Feedback 24:31 Offloading Thinking To AI 29:50 Humans In The Loop 35:16 Age And Tech Reactions 42:15 Why Curiosity Requires Safety 48:15 Personal Codex And AI 50:54 Becoming More Yourself 54:34 The Debrief
Why Your Favorite Brand Stopped Caring About You - Eric Ries, Author of The Lean Startup
27 May 2026
00:56:24
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.
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
You Can't Outsource Wisdom: Bestselling Author Ryan Holiday on What the Stoics Have to Say About AI
13 May 2026
00:54:59
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.
Bullshit 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.
00:00 Intro: You Can’t Outsource Wisdom 00:29 Meet Ryan Holiday 02:03 The Dream Was To Work Less 03:07 Who Actually Gets The Time? 06:32 Leadership, Culture, And Family First 08:38 How Will You Measure Your Life? 10:11 The Stoic View Of Change 14:44 AI Hallucinations And Shameless Confidence 17:21 You Cannot Outsource Wisdom 19:08 Cognitive Offloading Vs Real Understanding 20:22 Ego, Flattery, And AI 22:52 AI As Editor And Thought Partner 24:59 Mediocre Vs Exceptional Work 31:15 Why Bullshit Detection Matters 38:06 Stoicism, Agency, And Adapting To Change 43:31 The Debrief
Proof of Craft: What It Takes to Stand Out When Everything Looks Good - with Laura Jones, CMO of Instacart
29 Apr 2026
01:06:49
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.
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
Nobody Is Getting New Manager Training for Their AI Team - with Dan Klein, UC Berkeley
15 Apr 2026
01:03:19
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
00:00 Intro: Fluency vs Truth 00:34 Meet Dan Klein 02:53 Why Fluency Misleads 05:11 How LLMs Guess 07:30 What Is Hallucination 08:54 Deception and Alignment 11:22 Why Agents Break 12:48 Chaining and Determinism 16:01 When Hallucination Helps 22:33 Beyond Scale for Reliability 30:40 Synthetic Data Training 31:10 Enterprise Agent Use Cases 33:44 Healthcare Risks 39:13 Enterprise Literacy Gap 41:27 Delegation and AI Management 54:37 The Debrief
AI-Native or Not: The Defining Choice for Companies Right Now - with Melissa Cheals, CEO of Smartly
01 Apr 2026
00:49:43
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.
00:00 Intro: Challenging AI Assumptions 00:28 Meet Melissa Cheals 01:17 The Spark For Change 02:36 Vision And Early Signals 03:48 Hiring For Transformation 06:12 Unlocking Data With AI 08:27 Breaking Silos Across Teams 10:39 Why Leaders Must Learn AI 13:42 Leading With AI And Clarity 17:05 The AI-Native Decision 21:45 Thinking Bigger With AI 25:23 Less Meetings More Writing 26:33 The Self-Disruption Imperative 29:11 Breaking Silos With Value Streams 31:28 Managing Fear And Change 32:50 Learning And Shipping Faster 34:58 Debrief
Greg Shove on Why Most Companies Are Not Seeing ROI On AI (yet)
18 Mar 2026
00:59:14
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.
00:00 Intro: Entering the Era of AI Chaos 00:31 Meet Greg Shove 01:32 Enterprise AI Is a C Minus 01:51 AI’s ROI Is “Leaking” to Employees 03:04 When Individuals Outrun the Organization 05:44 When AI Breaks Workflows 06:47 Disposable Software and New Ways of Building 09:10 Cut vs Create 12:01 Using the Calendar as a Lever 16:24 Why Enterprises Don’t Move 17:32 When Customers Force Change 21:31 AI Breaks Capability Boundaries 25:44 The Productivity Firehose 27:49 Who Actually Captures the Value 28:45 Why Everyone Needs Good AI 32:00 Adoption Beats Buying More Tools 40:17 Teaching the 90 Percent 43:48 Where Humans Still Matter 48:09 The Debrief
How to Subtract: The Most Underrated Skill of the AI Era - with Leidy Klotz
04 Mar 2026
00:58:45
Leidy Klotz has spent years studying a simple but overlooked phenomenon: when we try to improve something, our first instinct is to add rather than remove. He shares the Lego bridge experiment that sparked his research and explains how this additive bias scales from small design decisions to entire organizations. Over time, companies accumulate reporting lines, meetings, software, and policies without questioning what no longer serves them.
Henrik and Jeremy explore how AI tools intensify this pattern. When generating ideas, launching projects, writing code, or producing content becomes effortless, the temptation to add grows stronger. The cost of producing information drops, but the cost of consuming it rises. Without guardrails, organizations risk what Leidy calls “organizational indigestion.”
The discussion moves from insight to implementation. Leidy outlines practical ways to counteract additive bias, including stop-doing lists, default kill dates on projects, and designing environments that make subtraction visible and acceptable. In a world of accelerating AI output, leaders must intentionally decide what to remove, what to protect, and what truly matters.
Key Takeaways:
We default to adding, not subtracting
When faced with a problem, our instinct is to introduce something new. Subtraction rarely occurs to us, even when removing something would improve clarity and performance.
Generative AI amplifies additive bias
AI makes producing content, code, and ideas easier than ever. Without constraints, this frictionless creation can accelerate complexity instead of progress.
More organizations die from indigestion than starvation
Over time, companies accumulate tools, processes, and policies that quietly slow them down. The real risk is often not too few ideas, but too many unexamined additions.
Architecture beats willpower
Rather than relying on discipline alone, leaders can design systems that encourage subtraction. Stop-doing lists and default expiration dates make removal expected instead of exceptional.
Protect what matters before adding more
Before introducing new tools, workflows, or AI systems, leaders must define what is already working and worth protecting. Subtraction requires clarity about what should stay, not just what should go.
00:00 Intro: Our Instinct to Add 00:28 Meet Leidy Klotz 01:15 The Subtract Idea 02:56 Organizations Get Bloated 03:49 Scandinavian Design Mindset 04:32 New Book: In a Good Place 05:59 AI Abundance and Indigestion 08:12 Curate Context, Not More 11:38 Cues and Stop-Doing Lists 15:00 Default Debt and Kill Dates 17:10 Odysseus Contracts and Biases 21:28 Reengage the Physical World 29:17 Bike Shedding and Priorities 36:10 Making Is Thinking 49:16 The Debrief
From Roadmaps to R&D: How AI Is Changing Product Development - with Richard White, Founder of Fathom AI
18 Feb 2026
00:56:58
Fathom was built on the assumption that transcription would become commoditized and generative models would steadily improve. Rather than training proprietary models, Richard focused on building the infrastructure around them and waiting for model capabilities to reach the right threshold.
In this conversation, he explains why AI has made effort and impact harder to predict, and why that shifts product development from roadmap execution toward experimentation. He describes separating an exploratory AI team from core engineering, structuring that team to prototype and write specs, and expecting a meaningful portion of experiments not to work. Richard introduces his Jenga model for AI development, testing different models and use cases to find where resistance is lowest. He also discusses the operational realities of rapid model updates, hallucination rates, and what he calls the LLM treadmill.
The discussion explores qualitative QA, organizational design, buy versus build decisions, and why leadership taste plays an increasingly important role as AI lowers the barrier to generating outputs.
Key takeaways:
Estimating effort and impact is becoming harder As model capabilities improve quickly, features that require months today may take far less time in the near future. This makes traditional planning assumptions less stable.
Product development increasingly resembles R&D With shifting capabilities and uncertain outcomes, teams must experiment, prototype, and iterate rather than rely solely on long term roadmaps.
Organizational structure must reflect experimentation Separating exploratory AI work from core engineering can allow faster iteration while maintaining stability elsewhere.
Rapid model updates create operational pressure Frequent improvements and changing performance levels can require teams to revisit and adjust features more often than in traditional software cycles.
Qualitative judgment plays a larger role As AI lowers the cost of generating outputs, evaluating quality and deciding what to ship becomes increasingly important.
00:00 Intro: Why AI Breaks Roadmaps 00:19 Meet Richard White (Fathom AI) 02:16 From Roadmaps to R&D 04:49 Designing AI Teams for Speed 07:11 The Jenga Model 09:56 Failing 50% & AI Team Psychology 13:40 LLMs as Interns & Anti-Planning 21:01 QA, Data Pain & Developing Taste 24:59 Executive Taste & Culture Rules 27:20 Reacting to AI Waves 28:50 Fathom’s 4-Step Product Plan 30:47 What New Models Unlock 32:13 From Scribe to Second Brain 40:32 Build vs Buy in AI 45:32 The Debrief
Here’s How to Know If You’re Getting the Most Out of AI – with Bryan McCann, CTO of You.com
04 Feb 2026
00:59:50
In this episode, Bryan McCann joins Henrik and Jeremy to explore how search is evolving from simple queries into more conversational and agent-driven systems, and why prompting is likely a temporary skill. Bryan shares how his definition of productivity changed as an AI researcher, moving away from doing the work himself and toward designing plans and experiments that machines could run continuously.
The conversation expands to leadership and organizational design. Bryan explains why helping others learn how to work with AI became his highest-leverage activity, and offers a simple rule of thumb: try to get AI to do the task first, and treat anything it can’t do as an interesting research problem. Henrik and Jeremy connect this to Bryan’s view that organizations may increasingly resemble neural networks, with information flowing more freely and decisions less tied to rigid hierarchies.
Key Takeaways:
Productivity can be measured by machine output, not human effort Bryan explains how “keeping the GPUs full” became his primary measure of productivity.
Prompting is useful, but likely temporary The episode discusses why future systems may rely less on explicit prompts and more on inferred context.
Try AI first, then learn from what it can’t do Tasks AI struggles with can reveal meaningful research opportunities.
Leadership is about scaling others Bryan shares how his focus shifted from scaling himself to helping his team increase impact.
Organizations may benefit from neural-network-like design Better information flow and fewer bottlenecks can improve decision-making.
00:00 Intro: Keeping the GPUs Full 00:22 Meet Bryan McCann: CTO & co-founder of You.com 00:43 Why Search Is Breaking - and Why It Becomes a Skill 01:41 From Search to Agents 03:18 The Case for Proactive, Context-Aware AI 04:30 We Don’t Need New Hardware - We Need Trust 05:43 The Trust Problem of Always-On Listening 07:57 Trust as the Real Bottleneck (Not AI Capability) 09:52 Delivering Immediate Value to Earn Trust 12:13 Business Models and Escaping the Attention Economy 17:27 What “Agents” Really Mean - and Why the Term Will Fade 20:37 Productivity, Parkinson’s Law, and Keeping the Machines Running 23:52 Scaling Yourself vs. Scaling Your Team 29:57 Building Culture: Automate, Throw Away, Rebuild 35:46 Designing Organizations Like Neural Networks 45:02 Recruiting for Initiative in an AI-Native Organization 49:18 The debrief
Building An Enterprise AI Innovation Lab: A Master Class with Humza Teherany, Chief Strategy Officer of Maple Leaf Sports and Entertainment
21 Jan 2026
00:58:15
In this episode, Humza Teherany breaks down how he bridges deep technical fluency with strategic leadership at MLSE, home to the Raptors, Maple Leafs, and more. He shares how a vacation turned into an AI reawakening and how that hands-on immersion led to a fundamental shift in how his organization builds and experiments.
Humza walks through MLSE’s build in a day practice, their internal AI platform, and why speed to prototype now unlocks more than just efficiency. It changes who gets to shape the future. He, Jeremy, and Henrik explore the limits of traditional enterprise AI rollouts and how to build spaces for superusers that enable company-wide transformation. The conversation covers how technical literacy impacts credibility, why idea execution is the new differentiator, and how Humza’s five-year-old inspired a bedtime story app powered by AI.
Whether you're a CTO, a founder, or just figuring out where to start, Humza makes a compelling case. The best leaders don’t delegate this moment. They build.
Key Takeaways
Leaders should not delegate the AI moment Humza, Henrik, and Jeremy agree that this is a moment for leaders to be hands-on. The ones who build and explore the tools themselves are the ones unlocking real impact.
Technical fluency builds credibility and better decisions Humza’s return to his technical roots has changed how he leads. Understanding how AI works helps leaders earn trust and make smarter, faster choices.
Speed enables inclusion MLSE’s build in a day model allows more people to contribute ideas and see them turned into real prototypes. Moving fast isn’t just efficient - it changes who gets to participate.
Empower your superusers first Rather than starting with enterprise-wide training, Humza focuses on enabling the small group already eager to build. That early energy helps drive broader culture change.
00:00 Intro: Humza Teherany and MLSE 00:27 The Role of C-Suite Leaders in AI 01:08 Reconnecting with Technical Skills 02:08 Diving Deep into AI Tools 03:03 The Importance of Hands-On Learning 04:25 Progression from Consumer to Technical AI Tools 07:28 Building a Business Case for AI 10:03 Creating a Culture of Innovation 14:00 Implementing AI in Business Operations 21:05 Challenges and Strategies in AI Adoption 26:17 Organizational Structure for AI Success 32:02 The Importance of Reviewing and Planning Code 33:01 The Future of Solo Developers and New Technologists 34:58 Reimagining Company Structures with AI 38:55 Key Skills for Future Technology Leaders 41:19 Personal AI Experiments and Innovations 46:52 Encouraging Creativity in Children with AI 49:11 The Debrief
Why AI Gets People Wrong: The Real Source of Insight with Anthropologist Mikkel B. Rasmussen
06 Jan 2026
00:56:22
Mikkel B. Rasmussen brings a rare lens to the AI conversation. As an applied anthropologist, he has spent decades helping companies like LEGO uncover what is really going on beneath the surface.
In this episode, he shares how deep insight often begins with being wrong, why surprise is the clearest sign you have found something meaningful, and how the pain of not knowing is essential to breakthrough thinking. He also explains how AI is transforming his own research, from pattern recognition to video ethnography, and introduces a provocative idea: Anthropology Without Anthropologists.
Jeremy and Henrik reflect on what it means to teach AI how to surprise us, how synthetic data might reshape experimentation, and why better insights begin with better questions.
Key Takeaways
Insight starts with being wrong Mikkel defines insight as the gap between how we think the world works and how it actually is. Anthropology helps uncover these mismatches, and that is where real breakthroughs begin.
Pain is part of the process Mikkel and Jeremy both reflect on the emotional struggle that precedes insight. The doubt, sleepless nights, and questioning whether the work will ever come together is not failure. It is a necessary stage of discovery.
Surprise is a signal The moment of surprise, when a new pattern emerges or an assumption is shattered, is at the core of applied anthropology. For Mikkel, it is the clearest sign that you have found something real.
AI can accelerate experimentation Mikkel shares how AI is already helping his team analyze patterns, run faster experiments, and even conduct interviews that outperform humans in some cases. The goal is not to replace people but to push the limits of what is possible.
00:00 Intro: Why This Conversation Matters 00:25 Meet Mikkel: Founder of Human Activity Laboratory 01:14 Understanding Anthropology and AI 03:32 Applied Anthropology: Tools and Techniques 04:56 The Role of Narratives in AI 07:06 The Importance of Sensory and Social Dimensions 13:06 Case Study: LEGO and the Anthropology of Play 21:07 The Role of Surprise in Anthropology 27:51 AI and Human Synergy 31:26 Exploring AI's Limitations and Potential 32:46 Anthropology Without Anthropologists 34:17 AI's Role in Generating Insights 37:23 Human Bias in AI-Generated Ideas 42:05 Synthetic Data and Its Applications 47:34 The Future of AI in Anthropology 49:25 The Debrief
How the World’s Leading AI-First Fashion House Flips the Cash Flow Equation - with Diarra Bousso
24 Dec 2025
01:09:09
Diarra Bousso returns to Beyond the Prompt to share how she's reprogramming the fashion industry using AI, math, and a relentless spirit of experimentation. From selling AI-generated products before they exist to cutting out waste and wait times, she walks us through a radical new approach to design and operations.
She explains how her team uses scientific rigor to test marketing ideas, create on-demand collections, and rethink the traditional fashion calendar. Diarra also opens up about the origin of her experimental mindset, which began during a year of recovery after a life-changing accident, and how that philosophy now shapes her leadership.
The episode wraps with reflections on sustainability, mental health, and what it means to build a joyful, human-first company in the age of AI. Diarra shares how she’s using AI not just to scale her business, but to reclaim her time, and why her next venture might bring these tools to creators everywhere.
Key Takeaways
Experimentation is the foundation Diarra treats her entire business as a lab. Every idea is a test, and her team is trained to think in hypotheses, measure results, and adapt quickly.
AI enhances human creativity She sees AI as a creative partner, not a replacement. It helps her move faster, make smarter decisions, and focus on the parts of design that require real taste and vision.
Sell before you build By testing AI-generated designs with customers before making anything, Diarra unlocks cash flow, cuts waste, and sidesteps the long timelines of traditional fashion.
Sustainability starts with the founder Diarra applies the same mindset to her own life. She’s using AI to reclaim time, reduce burnout, and build a business that supports health as well as growth.
00:00 Intro: AI-Driven Fashion 00:13 Meet Diarra Bousso: Founder of DIARRABLU 01:43 The Power of Experimentation 02:00 A Life-Changing Accident and Recovery 04:40 Embracing a Culture of Experimentation 06:13 Scientific Approach to Business 09:48 Empowering the Team 15:03 AI in Fashion Design 18:36 Revolutionizing the Fashion Industry 28:09 Traditional vs. Digital Fashion Models 32:18 Embracing AI in Fashion Design 32:49 Collaborating with Retailers Using AI 35:06 AI's Role in Prototyping and Design 36:58 The Future of AI in Creative Industries 39:14 Navigating Resistance to AI 48:10 Operationalizing AI for Efficiency 52:18 Balancing Innovation and Personal Well-being 57:19 Debrief
The Future of AI with Illia Polosukhin: The Man Who Put the T in GPT
09 Dec 2025
00:54:46
In this episode, Illia Polosukhin joins Henrik and Jeremy to trace the origins of transformers and how practical constraints inside Google led to a breakthrough that reshaped modern AI. He explains why recurrent models were hitting limits, how parallel attention opened the door to scale, and why he believed a major jump in capability was imminent long before the rest of the world saw it.
The conversation then turns to the risks and responsibilities of today’s AI systems. Illia describes how models can be subtly guided to influence user opinions, why open weights are not the same as truly open models, and how hidden behaviors can be embedded during training. He explains why provenance and verifiable data pipelines matter, especially as AI begins mediating more of the information we rely on.
Later in the episode, Illia outlines how blockchain can support trust, identity, and coordination in a future where AI agents act on our behalf. He shares why information is becoming more valuable than money, how ownership of personal AI models will shape user agency, and why domain expertise becomes significantly more powerful when paired with modern generative tools.
Key Takeaways:
Transformers emerged from practical constraints, not theory Illia explains that the shift from recurrent networks to attention was driven by speed and parallelization needs at Google, not a desire to invent a new paradigm.
AI’s step change was foreseeable to early builders Illia expected a ChatGPT level breakthrough several years before it arrived, based on clear research signals and accelerating model performance.
Provenance and trust will define the next phase of AI As AI systems can be subtly manipulated, Illia argues that verifiable data pipelines and transparent training processes are essential to prevent large scale misinformation.
Ownership and identity matter in an agent driven world Illia believes individuals will soon rely on AI agents that act autonomously, making it critical that users own their models and that interactions between agents are secured and verified.
00:00 Intro: AI and Information Control 00:29 Meet Illia Polosukhin: Co-Author of 'Attention is All You Need' 01:03 The Evolution and Impact of AI 13:24 The Birth of Near AI and Blockchain Integration 15:16 Challenges and Innovations in Blockchain and AI 22:17 Privacy and Security in AI Applications 26:58 Exploring Sleeper Agents in AI 29:19 Practical AI Implementation in Teams 30:06 AI's Role in Product Development 31:41 Challenges and Future of AI in Development 36:35 AI and Economic Alignment 41:46 The Future of AI Agents 44:14 Debrief
AI’s Next Frontier: World Models Explained by Christian Keller
27 Nov 2025
00:45:04
In this episode, Christian Keller joins Henrik and Jeremy to explain how world models are shaping the next stage of generative AI. He talks through how AI learns using different types of inputs, and why video adds a sense of continuity, change, and cause and effect that text alone does not provide. Christian shares vivid analogies and clear examples to show what multimodal models make possible.
The conversation moves into how AI is now used throughout the research process, from generating synthetic data to evaluating model outputs. Christian shares how this loop is already in motion and how AI is helping scale and accelerate experimentation. He also reflects on the shift after ChatGPT launched, and how that changed the pace and structure of research work.
Later in the episode, Christian describes how individual workflows are evolving, and how asking simple questions like “Could AI help with this?” often opens new possibilities. He shares examples from his own work and home life, including how his wife built and graded her own French exercises using generative tools.
Key Takeaways:
Text removes essential information Christian explains that text compresses reality and loses detail, context and temporality. Images and video help restore what text leaves out.
World models give AI a sense of change Video introduces the before and after and how things move or enter a scene. This helps models learn cause and effect and builds more robust understanding.
AI helps build AI Models can generate data, evaluate results and support researchers during development. Christian shows how this creates new ways of scaling experimentation and training.
Workflows shift when AI handles early steps Christian shows how tasks like debugging and prototyping change with generative tools, which reshapes roles and opens new opportunities for innovation.
00:00 Intro: Information Compression 00:37 Meet Christian Keller: AI Expert 01:13 The Evolution of AI Products 02:11 Impact of ChatGPT on AI Development 02:38 Understanding PyTorch and Its Role 07:41 The Bitter Lesson in AI 09:12 Challenges and Future of AI Models 18:57 Using AI to Build AI 23:25 Innovative Chat Interfaces 23:41 Building the Autos Platform 24:35 Epiphanies in AI Integration 25:18 AI in Entrepreneurial Workflows 26:32 Challenges in AI Integration 31:15 Bias in AI Models 38:06 Debrief
How Science Suggests You Change Your Organization - with Prosci’s Tim Creasey and Paul Gonzalez
11 Nov 2025
00:53:46
Generative AI is moving fast, but most organizations aren’t. Tim Creasey and Paul Gonzalez have spent their careers studying why. As leaders at Prosci, they’ve worked with thousands of teams navigating complex change, and in this episode they share what their research says about the human side of transformation.
They discuss why traditional tactics like comms and training break down in the face of rapid AI adoption, and how successful organizations create the conditions for people to actually change. From hands-on leadership and peer-driven learning to the power of experimentation and the ADKAR model, this conversation is packed with practical tools and hard-earned insights.
Tim and Paul also explore how AI is reshaping organizational structures, what “exposure hours” reveal about executive readiness, and why culture beats mandates every time. Whether you’re leading change or stuck inside it, this episode offers a grounded look at what actually works when everything is in motion.
Key takeaways:
Bold vision is not enough - it also needs to be balanced The most effective AI leaders communicate both where the organization is going and what teams are doing right now to get there. Prosci’s research shows that near-term clarity matters just as much as long-term ambition.
Leaders need to use the tools themselves Tim and Paul introduce the idea of “exposure hours” as a leading indicator of readiness. The more time executives spend actively experimenting with AI, the better positioned they are to lead transformation.
Experimentation requires structure and safety Organizations can’t just tell people to try new things. They need to carve out time, reduce the stakes, and make experimentation a shared and visible part of how work gets done.
Real change still happens one person at a time Despite all the new tech, the fundamentals haven’t changed. Individuals need awareness, desire, knowledge, ability, and reinforcement to adopt new behaviors. Prosci’s ADKAR model remains essential for making change stick.
00:00 Introduction to Change Management and AI Adoption 00:25 Meet the Experts: Tim Creasey and Paul Gonzalez 01:51 The Challenges of Change Management 04:07 Generative AI Transformation: Unique Challenges 07:44 Key Ingredients for Successful AI Adoption 15:18 Building a Culture of Experimentation 20:43 The Role of Leadership in AI Transformation 25:54 Future Organizational Designs with AI 27:02 Disruptive Organizational Changes 28:00 Examples of Innovative Enterprises 28:15 Military Analogies in Business 29:30 Challenges in Organizational Change 30:36 Timeless Principles of Change Management 31:36 The Role of Leadership in Change 33:13 ADKAR Model for Change 35:51 Addressing Resistance to Change 40:05 Effective Communication Strategies 47:48 Concluding Thoughts and Reflections
You Can’t Vibe Code a 100-Ton Truck: Inside Applied Intuition’s Approach to Safety-Critical AI
28 Oct 2025
00:55:54
Applied Intuition builds the kind of AI you don’t see, but can’t live without. Co-founders Qasar Younis and Peter Ludwig share how their $15 billion company powers vehicle intelligence across cars, trucks, tanks, mining equipment, and defense systems operating in some of the most demanding conditions on earth.
They explain why combining AI with safety-critical systems raises the stakes, how a single mistake can destroy an entire company, and why so many autonomy startups ended up in the “graveyard.” The conversation explores the slow, methodical path to real autonomy, the hidden complexity of machines that run nonstop, and why consumer AI metaphors break down once software meets the physical world.
Qasar and Peter also reflect on how Applied uses AI internally, how their principle of “radical pragmatism” keeps innovation grounded, and what it takes to move fast without breaking things when lives and livelihoods are on the line. From six-figure labor shortages in remote mines to the future of defense and logistics, this episode reveals how AI is quietly transforming the physical world — one carefully coded system at a time.
Key Takeaways:
Safety changes everything about AI When AI moves from the screen to the real world, the rules change. Qasar and Peter explain why building for trucks, tanks, and jets demands a different kind of discipline — one where precision and safety replace speed and iteration.
The graveyard of autonomy is real There’s a long list of companies that underestimated what it takes to build safe, reliable autonomy. Applied Intuition’s founders share what went wrong — and why moving slower has been their biggest advantage.
Radical pragmatism is the hidden differentiator Inside Applied Intuition, “radical pragmatism” isn’t a slogan — it’s a practice. Qasar and Peter describe how it guides product decisions, culture, and leadership, helping them innovate in places where failure isn’t an option.
The next frontier of AI is off the screen From mines to military systems, the future of AI won’t be chatbots — it will be machines that think, move, and decide in the physical world. Jeremy and Henrik reflect on how that shift raises the bar for builders, leaders, and the technology itself.
00:00 Intro: Safety Critical Systems 00:33 Meet the Founders of Applied Intuition 01:09 Understanding Applied Intuition's Unique Approach 03:02 The Human-Machine Teaming Concept 07:26 Challenges in Autonomous Driving 16:39 AI in Industrial Applications 28:27 Future of Fighter Jets and AI 29:50 AI in Applied: Coding Tools and Beyond 33:16 Radical Pragmatism and AI Integration 36:03 Challenges of AI Adoption in Large Organizations 39:56 Human and Technical Challenges in AI 42:02 Innovation and Organizational Structure 48:38 Reflections on AI and Future Prospects
How IBM Used AI to Cut 40% of HR Operating Costs and Reinvest in the Company
15 Oct 2025
00:53:08
As Head of IBM Consulting, Mohamad Ali led one of the most ambitious enterprise AI transformations to date. By making IBM its own “Client Zero,” his team tested every AI solution internally before bringing it to market. The effort began with massive hackathons involving 150,000 employees, turning curiosity into capability and belief at scale.
Mohamad shares how leadership alignment, process redesign, and broad employee engagement drove $3.5 billion in cost savings and renewed growth. Jeremy and Henrik reflect on why IBM’s model may signal the next evolution of consulting — where organizations act as their own laboratories for change
Key Takeaways:
Start with Yourself: “Client Zero” Works IBM transformed internally before advising clients, using its own systems as a testing ground. This allowed the team to validate AI tools, workflows, and cultural shifts in real conditions, creating credibility and clarity before going to market.
Transformation Needs More Than Tech Success came from a mix of technical leadership, process redesign, and cultural momentum. AI wasn’t just layered on; it was embedded into workflows, backed by leadership buy-in, and powered by 150,000 employees who participated in company-wide hackathons.
Digital Labor Is Reshaping Business Models IBM automated most transactional HR tasks with AI tools like AskHR, driving a 40% reduction in HR operating costs — a look at how hybrid human–AI teams transform services. Measure and Share the Impact Transformation became real when IBM tied outcomes to business metrics. By reporting $3.5 billion dollars in savings and tracking results with the CFO, IBM showed how to make AI adoption tangible, accountable, and visible to both employees and investors.
00:00 Intro: HR Automation 00:41 Introduction of Mohamed Ali and IBM's Transformation 01:14 IBM's Enterprise Transformation 01:41 The Role of AI in IBM's Success 03:25 Rejoining IBM: A Strategic Decision 04:33 Key Components of AI Implementation 07:21 Employee Engagement and Hackathons 08:59 Technical Leadership and AI 10:37 Global Tax Optimization with AI 11:17 Scaling AI Solutions for Clients 22:00 Monetizing Digital Labor 26:50 Digital Labor and Procurement Projects 27:29 Unbundling and Economic Implications 28:44 Technological Shifts and Market Expansion 30:04 AI-Powered Business Transformations 32:22 Case Study: L'Oreal's AI Integration 39:13 HR Automation and Cost Reduction 42:09 Creative Innovations in AI Applications 43:59 Advice for Leaders on AI Integration 45:43 Final thoughts
How Do You Strategize in the AI Era? - with Martin Reeves, Head of BCG’s Think Tank
01 Oct 2025
01:06:01
Martin Reeves has spent decades advising CEOs on how to think about strategy. As head of BCG’s Henderson Institute, he has built a career challenging leaders to balance efficiency with imagination and to prepare for the next disruptive shift.
In this conversation, Martin tells Henrik and Jeremy why AI alone will not give companies an edge and might even strip them of advantage. He unpacks the “two jobs of business”: playing the current game better than anyone else while simultaneously asking what the next game will be. He argues that AI only sharpens this paradox, forcing leaders to think faster, experiment more, and draw on human imagination in new ways.
The discussion covers the risks of over-optimization, the future of consulting, and the paradoxes of AI adoption. Along the way, Reeves explains how AI can accelerate exploration, why framing the right questions is the strategist’s most important job, and why times of disruption are when number twos become number ones or disappear altogether.
Key Takeaways:
Strategy is the double game Long-term success means playing today’s game efficiently while also inventing tomorrow’s. Henrik and Jeremy stress how rare it is for leaders to do both, yet this is exactly what AI demands.
AI efficiency without imagination is a trap Adopting the same tools as competitors drives efficiency but commoditizes advantage. The hosts underline that imagination and unique use are what create real differentiation.
The strategist’s edge is asking the right question Martin highlights that strategy starts with framing the real question. Henrik and Jeremy note that questioning and cognitive diversity are crucial in the AI era.
Disruption reshuffles winners and losers Times of change are when number twos become number ones and leaders disappear. The wrap-up emphasizes the urgency of experimenting and adapting now.
Human imagination stays essential AI can accelerate exploration, but creativity, ethics, and originality remain uniquely human — and decisive for future leadership.
00:00 Intro: Two Jobs in Strategy, Today’s Game and Tomorrow’s Game 01:33 Martin Reeves and the Henderson Institute 04:02 Defining Strategy in the AI Era 05:12 AI and Human Imagination 09:20 Efficiency vs. Competitive Advantage 13:18 Organizational Design for the Future 23:09 The Paradox of Imagination in Business 33:02 Harnessing Serendipity for Innovation 35:18 Devil’s Advocacy and Meeting Optimization 36:51 Where AI Helps and Hurts Organizations 38:16 The Limits of AI Training Data 42:56 How Martin Uses AI Day to Day 47:09 What’s the Next Game for Consulting 53:15 Final Reflections
The AI Playbook Every Leader Needs: A Chat With Adam Brotman & Andy Sack
16 Sep 2025
01:04:59
Adam Brotman and Andy Sack sit down with Henrik and Jeremy to unpack their book AI First and the framework they have developed for leaders. They argue that AI is not just another technology wave but a leadership reset that demands new playbooks, new structures and new ways of thinking.
They explain why AI should be seen as an augmentation of human intelligence, an “Ironman suit” for leaders, and how mindset, experimentation and governance are essential to adoption. The conversation also explores organizational redesign, the role of executives in fostering AI literacy and the urgency of adapting quickly as the technology advances.
This episode offers a practical and forward-looking discussion on how leaders can integrate AI across their organizations, build cultures of experimentation and future-proof their businesses in a rapidly changing landscape.
Key Takeaways:
AI is a leadership reset, not just a technology shift. Adam and Andy argue that AI demands a new playbook for leaders. It is not simply another tool, like mobile or digital before it, but a force that changes how companies are structured, how decisions are made, and how leaders must think about competition.
AI should be treated as a co-intelligence tool — an “Ironman suit” for leaders. Instead of replacing humans, AI augments their capabilities. Leaders who embrace AI can make smarter, faster decisions and guide their organizations more effectively. The metaphor of the Ironman suit captures this idea of augmentation rather than substitution.
Culture and experimentation matter more than the tools. Mindset, governance, and a willingness to experiment are the foundations of becoming AI-first. Adam and Andy stress that companies need structures like AI councils, experimentation frameworks, and a culture that celebrates rapid prototyping in order to integrate AI across the organization.
The urgency is real: companies that delay will fall behind. Jeremy and Henrik underline this in their closing reflections — businesses cannot treat AI as optional or wait for perfect clarity. The pace of change is accelerating, and organizations that don’t engage now risk losing ground permanently, while those that act can reinvent themselves and secure long-term advantage.
00:00 Intro: The Urgency of AI 00:19 Meet the Authors & The Premise of AI First 03:43 Defining an AI-Forward Leader 05:02 Adoption, Resistance & the AI Wake-Up Call 08:01 Why Mindset Matters More Than Tools 09:39 Experimentation, Governance & AI Culture 14:09 Re-architecting Organizations for AI 28:42 Balancing Innovation and Safety 35:45 The Evolution of AI Safety 37:46 Open Source vs. Closed Source Debate 40:07 AI’s Role in Organizational Agility 41:32 Human Augmentation & Co-Intelligence 42:34 The Future of AI and Autonomous Agents 46:14 Prototyping, Vibe Coding & Rapid Innovation 54:02 The Future of Organizational Design & Final Reflections
How Entrepreneurs Can Compete in the Age of AI: Henrik Werdelin & Nicholas Thorne on Their New Book Me, My Customer and AI
02 Sep 2025
00:49:33
In a shift from the usual format, Henrik Werdelin steps into the guest seat—alongside Nicholas Thorne—for a live conversation with Jeremy Utley about their new book Me, My Customer, and AI. They explore what it takes for entrepreneurs to compete in the age of AI — from redefining resourcefulness to thinking like founders, even inside a job.
The discussion dives into the book’s central frameworks, including the Five Ps (powers, passions, possessions, positions, and potentials) and the “it sucks that…” approach to identifying real problems worth solving. Along the way, they reflect on how AI is changing the leap from idea to execution, why more people may need to think entrepreneurially, and the shift from operating to orchestrating.
They also share lessons from the writing process itself—how they tried to use AI, where it fell short, and why Me, My Customer, and AI ends when it does.
This episode isn’t just about launching a book. It’s about rediscovering agency, and the questions we all need to ask when starting something new.
Key Takeaways:
This isn’t a book about AI—it’s a book about you. Henrik and Nicholas share how the real questions emerging from AI are deeply human ones. The book focuses first on self-understanding, then on the customer, with AI as the third piece—not the center.
The Five Ps framework helps you figure out what to build—and why. Powers, passions, possessions, positions, and potentials offer a structured way to explore personal founder-market fit. It’s a tool for generating ideas, but also for stress-testing them.
Real problems often hide in plain sight—it just sucks that no one’s solved them. Using the phrase “it sucks that…” makes it easier to spot problems worth solving. It’s simple, emotional, and sharp enough to cut through vague ideas and find what really matters to people.
Entrepreneurial thinking isn’t just for founders anymore. In a world shaped by AI agents and fluid roles, more people will need to act like entrepreneurs—taking initiative, connecting dots, and orchestrating rather than operating.
00:00 Intro: The Human Questions Behind AI 00:37 Personal Reflections on AI 01:26 The Book’s Unique Perspective 02:55 AI and Human Resourcefulness 05:46 Entrepreneurship in the AI Era 13:05 The Five Ps Framework 23:53 Identifying Real Problems 25:39 Why Identifying and Reframing Problems Matters 26:27 The Concept of “It Sucks That” 27:23 Historical Context and Practical Applications 28:22 The Role of Language in Problem-Solving 29:43 AI’s Influence on Writing and Creativity 31:47 Challenges and Limitations of AI in Writing 35:38 The Future of AI in Creative Processes 43:30 Entrepreneurial Skills for the Modern Era 48:26 Audience Interaction and Final Thoughts
Inside Zapier’s Code Red: How CEO Wade Foster Hit Pause to Reinvent for AI
19 Aug 2025
01:03:23
Wade Foster, co-founder and CEO of Zapier, joins Henrik and Jeremy to talk about how AI is changing the company from the inside out. He shares the moment Zapier declared a “code red” on AI and the steps they took to turn urgency into action — encouraging more experiments, removing tolerance for inaction, and celebrating wins along the way.
Wade discusses his own AI use cases, the importance of internal examples in driving adoption, and why duplication of efforts can speed up learning. He reflects on the leadership challenge of guiding a 14-year-old company through cultural transformation, balancing productivity gains with employee well-being, and preparing for a future where AI agents work with each other.
This episode offers a clear, practical look at what it takes to embed AI into an established organization, and keep it moving forward.
Key Takeaways:
A “code red” can be a catalyst for real change. When Zapier declared a company-wide “code red” on AI, it wasn’t just a signal. It pushed people to experiment more, act faster, and rethink established ways of working.
Culture is harder to change than technology. The real challenge wasn’t getting the tools in place, it was getting people to use them. Zapier’s approach focused on rewarding curiosity, sharing internal examples, and removing tolerance for inaction.
Duplication can drive innovation. Instead of centralizing all AI projects, Zapier encouraged parallel efforts. When multiple teams tackled similar problems, they often uncovered different and better solutions more quickly.
Leadership in the AI era is about speed and sustainability. Henrik and Jeremy highlight how Wade’s approach blends urgency with care for the people doing the work. Productivity gains matter, but so does avoiding burnout and making AI adoption last.
00:00 Setting Company Culture: Rewards and Tolerances 00:43 The Rise of AI at Zapier 02:19 Wade's Social Media Presence 05:06 Challenges in AI Adoption 07:32 Personal Use of AI: Health Tracking 10:21 Business Applications of AI 13:34 Automating Repetitive Tasks 20:35 Voice of Customer Program 24:26 Customer Brief Generator 33:27 Code Red: Embracing AI 35:32 Subtle Encouragement and the Impact of GPT-4 36:38 Code Red: A Turning Point 36:51 Embracing AI: From Fear to Familiarity 38:13 The Journey to AI Adoption 39:11 Challenges in Organizational Change 40:41 Managing Resistance and Encouraging Experimentation 43:55 Building a Remote Culture with AI 46:29 The Future of Work and AI 48:33 Agent-to-Agent Communication 51:32 The Importance of Duplication in Innovation 56:43 Final Thoughts
Can AI Replace Me? Evan Ratliff on Letting an AI Clone Live His Life
05 Aug 2025
00:58:11
In this episode, Evan Ratliff, journalist and creator of the podcast Shell Game, shares the wild and personal story behind his experiment in AI voice cloning. What began as curiosity turned into a six-month dive into building an AI version of himself—one that could answer phone calls, conduct interviews, and even fool friends and family. From scamming the scammers to testing AI therapy, Evan walks us through what it’s like to put a synthetic version of yourself into the world and watch how people respond.
The conversation explores the uneasy collision of identity, automation, and ethics. Evan talks about the emotional reactions people had when they realized they weren’t actually talking to him, the disturbing effectiveness of AI in fraud, and the strange intimacy of hearing your own voice say things you didn’t write. He also reflects on what it means to resist optimization—not because tech can’t help, but because some parts of life aren’t meant to be outsourced.
This episode is a human story wrapped inside a technological one—about trust, loneliness, and how we navigate a world where even our voices aren’t entirely our own.
Key takeaways:
AI voice agents challenge more than trust—they challenge identity. Evan’s experiment revealed just how disorienting it is when people hear your voice and think it’s you—only to realize it’s not. The emotional impact was real: friends felt tricked, disconnected, and in some cases, deeply lonely.
Scammers are already using AI—and they’re getting better at it. Far from being hypothetical, AI-powered scams are already widespread and industrialized. Voice cloning isn’t just a curiosity—it’s a weapon, and we’re all potential targets. A family safe word might be your best defense.
Not everything should be optimized—and maybe that’s the point. Evan pushes back on the idea that life should be frictionless. In the pursuit of efficiency, we risk removing the small, inconvenient interactions that actually make life meaningful—like small talk, shared confusion, and human error.
This moment feels like early social media—and we should be paying attention. Henrik and Jeremy reflect on the eerie parallels between today’s AI boom and the rise of the social web. Back then, few anticipated the long-term impact on mental health and connection. With AI, we may be walking into similar territory—unless we ask harder questions now.
00:00 Intro: Thoughts on AI Deception 00:40 Meet Evan Ratliff: Technology, Crime, and Identity 01:13 The Shell Game Podcast: Exploring AI Voice Cloning 03:50 Challenges and Improvements in AI Voice Technology 04:57 Inspiration Behind the Voice Cloning Experiment 11:05 Practical Applications and Ethical Considerations 17:31 AI in Scamming: Risks and Realities 25:04 Protecting Yourself from AI Scams 27:49 Reflecting on Technological Change and Human Adaptation 29:59 The Reluctance to Embrace New Technology 30:36 The Dangers of Social Media 31:59 AI in Therapy and Personal Experiences 33:39 Creating an AI Agent of Yourself 38:09 The Challenges of Small Talk with AI 38:55 Personal Tech Stack and AI Usage 42:59 Balancing Efficiency and Meaningfulness 45:32 The Future of AI and Human Interaction 52:18 Concluding Thoughts and Reflections
How the Chief Creative Officer of an Award-Winning Ad Agency Prompts the Perfect Pitch
22 Jul 2025
00:42:13
In this episode, Jeff Benjamin, Global CCO of Tombras, shares how AI helps him get unstuck, build confidence, and push bold ideas forward—even when self-doubt creeps in. From romcom scripts to Arby’s pitches, he shows how AI acts as a sparring partner: sharpening thinking, stress-testing ideas, and keeping momentum alive.
We get into what separates distinct from generic, why affirmation can be a trap, and how the urge to share is still at the heart of creativity. If you're chasing big ideas—or just trying to beat the blank page—this one hits home.
Key Takeaways:
Affirmation builds momentum—but can also blind you — One of AI’s biggest features is how confidently it backs you up. That “glazing” energy feels great—but if you don’t challenge it, you risk falling in love with something average. Confidence needs a counterbalance: taste.
The best prompt is a person—not a question — Jeff gets better output by asking AI to role-play voices he respects—like Don Draper or a cold war-era Olympic judge. The magic isn’t in better instructions. It’s in asking from a more interesting perspective.
Your idea is ready when it bubbles over — Jeff doesn’t go to his team with half-baked concepts. He waits until the idea is bubbling—when he can’t not share it. That moment is emotional, not procedural. AI helps him reach it faster—but the instinct to share is still deeply human.
Big ideas have width—AI helps him see the shape — For Jeff, a great idea isn’t a line—it’s a landscape. If it’s a real “big idea,” it spawns more ideas: social angles, activations, scripts. AI helps him test whether a concept has legs—or if it’s just a clever line with no room to run.
00:00 Overcoming Self-Doubt in Business 00:37 Meet Jeff Benjamin: Creative Leader at Tombras 00:56 The Role of AI in Creative Processes 02:24 Using AI as a Sparring Partner 04:34 Practical Examples of AI in Action 09:31 The Impact of AI on Team Dynamics 11:37 Balancing AI and Human Creativity 14:13 The Future of AI in Creative Industries 21:06 Exploring Human Skills for AI Mastery 22:09 The Art of Asking Better Questions 22:40 AI as a Creative Partner 24:41 The Excitement of Sharing Ideas 30:09 Generational Differences in AI Interaction 32:35 The Risk of AI Dehumanization 38:19 Concluding Thoughts
Chief of Staff for the Masses: How Meta’s Joshua To Designs Wearables with AI
08 Jul 2025
01:00:37
In this episode, Joshua To, VP of Product Design at Meta, shares how AI is reshaping how—and where—we interact with technology. He walks us through Meta’s evolving approach to AR and wearables, why notifications are still the killer use case, and how AI is becoming the “brain behind empathy.”
We dig into what it means to build interfaces that understand you, why audio might be the future’s most underrated platform, and how designing for emotion changes everything—from form factor to function. Joshua also reflects on his path from launching a clothing brand to leading design at Google and Meta, and what those worlds taught him about craft, context, and human-centered systems.
This one’s for anyone designing AI into the real world—where every interface choice carries weight, and intelligence starts with listening.
Key takeaways:
Empathy Is the Real Intelligence — Joshua flips the definition of smart tech. It’s not just about outputs—it’s about understanding you. Context, tone, emotion—that’s what great AI will sense and respond to.
Design for the Moment, Not the Feed — AR’s killer use case isn’t games—it’s restraint. Joshua shares why the best AI product might just be the one that knows not to ping you. Context-aware computing is the real unlock.
Audio Is the Interface to Watch — Forget screens. The most powerful interface might be your ears. From wearables to ambient signals, Joshua explains why audio design is the next big frontier for human-centered AI.
AR Isn’t a Feature—It’s a System of Consideration — Joshua reframes augmented reality as quiet, ambient infrastructure. The real power of AR isn’t spectacle—it’s subtlety. It helps you move through the world with less friction, not more.
00:00 Intro: Fixing Notifications With AI 00:54 Meet Josh: VP of Product Design at Meta 02:06 From Hoodies to Hardware: Josh's Journey 03:53 The Google Experience: From Ads to Product Management 10:37 The Evolution of Google Glass and AR 19:12 The Role of AI in Josh's Career 22:25 Designing the Future: AR, VR, and Attention Management 32:49 Contextually Aware Suggestions 33:38 Leveraging Generative AI in Design 34:52 AI's Role in Concept Art and Storyboarding 41:24 AI Tools and Model Capabilities 45:54 The Future of AI and Wearables 51:58 Reflections and Takeaways
The AI Implementation Audit: What Section’s CEO Learned in 18 Months
24 Jun 2025
01:08:27
In this episode, Greg Shove, CEO of Section and founder of Machine and Partners, joins us for a "where are they now" follow-up—and doesn’t hold back. Greg walks through the rise of Pro AI, his new AI-powered coach, and why traditional upskilling is already obsolete.
We explore the overlooked friction points in AI adoption, from cultural taboos (“it feels like cheating”) to failed enterprise rollouts. Greg challenges the prevailing mental models and warns that the real upheaval is still ahead: business model disruption, not product disruption.
From royalty-based agents to outcome-based pricing, Greg lays out why service-heavy industries—from law firms to SaaS—are heading for a margin-crushing future. Plus: the moral responsibility of CEOs, the fallacy of lifelong learners, and why working with AI means holding onto your own judgment.
A sharp, honest look at what it really means to work smarter—not just faster—in the age of AI.
Key takeaways:
AI use is no longer optional—it's the new baseline. Proficiency with AI tools isn’t a competitive edge anymore—it’s a basic requirement. Greg argues that “being in the AI class” is now table stakes, and organizations must rapidly close the gap between aspiration and actual adoption.
Business model disruption will hit harder than tech disruption. Greg makes a compelling case that AI’s biggest impact won’t come from the tools themselves, but from entirely new ways of charging for value—like outcome-based pricing and AI-native service models that undercut human capital costs.
Leaders must shift from AI policies to AI manifestos. Adoption is stalling because organizations lead with fear. Instead, Greg urges leaders to clearly message that using AI is smart, encouraged, and expected—and to model that behavior themselves.
Most people won't be lifelong learners—so give them outputs, not courses. With Pro AI, Greg confronts a hard truth: most users don’t want to learn; they want results. AI-powered coaching that delivers outcomes—not just education—is the future of upskilling.
00:00 Embracing AI: Changing Work Culture 00:29 Introduction: Meet Greg Shove 01:10 AI in Daily Work: Tools and Changes 03:59 Business Model Disruption: The Next Big Shift 12:45 Training and Adoption Challenges 19:14 The Future of Work: AI's Impact on Jobs 32:02 Leadership and AI: Strategies for Success 35:20 Embracing AI in the Workplace 36:51 Workflow Redesign with AI 39:39 The Role of AI Agents 40:12 Challenges in AI Adoption 45:14 Pro AI: The AI-Powered Coach 51:03 Disrupting Business Models with AI 57:52 Cognitive Offloading and AI 01:03:02 Final Thoughts and Reflections
Rebuilding from Inside: How John Waldmann Led an AI Shift Without Breaking His Team
10 Jun 2025
00:52:29
In this episode, John Waldmann, CEO of Homebase, shares how the 10-year-old SaaS company blew up its roadmap and rebuilt around AI—from culture to code. He walks us through the shift from 20-page PRDs to lightning-fast demos, reclaiming product leadership, and pushing teams into their “oh shit” moment with AI.
We explore the leadership reckoning, cultural resistance, and practical playbook behind the transformation—and what it means for the future of SaaS, small businesses, and human-centered AI. If you're leading (or bracing for) an AI shift, this one’s packed with hard-earned lessons and honest insight.
Key Takeaways:
You Can’t Wait for Buy-In—Leadership Means Pushing the Shift — John didn’t wait for excitement or alignment—he took back product leadership and forced the move toward AI. It wasn’t about consensus, it was about momentum. If you’re leading a team through this kind of shift, your job isn’t to ask for permission—it’s to create urgency before it's obvious.
Speed Over Specs — Prototypes Are the New Strategy — Homebase moved from 20-page PRDs to live demos built in hours. That switch didn’t just make shipping faster—it changed the way teams learn, think, and listen to customers. The takeaway? Stop planning in the abstract. Ship something real, now.
Culture Is the Real AI Roadblock — The hardest part of going AI-first isn’t tech—it’s trust, fear, and inertia. From engineers to support teams, John had to help people reach their “oh shit” moment with AI. That’s when change sticks. Until then, it’s just optional homework. Leaders need to make adoption inevitable.
AI Should Bring You Closer to Your Customers, Not Farther — This episode isn’t about chasing shiny tools. It’s about using AI to reduce the noise—so your team can focus more on humans, not less. For John, pragmatic AI is about freeing up time, getting closer to customer problems, and making the org feel smaller, not colder.
00:00 Introduction and Initial Reactions to AI 00:31 Meet John Waldmann and the Story of Homebase 00:53 Reinventing Homebase as an AI-First Company 01:46 From PRDs to Prototypes: Building Faster, Learning Smarter 05:02 How AI Is Reshaping the Customer Experience 09:19 Culture Shock: Resistance, Skepticism, and AI Adoption 14:03 The End of SaaS as We Know It? 19:34 Leading Through Disruption: Ownership, Urgency, and Org Design 25:12 Forcing the Shift: Getting Teams to Embrace AI 27:50 Hiring the Unemployed—and Other Nontraditional Talent Bets 28:56 Curiosity > Credentials: What to Look for in AI-Ready Teams 31:57 New Expectations, OKRs, and Holding Teams Accountable 37:10 Serving Small Businesses Better with AI 44:52 Final Thoughts: Team Dynamics, Founder Risk, and What’s Next
Why HR not CTOs Will Lead AI Augmentation - with Joshua Wöhle
27 May 2025
01:02:10
In this episode, Joshua Wöhle, co-founder and CEO of Mindstone, shares how AI can go beyond automation to truly augment thinking, strategy, and workflows. He walks us through the personal rituals and frameworks he uses to spot high-leverage opportunities, and why iteration—not speed—is the real unlock.
We explore how non-technical teams can build custom tools without code, why HR is the real AI driver in most orgs, and how the shift from SaaS to tailored internal solutions is reshaping the future of work. Packed with practical insights for anyone ready to move beyond the buzzwords and into real AI-powered productivity.
Key Takeaways:
AI’s Real Value: Augmentation Over Automation — Joshua explains why the biggest win with AI isn’t cutting tasks—it's using AI to amplify your thinking. If you’re only automating, you’re missing out on AI as a creative and strategic partner.
Crack the Code on the "Utility Threshold" — AI should save you time or improve outcomes. If it doesn’t, you haven’t hit the utility threshold yet. Joshua shares how to spot when AI becomes truly useful—and how small tweaks can unlock massive gains.
Why You Should Build, Not Buy (No Coding Needed) — Forget pricey SaaS tools. Joshua reveals how anyone—yes, even non-tech teams—can quickly build custom AI solutions that fit their workflow, saving time, money, and boosting flexibility.
HR: The Unexpected Hero of AI Adoption — It’s not your CTO driving AI success—it’s HR. Joshua makes the case for why empowering people, not just deploying tech, is key to creating AI-augmented teams that thrive in the future of work.
00:00 Introduction to Joshua Wöhle and Mindstone 01:10 Personal Practices for Automation 02:35 Early Wins in AI Automation 11:23 Levels of AI Proficiency 14:59 Utility Threshold in AI 24:51 AI in Organizational Structures 33:21 Introduction to the Early Space and AI Integration 33:45 Joshua's Entrepreneurial Journey and AI Augmentation 34:37 Challenges and Breakthroughs with AI 35:32 The Evolution of Building with Generative AI 37:56 The Future of SaaS and Internal Development 40:34 Practical Examples of AI Implementation 50:14 The Importance of Iteration and High-Value Tasks 54:56 Concluding Thoughts and Reflections
What AI Can't Replace - How The Atlantic Deals with Disruption
13 May 2025
01:00:45
In this episode, Nicholas Thompson, CEO of The Atlantic, shares a personal and expansive look at how AI is reshaping creativity, leadership, and human connection. From using ChatGPT in marathon training to rethinking journalism in the age of agents, Nicholas explores AI not just as a tool—but as a thought partner.
We dive into cognitive offloading vs. augmentation, the ethics of AI-generated content, and why preserving “unwired” intelligence still matters. He also reflects on leading through disruption, building analog habits, and fostering team-wide experimentation. A rich conversation on staying human in an increasingly automated world.
Key Takeaways:
Your “unwired” intelligence is your AI superpower — The more human skills you build—like deep focus, emotional presence, and analog thinking—the better you’ll be at wielding AI. Thompson argues that cultivating these unwired abilities isn’t just about staying grounded—it’s about unlocking the full potential of the tools.
Don’t fight the storm—gear up and adapt — AI is already transforming media and creative industries. Thompson compares it to a coming storm: you can’t stop it by yelling at the clouds. Instead, embrace it, understand it deeply, and make strategic decisions based on where it’s heading.
Leadership means showing, not just telling — As a CEO navigating disruption, Thompson doesn’t just advocate for AI exploration—he models it. From training staff on GPTs to walking the halls and testing ideas live, he treats leadership as a practice of visible experimentation and continuous learning.
AI relationships can’t replace real connection—but they can confuse it — Whether it's logging meals with a bot or losing a personalized Enneagram coach to a reset, Thompson highlights the emotional pull of AI and the dangers of relying on digital companions over human ones. Staying socially connected, especially through “third spaces,” is more important than ever.
00:00 Introduction to Nicholas Thompson 00:11 Navigating the Information Overload 01:10 Daily Tech Insights and Tools 02:10 Using AI for Content Creation 04:39 AI as a Personal Trainer 08:02 Emotional Connections with AI 12:12 The Risks of AI Relationships 16:17 Preparing for AGI and Cognitive Offloading 30:26 AI's Impact on Leadership 31:10 Navigating AI Competitors 32:01 Internal AI Strategies 32:49 Ethical Considerations in AI Usage 34:07 AI in Journalism and Writing 36:32 Practical AI Applications 40:27 Balancing AI and Human Skills 49:27 Future of AI in Media 53:50 Final Thoughts and Reflections
Prompting for Originality: How Devin McNulty Is AI-Enabling His Workshop Business
29 Apr 2025
00:55:50
In this episode, Devin McNulty, founder of Funmentum Labs and creator of Funware, shares how he’s turning fun into a serious engine for creative work. After 15 years of running workshops for Fortune 500s, Devin built an AI-powered facilitation tool that helps hybrid teams generate better ideas—without needing a pro in the room.
We explore how he treats AI like a co-facilitator, not a thought partner, and what it means to “pre-train” AI the way you'd brief a human. Devin also unpacks how to turn creative intuition into scalable software—and why levity, timing, and rough ideas can unlock big breakthroughs. A smart listen for anyone building tools, workshops, or teams that need to think more boldly.
Key Takeaways:
Fun Is a Strategic Tool—Not a Distraction – Devin challenges the assumption that “fun” and “serious work” are at odds. His facilitation method uses play to unlock alignment, compress timelines, and spark better ideas—especially in rooms that normally resist creative approaches.
AI Can Facilitate, Not Just Assist –Most teams use AI as a solo tool or sidekick. Devin flips the script—designing AI to act like a group facilitator. Funware injects prompts, rephrases challenges, and even drops well-timed bad ideas to shift group dynamics and drive progress.
Pre-training Your AI Is Like Prepping a Human Teammate –One of Devin’s biggest insights: treat your AI agents like collaborators. Build them with clear intent, layer in prompting strategy, and fine-tune them for the moment they’ll be used—just like you’d brief a co-facilitator before a workshop.
Productizing Yourself Is the New Playbook –Devin’s journey is a case study in AI-first entrepreneurship—turning deep craft into software. His advice? Start with your workflow, atomize it into repeatable components, and build tools that deliver value with the push of a button.
00:00 Intro to Funmentum Labs & Funware 00:38 Why Fun Is a Powerful Work Strategy 01:41 Overcoming Skepticism in Serious Workplaces 02:27 Techniques to Engage Resistant Teams 06:32 Can AI Be Funny? Humor in Corporate Settings 08:03 How Funware Uses AI to Drive Group Creativity 11:43 Automating Workshops with AI-Powered Prompts 14:04 Devin’s Path from Facilitator to AI Builder 16:21 Advanced Prompting Techniques in Funware 28:34 Creative Prompting: Logos, Personas & Play 30:04 Exercises to Push Beyond Obvious Ideas 31:35 How AI Unlocks Group Innovation 36:55 Pre-Training AI for Better Collaboration 43:35 Using AI as Muse, Challenger & Focuser 48:46 Final Thoughts
How Mihir Shukla Is Reimagining Work With 300 Million AI Agents (and Counting)
15 Apr 2025
00:48:47
In this episode, Mihir Shukla, CEO and Chairman of Automation Anywhere, shares how he’s building an autonomous enterprise—where AI doesn’t just assist work, but performs it. With over 300 million AI agents in action, Mihir argues the future of work is already here.
We dive into how Automation Anywhere automates everything from tax to customer service, how to spot high-impact use cases, and why culture—not tech—is the biggest blocker. Mihir also zooms out to explore the global productivity crisis, the shrinking workforce, and the moral imperative to upskill at scale. A powerful episode on what work can look like when AI is truly embedded.
Key Takeaways:
Don’t Wait for the Future of Work—Build It - Mihir’s team is already running 300 million AI agents across global enterprises. From automating 90% of tax operations to generating CEO-ready briefings on the fly, he shows how much of today’s work can be autonomous—and how fast it’s scaling.
Stalled Productivity? AI Is the Only Way Through - Despite $40 trillion in global IT spend, productivity hasn’t improved since 2008—and now the workforce is shrinking. Mihir argues that doubling productivity isn’t a moonshot—it’s an economic necessity, and AI is our best shot.
Change Doesn’t Come from the Top—It Starts with Teams - Transformation doesn’t begin in the boardroom. Mihir shares how just 2 out of 10 employees experimenting with AI can ignite org-wide momentum—if they’re given ambitious goals, proper training, and permission to lead.
Upskill the World, One Community at a Time - From the Mississippi Delta to Nepal, Mihir’s upskilling efforts prove that AI fluency doesn’t require a degree—just access. With the right training, someone flipping burgers can land a $120K AI job in three months. Talent is everywhere. Opportunity isn’t.
00:00 Introduction to Mihir Shukla & Automation Anywhere 01:20 Vision for Autonomous Enterprises 03:03 Reimagining Work Processes 04:17 Principles of Automation 06:12 Challenges and Solutions in AI Adoption 09:15 The Importance of AI in Modern Workplaces 21:31 Studying and Rethinking Work 26:55 The Challenge of Adapting to AI-Powered Workflows 27:55 The Impact of AI on Task Management 31:24 AI in Customer Service and HR Operations 33:03 The Strategic Value of AI in Finance 37:30 The Social Impact of AI and Upskilling Initiatives 40:40 Final Thoughts and Takeaways
Eric Porres is Rewiring Logitech’s Org for the AI Age. First; he trained 800 people himself.
03 Apr 2025
00:56:20
In this episode, Eric Porres, Global Head of AI at Logitech, shares how he’s working to turn a 7,000-person company into an AI-fluent organization. From running a GenAI survey to personally training 800+ colleagues in his first 100 days, Eric lays out the foundations of a practical, human-centered AI strategy.
He discusses building a culture of “augmented intelligence” through habits, champions, and clear frameworks—like prompt refinement, long-form instructions, and task-focused design. Looking ahead, Eric explores the rise of agentic AI, internal tools, and how to measure impact beyond usage metrics. A must-listen for anyone driving meaningful AI adoption at scale.
Key Takeaways:
AI Fluency Starts with Behaviour, Not Just Tools – Eric’s approach isn’t about pushing more AI - t’s about teaching people how to think differently. From measuring conversation depth to rewriting prompt habits, Logitech is focused on real behavioural change.
Train 800, Influence 7,000 – Before becoming Head of AI, Eric trained 800+ colleagues himself. That grassroots effort - combined with identifying “quiet champions” across teams- created the internal momentum for company-wide transformation.
Build the Right Interface, Not Just the Right Model – A powerful insight: it’s not which model you use, it’s how people interact with it. Logitech prioritized intuitive, user-friendly AI experiences to meet employees where they work.
From Individual Fluency to Agentic Teams – Looking ahead, Eric envisions a world where employees work alongside custom AI agents. The future isn’t just prompt mastery - it’s knowing what to delegate, what to own, and how to manage an AI-augmented team.
00:00 Intro to Eric Porres 00:46 What the First 100 Days Look Like as Head of AI 01:51 Measuring AI Adoption: Surveys, Usage & Quality 05:34 Training 800 Colleagues: How Eric Taught AI Mastery 19:50 From Side Role to Head of AI: Eric’s Transition Story 23:02 Scaling AI Across Teams: Tools, Access & Equity 28:56 Choosing the Right Model for the Right Job 30:28 Measuring Success: NPS, Feedback, and Real Usage 32:05 The Rise of AI Champions and Teaching as Proof of Mastery 34:31 Beyond Fluency: Preparing for the Agentic Future 36:45 Atomizing Workflows: Making AI Work for You 39:10 AI in Sales & Customer Service: The Agent Use Case 43:26 Personal Knowledge Bases and AI-Augmented Thinking 50:49 Final Thoughts and Takeaways
How Blair Vermette Went from AI Skeptic to a Pioneer of Viral AI Videos
18 Mar 2025
00:56:15
In this episode, Blair Vermette, founder of Rabbit Hole, shares his journey from traditional TV production to becoming a pioneer in AI-powered storytelling. Once frustrated by the rise of AI in creative work, Blair chose to lean in—leading to the creation of Floral, a viral Adidas spec ad that transformed his career.
He talks about scaling his creative studio, navigating the chaos of AI-generated content, and how his editing background gave him a competitive edge. Blair also breaks down his “break the spine” storytelling philosophy, the balance between curation and creation, and the enduring role of human instinct in an increasingly AI-shaped creative world.
Key Takeaways:
Curation is as Vital as Creation – AI doesn’t replace creativity; it enhances it. Blair emphasizes that knowing how to curate and refine AI-generated content is just as important as generating it.
Spec Ads Can Open Doors – Blair’s Adidas Floral campaign proved that self-initiated projects can be career-defining, attracting industry attention and unlocking new opportunities.
Instinct and Storytelling Still Matter – While AI can generate stunning visuals, human intuition, taste, and storytelling structure remain irreplaceable in making content truly compelling.
Adapting to AI is Crucial for Creatives – AI is reshaping creative industries, and those who embrace experimentation and evolve their skill sets will be best positioned for success.
Breaking the Spine Unlocks Originality – Blair challenges traditional storytelling structures by disrupting linear narratives, starting in unexpected places, and reshaping story arcs to keep audiences engaged.
00:00 Introduction to Blair and Rabbit Hole 00:25 Blair's Journey into Generative AI 01:53 The Impact of Generative AI on Creativity 04:35 Creating 'My Name is Gary' 07:51 The Cost and Constraints of Traditional Animation 14:38 The Making of the Adidas Spec Ad 19:02 The Viral Success and Its Aftermath 24:08 Scaling Up to Meet Demand 27:20 The Dilemma of Building a Team 28:55 The Importance of Instinct and Originality 29:48 Professionalism in Creative Work 30:16 Leveraging AI in Storytelling 34:50 The Value of Obsession and Specificity 36:02 Entrepreneurial Ideas for Creative Growth 44:02 Breaking the Story Spine 48:18 Navigating the AI Transition 50:58 Final Reflections and Encouragement
BONUS EPISODE: Boris Eldagsen: Why AI-Generated Images Aren’t Photography
12 Mar 2025
00:44:09
Berlin-based artist Boris Eldagsen made headlines when he won—then refused—the Sony World Photography Awards after revealing that his winning image was AI-generated. In this special episode of Beyond the Prompt, Eldagsen takes us through his transition from traditional photography to what he calls promptography—a new category for AI-generated images. He explores the fundamental differences between photography and AI-generated art, why clear definitions matter in creative competitions, and how AI unlocks new dimensions of artistic freedom. The conversation dives deep into the philosophical and technical aspects of AI-generated images, the role of surprise in the creative process, and what the future holds for photography in the age of AI. If you've ever wondered where art and AI collide—or how to embrace the unexpected in your creative work—this episode is for you.
Key Takeaways:
AI expands artistic freedom, not replaces artists – AI removes physical limitations, allowing artists to create purely from imagination. But vision, composition, and storytelling remain essential—great art is still shaped by human experience.
Surprise fuels creativity – Whether capturing an unexpected moment in street photography or experimenting with AI-generated images, Boris believes that embracing the unpredictable is key to artistic innovation.
AI isn’t photography—it needs its own category – Boris argues that AI-generated images aren’t made with light and shouldn’t compete in photography contests. Instead, he calls for a new category—promptography—to recognize AI’s distinct creative process.
00:00 Introduction to the Special Episode 00:41 Meet Boris Eldagsen: The AI Photographer 01:07 The Sony World Photography Awards Controversy 05:20 Defining Photography in the Age of AI 07:39 The Art of Promptography 12:10 Boris's Creative Process and Workflow 19:30 The Future of Photography and AI 30:53 Tips for Aspiring Promptographers 38:51 Exploring AI Tools and Techniques 41:29 Conclusion and Reflections
Future-Proofing Your Career and Income in the Age of AI with Dr. Joan Palmiter Bajorek
05 Mar 2025
00:42:42
AI is transforming careers, personal branding, and financial planning - so how can you stay ahead? Dr. Joan Palmiter Bajorek, entrepreneur, investor, bestselling author, and host of Your AI Roadmap, shares strategies from her new book to help future-proof your career and income. She breaks down how to build a strong personal brand, expand your network, and stay financially secure in an AI-driven world. We also explore AI’s impact on job searches, gender bias, and the balance between automation and authenticity. Whether you want to pivot into AI, strengthen your career, or make smarter financial moves, this episode offers valuable, actionable strategies to help you navigate the future.
Key Takeaways:
Optimize for AI Search – Treat your online presence like SEO for AI. Ensure your LinkedIn and personal website include the right keywords so AI-driven tools and recruiters can easily find you.
Networking Drives Career Growth – 70% of jobs come from introductions. Being proactive, following up, and offering value in professional relationships is key to unlocking new opportunities.
Financial Preparedness is a Career Advantage – Many high earners still live paycheck to paycheck. Building an emergency fund of 6–12 months helps navigate layoffs and career shifts with confidence.
AI Can Enhance, but Authenticity Wins – AI-generated headshots and tools can refine your brand, but people connect with realness. Finding a balance between AI optimization and human authenticity is essential.
00:00 Introduction and Background 00:22 The AI Roadmap Book 01:54 Key Actions to Future-Proof Your Career 03:01 Building an Emergency Fund 05:44 Leveraging AI for Financial Planning 07:36 Networking Strategies 10:59 Personal Branding with AI 14:11 The Human Element in AI 19:51 Effective AI Prompting Techniques 20:29 AI's Influence on Job Matching 22:21 Using AI for Personal and Professional Tasks 22:59 Choosing the Right AI Tool 25:08 The Future of AI and Human Collaboration 26:16 Balancing Career, Money, and Joy 28:00 Gender Bias in AI 32:30 Conclusion and Final Thoughts
How to build a business with AI? Founder of Audos - Nicholas Thorne on the New Rules for Entrepreneurship
18 Feb 2025
01:02:21
In this episode, Nicholas Thorne, co-founder of Audos, shares his mission to help a million entrepreneurs build sustainable, AI-powered businesses. He introduces the concept of the “Donkey Corn,” breaks down the Five P’s framework for spotting opportunity, and explains why AI makes entrepreneurship more accessible—and more urgent—than ever.
Nicholas also explores how to build with authenticity, leverage relationship capital, and align passion with purpose. This episode is full of tactical insights for anyone ready to turn ideas into action in the age of generative AI.
Key Takeaways:
AI Makes Entrepreneurship Essential – Nicholas highlights how AI-driven job displacement is reshaping traditional career paths, making entrepreneurship a necessary and forward-thinking choice.
The ‘Donkey Corn’ Model – Learn about this innovative, sustainable business model powered by AI that helps entrepreneurs scale effectively.
Relationship Capital is Key – Authentic connections and leveraging networks are fundamental to building successful ventures and understanding customer needs.
The Five P’s Framework – A simple but powerful tool for identifying market opportunities by focusing on customer pain points and aligning them with viable solutions.
Start Small, Scale Strategically – Nicholas emphasizes the value of beginning with manageable AI applications and iterating over time to create big, scalable impact.
00:00 Meet Nicholas Thorne: Co-Founder of Audos 01:06 The Mission of Audos: Empowering Entrepreneurs in an AI-Driven World 02:21 The Future of Work: Why AI Is Essential for Entrepreneurs 05:09 Real-Life Success Stories: The Donkey Corns Explained 09:40 The PreHype Journey: Building Entrepreneurial Expertise 22:24 The 5P Framework: Identifying Your Ideal Customer 31:56 Visceral Language and AI: The Power of Words in Business 33:05 AI’s Role in Business: Consolidating and Simplifying Language 34:14 Problem Reframing: How AI Assists in Tackling Big Challenges 36:27 Generative AI in Action: Early Experiments and Insights 40:48 The Inkling Slot Machine: Sparking Innovation with AI 45:12 Authenticity in AI-Driven Businesses: Why It’s Crucial 56:38 Final Reflections and Actionable Insights
Why your organization needs to embrace AI—Or get left behind, with Brad Anderson
05 Feb 2025
01:11:28
In this episode, Brad Anderson, President of the Product Group at Qualtrics and former Microsoft exec, shares how AI is transforming how businesses operate—from internal culture to customer experience. He reflects on Microsoft’s shift from a “know-it-all” to a “learn-it-all” mindset, and how that same curiosity is driving change at Qualtrics.
From analyzing unstructured feedback to running AI summits and hackathons, Brad offers real-world stories on embedding AI into daily workflows and upskilling teams at scale. A must-listen for leaders navigating transformation in the age of AI.
Key Takeaways:
Learn-it-all beats know-it-all – Brad Anderson highlights how adopting a learn-it-all mindset, inspired by Satya Nadella, drives cultural and organizational transformation.
AI adoption starts with action – Every individual in a company must engage with AI daily to foster understanding and integration.
Innovation requires safe spaces – Creating environments for AI experimentation, such as hackathons and playgrounds, is essential for encouraging adoption and upskilling teams.
You get what you measure – Brad emphasizes the importance of tracking AI engagement metrics to identify areas for improvement and sustain momentum.
AI will redefine organizations – From generative AI to synthetic data, Brad explores how AI fundamentally transforms how businesses operate and serve their customers.
00:00 Introduction to Qualtrics and Brad Anderson 00:21 From Surveys to AI: The Evolution of Qualtrics 01:41 Lessons from Satya Nadella 03:48 Building a Customer-Centric Culture 06:51 Adopting AI in Business 13:29 Upskilling for AI Integration 22:15 Organizing for Innovation 27:13 AI Summits and Hackathons at Qualtrics 36:42 ChatGPT Obsession 37:19 Notebook LM and Team Alignment 38:57 Innovation and Unexpected Wins 40:42 Using AI in Negotiations 44:18 The Future of AI and Large Language Models 45:25 Driving AI Adoption 48:47 The Rapid Growth ofAI 56:42 AI-Powered Surveys at Qualtrics 01:01:13 Generative AI and Feedback Mechanisms 01:05:54 Wrap-Up and Key Takeaways
Reinventing Recruiting: Anvisha Pai on Using AI to Automate Hiring
21 Jan 2025
00:36:55
Anvisha Pai, founder of Dover, takes us inside how her team is using generative AI to transform recruiting—automating everything from job descriptions to candidate outreach for over 500 companies. She shares lessons from her early AI experiments at MIT, and how building a fail-fast culture has helped Dover stay ahead of the curve.
We dive into how her team turns quick AI tests into scalable wins, and how a culture of curiosity fuels long-term innovation. Whether you're scaling a startup or exploring AI’s role in team workflows, this episode offers actionable advice for thriving in an AI-powered future.
Key Takeaways
Early AI Adoption – Anvisha shares how Dover leveraged GPT-3 for tasks like job description writing and email automation, overcoming early limitations through iteration.
Fail-Fast Culture – Building a culture that encourages experimentation without fear of failure is key to driving innovation.
Empowering Teams – Dover prioritizes self-starters and provides resources to help non-technical staff engage with AI.
Iterative Product Development – The team emphasizes solving real customer problems manually before building scalable AI-powered solutions.
Staying Informed – Anvisha stresses the importance of habits like following industry leaders and experimenting with new tools to stay competitive in a rapidly changing field.
00:00 Introduction to Anvisha and Dover 00:14 Early Fascination with AI 00:29 First Experiences with AI 03:05 Founding Dover and Co-Founders 04:00 Early Challenges and Iterations 04:49 Exploring AI Applications at Dover 06:34 Impact of AI on Recruiting 07:25 Developing AI Tools and Products 09:10 Company Culture and Innovation 16:20 Staying Abreast of AI Developments 30:38 Leadership and Management 33:23 Conclusion and Reflections