Our sponsor for this episode is Microsoft. Want seamless collaboration without the cost? Microsoft Teams offers a robust free plan for individuals that delivers unlimited chat, 60-minute video meetings, and file sharing—all within one intuitive workspace that keeps your projects moving forward. Head to ⁠https://aka.ms/every⁠ to use Teams for free, and experience effortless collaboration, today.

AI forces us to reckon with what makes us human—a question caught between science and spirituality that MIT’s Dr. Alan Lightman is uniquely placed to explore.

Dr. Lightman is a physicist, bestselling novelist, and professor of the practice of humanities at MIT. As one of the first at MIT to hold a joint faculty position in both the sciences and the humanities, he’s at ease walking the line between the two disciplines.

I loved Dr. Lightman’s book Einstein’s Dreams, so I was psyched to have him on the show. We spent an hour talking about:

• Being a “spiritual materialist”: Dr. Lightman’s philosophy that knowing the scientific explanation for natural phenomena—like spiderwebs and lightning bolts—deepens our experience and feeling of wonder.

• The nature of consciousness: He believes that consciousness is a subjective experience emerging from the tangible activity of billions of neurons firing in our brains.

• AI isn’t conscious, even though it might appear to be: AI might display manifestations of consciousness—like the ability to plan for the future—but whether it has an inner experience in the truest sense is a fundamentally different question.

• Challenge your conceptions of what “natural” means: Dr. Lightman argues that since humans evolved through natural selection, everything our brains create—from eyeglasses and hearing aids to AI—can be considered “natural” as they are inevitable consequences of our naturally evolved intelligence

• AI that can do more than just data retrieval: Modern neural networks begin to approximate something resembling genuine thinking because the “digital neurons” process information in complex, non-linear ways.

• Evolution that blurs the lines between biology and technology: Dr. Lightman argues we’re driving our own evolution toward the “homo techno,” hybrid beings that merge human and machine; early examples include brain implants that enable paralyzed individuals to control robotic limbs.

Dr. Lightman also recently published a new book called The Miraculous From the Material, a collection of essays that combine scientific explanations of natural phenomena with his personal reflections on them. It has tons of striking pictures that you should check out.

This is a must watch for anyone interested in science, spirituality, and what it means to be human in the age of AI.

If you found this episode interesting, please like, subscribe, comment, and share! 

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Timestamps:

1. Introduction: 00:01:18

2. Science can deepen your sense of the spiritual: 00:02:36

3. The nature of consciousness: 00:11:31

4. AI might appear to be conscious, but it isn’t: 00:13:11

5. Why AI can be considered to be “natural”: 00:19:50

6. AI shifts the focus of science from explanations to predictions: 00:30:40

7. How modern neural networks simulate thinking: 00:33:48

8. Lightman’s vision for how humans and machines will merge: 00:39:38 

9. Does AI know more about love than you?: 00:43:11

10. How technology is accelerating the pace of our lives: 00:49:18

    
    

Links to resources mentioned:

• Alan Lightman: https://cmsw.mit.edu/alan-lightman/ 

• Lightman’s books: The Miraculous From the Material, Einstein's Dreams

• His documentary: Searching: Our Quest for Meaning in the Age of Science

• Walt Whitman’s poem: When I Heard the Learn’d Astronomer
  

Jonny Miller uploaded his entire life to ChatGPT to use it as the ultimate AI coach. 

He created what he calls a Codex Vitae—with core personality traits, values, goals, burnout signals and more to load into ChatGPT. It hyper-customizes his responses, to help him access deep meditation states, create custom supplementation plans, and do deep research on areas of brain and body that he finds interesting.  

Jonny runs a course on nervous system mastery, hosts a podcast, coaches founders and CEOs, and is building a wellness app—all using AI. As a long-time friend and writer for @every, I was psyched to have Jonny on AI & I to talk about how LLMs are expanding the breadth and depth of what he can do. We get into: 

• Energy as your greatest asset: Jonny’s philosophy around pursuing a non-traditional path—like us at Every—by fiercely protecting his energy and optimizing for “aliveness” instead of higher revenue figures.

• ChatGPT projects for everything: His use of projects in @ChatGPTapp to organize different areas of his life; for example, he uploads his meditation journal to a Jhana project and asks it for advice when he’s struggling with the practice on a particular day.

• Deep research in action: How he uses @OpenAI’s deep research to tackle practical questions about moving his family to Costa Rica, hilariously esoteric ones about whether there’s a connection between Pokémon and shamanism, and everything that lies in between.

• The rise of “centaur” teams: Jonny’s belief that @kevin2kelly’s prediction around “centaurs”—human + AI teams outperforming either human or AI working alone—is becoming our reality.

  
  

This is a must watch for anyone interested in using AI for personal development, coaching, or to build systems that can understand you. 

If you found this episode interesting, please like, subscribe, comment, and share! 

Want even more?

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To hear more from Dan Shipper:

• Subscribe to Every: https://every.to/subscribe 

• Follow him on X: https://twitter.com/danshipper 

  
  

Timestamps:

1. Introduction: 00:01:31

2. Dan and Jonny’s approach to running non-traditional businesses: 00:02:18

3. How Jonny uses ChatGPT to deepen his meditation practice: 00:12:04

4. Jonny uses AI to research a theory of how trauma is stored in our bodies: 00:25:44

5. Dan’s theory around how AI is changing science: 00:31:28

6. Jonny’s method to build personalized AI coaches: 00:32:35

7. How Jonny used OpenAI’s deep research to plan a move to Costa Rica: 00:47:07

8. Dan is developing an app that can predict his OCD symptoms: 00:52:50

9. AI makes the idea of a “quantified self” useful: 00:55:42

10. The future of human-AI coaching teams: 00:58:28

    
    

Links to resources mentioned in the episode:

• Jonny Miller: @jonnym1ller

• The nervous system mastery bootcamp: https://www.nsmastery.com/ 

• His podcast: Curious Humans with Jonny Miller 

• The nervous system regulation mobile app: Stateshift 

• Jonny’s method to build your AI coach: http://BuildyourAIcoach.com 

• More about Jhana: https://slatestarcodex.com/2017/09/20/meditative-states-as-mental-feedback-loops/ 

• Buster Benson’s Codex Vitate: https://2019.busterbenson.com/beliefs/

• The pieces Jonny has written for Every: “The Operating Manual for Your Nervous System,” “The Best Decision-Making Is Emotional,” “How to Pay Off Your Emotional Debt,” “The Art and Science of Interoception”     

I interviewed the Governor of New Jersey Phil Murphy.

We spent an hour talking about his vision for AI in government, economic development, and the regulatory challenges ahead. His approach is refreshingly pragmatic: 

• Spark real innovation at scale. Governor Murphy is laying the groundwork through an AI hub that pools the strengths of the government, academia (Princeton University), legacy tech (Microsoft), and next-gen players (CoreWeave). 

• Creating a place for the brightest minds to live and work. He’s making the Garden State irresistible for the best talent through walkable communities, legal recreational cannabis, and an angel investment tax credit.

• AI that augments teams, instead of replacing them. The Governor sees AI as an “accelerant” that enables teams to do more with the same number of employees. He’s walking the talk by training 61,000 NJ state employees in AI to automate busy work and free them to focus on strategic tasks.

• An integrated regulatory framework for AI. He believes that a technology as pervasive as AI should be regulated at a national level because the state-by-state approach could stifle innovation. 

Governor Phil Murphy is the first governor I’ve ever had on the show and I was honored he took the time to come on. I was also especially excited to do this because I grew up in New Jersey! This is a must watch for anyone interested in the intersection of AI and policy.

If you found this episode interesting, please like, subscribe, comment, and share! 

Want even more?

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To hear more from Dan Shipper:

• Subscribe to Every: https://every.to/subscribe 

• Follow him on X: https://twitter.com/danshipper 

  
  

Timestamps for Spotify:

1. Introduction: 00:02:00

2. Why there should be a nation-wide framework to regulate AI: 00:04:31

3. How 61,000 state employees in New Jersey are adopting AI: 00:10:34

4. Why new tech is key to transforming government services: 00:12:20

5. The Governor is bringing startups back to New Jersey: 00:17:30

6. How to stimulate innovation at scale: 00:25:28

7. The Governor is making New Jersey a top choice for the best talent: 00:33:07

8. Balancing technological progress while ensuring the workforce isn’t left behind: 00:36:56

9. We’re moving toward an “allocation economy”: 00:41:39

10. The Governor’s take on international regulation of AI: 00:43:43

Links to resources mentioned in the episode:

• Governor Phil Murphy: @GovMurphy

• More about the New Jersey AI Hub: https://njaihub.org/ 

Steve Schlafman is using a $20 ChatGPT subscription to expand his consciousness.

He’s doing this through:

• Advanced dream work—Steve records himself talking about his dreams every morning, uploads the transcript to ChatGPT, and prompts the LLM to analyze it like a Jungian dream analyst would. The model pulls out archetypes and hidden emotions that he would’ve been oblivious to.

• Creating living records of meaningful experiences—Instead of losing key insights from therapy or coaching, Steve uses the LLM to highlight emotional patterns, pick out recurring symbols, and build a personal growth timeline.

• Leaning into voice interfaces—Diagnosed with ADD as a child, Steve often lost track of ideas because his brain processed information faster than he could type or write it out. AI voice interfaces free him to process information in a way that’s more natural to him.

Steve is a former VC-turned-executive coach and the founder of Downshift, the “decelerator” for founders and executives. If you think this episode is too “woo” for your liking, Steve argues that you might be over-indexing on just one way of experiencing the world. 

We see the world through four windows: thinking, sensing, feeling, and imagining—and according to him, the last two are often ignored. So if your rational mind has always run the show, Steve invites you to let your feelings and imagination take the lead.

This is a must watch for anyone interested in using AI to understand themselves better—and grow.  

If you found this episode interesting, please like, subscribe, comment, and share! 

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1. Introduction: 00:01:07

2. The power of treating your startup as an evolving entity: 00:03:00

3. Building a business as a means of self-expression: 00:05:27

4. Prompting ChatGPT to do Jungian dream work: 00:17:45

5. Why you should listen to this episode, especially if it feels too “woo’” for you: 00:21:44

6. Visualizing Steve’s dream with ChatGPT: 00:36:31

7. Creating living records of meaning experiences with AI: 00:47:38

8. If you tend to think faster than you can type, lean into voice interfaces: 00:49:37

9. How Steve writes with AI: 00:52:13

10. How AI will disrupt traditional coaching and therapy: 00:54:03

Our sponsor for this episode is Microsoft. Want seamless collaboration without the cost? Microsoft Teams offers a robust free plan for individuals that delivers unlimited chat, 60-minute video meetings, and file sharing—all within one intuitive workspace that keeps your projects moving forward. Head to https://aka.ms/every to use Teams for free, and experience effortless collaboration, today.

Mike Maples knows how AI startups can beat incumbents with billions of dollars. 

Mike—who wrote early checks to Twitter, Twitch, Okta, and Lyft, and now invests through Floodgate, the fund he cofounded—told me it's not about the smartest model, or raising the most money. 

Startups can win in AI with better strategy.

AI is changing the economics of startups—both how they’re started and how they’re funded. A new breed of companies is emerging, and I invited Mike on the show to talk about how they can best strategize. Last year, Mike co-authored a book called Pattern Breakers, which is essentially a guidebook to why there’s no guidebook to building companies. I really liked it, and my colleague Evan Armstrong reviewed it for Every, so I was glad to have him on. We talk about how shifts in technology create space for smaller players to compete—even with AI giants like OpenAI—and how to capitalize on them.

If you found this episode interesting, please like, subscribe, comment, and share! 

Want even more?

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To hear more from Dan Shipper:

• Subscribe to Every: https://every.to/subscribe 

• Follow him on X: https://twitter.com/danshipper 

  
  

Timestamps for Spotify:

1. Introduction: 00:02:20

2. Innovate the business model, not just the product: 00:06:02

3. How startups can compete against the likes of OpenAI: 00:15:49

4. Mike’s take on DeepSeek: 00:19:34

5. Why the future has always belonged to the tinkerers: 00:21:44

6. How small teams today can make big money: 00:24:03

7. Find niches that incumbents can’t or don’t want to enter: 00:28:55

8. The qualities of the truly AI-native: 00:47:08

9. How AI changes the funding model for software companies: 00:53:46

10. Knowledge work is moving toward systems-level thinking: 00:58:23

Links to resources mentioned in the episode:

• Mike Maple: @m2jr

• The fund Mike confounded, Floodgate: @floodgatefund

• Evan’s piece reviewing Pattern Breakers: "A New Book of the Startup Bible" 

• Dan’s piece on the allocation economy: "The Knowledge Economy Is Over. Welcome to the Allocation Economy." 

Michael Taylor has perfected the art of getting AI to speak in tongues. He’s taught it to mimic the voices of your customers—so you can see how they would respond before you ship.

Michael is the creator of Rally, a market research tool that lets you simulate an audience of AI personas. He built a simulator that lets us A/B test Every’s headlines on an audience that mimics the real Hacker News audience. It’s become a part of my writing workflow, and I love it because you test your assumptions quickly, cheaply, and without any of the risks of putting something out into the world.

Besides Rally, Michael co-authored a book on prompt engineering for O’Reilly, and he writes a column for Every about managing AI tools like you would people. In a past life, he founded a growth marketing agency which he grew to 50 people and sold in 2020. One of the reasons I’m drawn to Michael’s work is because he has a tinkerer’s mindset. He’s always exploring the limits of what a new technology can do, and what he’s into today, everyone else will likely discover six months later. We spent an hour talking about using language models to judge your work, best practices for assessing an AI’s performance, and Michael’s flow inside Cursor. He also demos Rally live on the show, testing three different potential headlines for an Every article.

If you found this episode interesting, please like, subscribe, comment, and share! 

Want even more?

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To hear more from Dan Shipper:

• Subscribe to Every: https://every.to/subscribe 

• Follow him on X: https://twitter.com/danshipper 

  
  

Timestamps:

1. Introduction: 00:01:32

2. AI can simulate human personalities with remarkable precision: 00:04:30

3. How Michael simulated a Hacker News audience: 00:08:15

4. Push AI to be a good judge of your work: 00:15:04

5. Best practices to run evals: 00:19:00

6. How AI compresses years of learning into shorter feedback loops: 00:23:01

7. Why prompt engineering is becoming increasingly important: 00:27:01

8. Adopting a new technology is about risk appetite: 00:44:59

9. Michael demos Rally, his market research tool: 00:47:20

10. The AI tools Michael uses to ship new features: 00:55:03

• Links to resources mentioned in the episode:  

  • 
    
  • Michael Taylor: @hammer_mt

• 
  
• Join the waitlist for Rally, Michael’s synthetic market research tool: https://askrally.com/ 

• 
  
• The book Michael co-authored on prompt engineering: Prompt Engineering for Generative AI 

• 
  
• The column Michael writes for Every: Also True for Humans

• 
  
• Michael’s article on personas of thought: “I Asked 100 AI Agents to Judge an Advertisement”

• 
  
• Michael’s article on building a Hacker News simulator: “I Created a Hacker News Simulator to Reverse-engineer Virality” 
  

Nat Eliason’s career arc is borderline absurd—but it works. 

In the last five years, he ran an SEO agency, got into crypto, made $600,000 from a course on the note-taking toolRoam Research, flipped real estate in Austin for a 6x return, and published abook with Random House. He’s now writing a book of science fiction and running a viralcourse about building apps with AI.

I’ve known Nat for a long time, and I think he knows where the puck is headed better than anyone. He’ll see a new tool or trend, master it, build a business around it, and move on. Nat’s pulled it off with crypto, Roam, real estate—and now AI. His app-building course has over 800 students and racked up $200,000 in pre-sales in one week.

Nat was one of the first guests I had on the podcast and I was delighted to have him on again. We spent an hour talking about how coding with AI is creating new behaviors in programming, Nat’s best practices for using the coding tool Cursor, and his take on the future of writing with AI.

This episode is a must-watch for writers, creators, and anyone interested in the future of product building.

If you found this episode interesting, please like, subscribe, comment, and share! 

Want even more?

Sign up for Every to unlock our ultimate guide to prompting ChatGPT here:https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free.

To hear more from Dan Shipper:

• Subscribe to Every:https://every.to/subscribe 

• Follow him on X:https://twitter.com/danshipper 

  
  

Timestamps:

1. Introduction: 00:01:45
2. The origins of Nat’s viral course on building apps with AI: 00:10:15
3. How coding with AI has evolved over the last two years: 00:17:16
4. Nat creates an app using Composer, Cursor’s AI assistant: 00:20:52
5. Tactical tips for coding with Cursor: 00:24:36
6. How coding with AI is creating new behaviors in programming: 00:27:36
7. What excites Nat the most about the future of AI: 00:31:11
8. A demo of Hubbard, the AI editor Nat built for his science fiction writing: 00:37:28
9. When does it make sense to build custom software: 00:43:22
10. Nat’s take on the future of writing with AI: 00:47:48

Links to resources mentioned in the episode:  

• Nat Eliason: @nateliason

• Nat’s viral course about building apps with AI:Build Your Own Apps with AI

• The book Nat published about crypto:Crypto Confidential: Winning and Losing Millions in the New Frontier of Finance  

• Dan’s piece about how AI empowers creators:AI and the Age of the Individual 

Guillermo Rauch is one of the most prolific coders of this generation. 

But he doesn’t think of himself as a coder anymore. 

Coding, he says, is a specific skill that AI is becoming great at. Instead, he thinks the future of coding is more holistic, full-stack engineers who can ideate, design, and execute all together. 

Guillermo is the founder and CEO of Vercel, the creator of NextJS, and SocketIO. We spent an hour talking about the future of software development in an AI world—and the meta-skills that are essential for the coders of today to master—in order to use tomorrow’s tools to their fullest extent.

Here are a few takeaways:

If you found this episode interesting, please like, subscribe, comment, and share! 

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To hear more from Dan Shipper:

Timestamps:

Links to resources mentioned in the episode:  

AGI is coming. Reid Hoffman just wrote the book on how to prepare.

According to Reid, every major tech breakthrough (the written word, the printing press, the telephone) triggered mass fear. But, contrary to our worries, new technology tends to enhance human agency—even more so, if you know how to use it well.

Reid is the cofounder of LinkedIn, Inflection AI, and Manas AI; a partner at venture capital firm Greylock Partners; an early backer and board member of OpenAI; and an award-winning podcaster

We spent an hour talking about how to develop a compass for navigating AGI. Here are a few takeaways:

Our sense of human agency is not just about external control but an internal stance—how we approach uncertainty & new tech is crucial

In new technology waves, NO blueprint or plan will have the right answers. Instead, adapting to new technology requires broad access, an experimental mindset, and flexibility

In an AGI world most jobs will transform, not disappear—and how you can prepare with hands-on trial and error

How certain social norms and ethics should change as AGI changes the landscape—like individual access to personal data 

Why now may be finally be the era where quantified self tools become valuable

…and more, including everything in his new book Superagency, out this week. 

It was a pleasure to have him on the show for a second time. This is a must-watch for anyone who wants to help build a more human future with AI.

If you found this episode interesting, please like, subscribe, comment, and share! 

Want even more?

Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free.

To hear more from Dan Shipper:

Subscribe to Every: https://every.to/subscribe 

Follow him on X: https://twitter.com/danshipper 

Timestamps:

Introduction: 00:01:29

Patterns in how we’ve historically adopted technology: 00:02:50

Why humans have typically been fearful of new technologies: 00:07:02

How Reid developed his own sense of agency: 00:13:25

The way Reid thinks about making investment decisions: 00:20:08

AI as a “techno-humanist” compass: 00:29:40

How to prepare yourself for the way AI will change knowledge work: 00:35:30

Why equitable access to AI is important: 00:41:39

Reid’s take on why private commons will be beneficial for society: 00:45:15

 How AI is making Silicon Valley’s conception of the “quantified self” a reality: 00:47:23

The shift from symbolic to sub-symbolic AI mirrors how we understand intelligence: 00:52:14

Reid’s new book, Superagency: 01:03:29

Links to resources mentioned in the episode:  

Reid Hoffman: @reidhoffman

Superagency, Reid’s newest book:

Nabeel Hyatt is looking for the “Japanese toilets” of AI—products that delight users in unexpected ways.

As a partner at Spark Capital, that investment philosophy has paid off. Despite making only 1-2 investments a year, he’s picked some of the biggest winners in AI so far: Descript, Cruise, and Granola.

We spent an hour unpacking: 

How much “leash” top products give to AI agents—and why that matters

How he spots remarkable AI products

Why “sensitivity” is one of the most important traits of top founders

The huge opportunities for AI products to help users explore new “possibility spaces”

How Nabeel is actually using AI tools like ChatGPT, Claude, and AI code editor Windsurf in his life 

If you found this episode interesting, please like, subscribe, comment, and share! 

Want even more?

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To hear more from Dan Shipper:

Subscribe to Every: https://every.to/subscribe 

Follow him on X: https://twitter.com/danshipper 

Timestamps:

Introduction: 00:01:32

Why Nabeel doesn’t invest in more than two companies per year: 00:01:50

Why the words you use to describe your business matter: 00:06:49

What a product with soul looks like: 00:13:45

Patterns in the remarkable founders Nabeel has invested in: 00:16:48

How Nabeel evaluates popular coding agents: 00:24:12 

AI has broadened the horizons of what Nabeel can do: 00:32:29

How funding models are changing as AI makes it cheaper to build software: 00:36:28

Nabeel’s framework for when to trust an LLM: 00:45:43

 Guide AI to provide context (and not just quick answers): 00:55:39

Links to resources mentioned in the episode:  

Nabeel Hyatt: @nabeel, https://nabeelhyatt.com/ 

Spark Capital: https://www.sparkcapital.com/ 

The piece Chris Pedregal wrote for Every: How to Build a Truly Useful AI Product 

Chris Pedregal on AI & I: 🎧 The Secret to Building Sticky AI Products 

The AI tools Nabeel talks about: Windsurf, Wordware