Learn how the smartest people in the world are using AI to think, create, and relate. Each week I interview founders, filmmakers, writers, investors, and others about how they use AI tools like ChatGPT, Claude, and Midjourney in their work and in their lives. We screen-share through their historical chats and then experiment with AI live on the show. Join us to discover how AI is changing how we think about our world—and ourselves. For more essays, interviews, and experiments at the forefront of AI: https://every.to/chain-of-thought?sort=newest.
Kevin Kelly has spent more time thinking about the future than almost anyone else.
From VR in the 1980s to the blockchain in the 2000s—and now generative AI—Kevin has spent a lifetime journeying to the frontiers of technology, only to return with rich stories about what’s next.
Today, as Wired's senior maverick, his project for 2025 is to outline what the next century looks like in a world shaped by new technologies like AI and genetic engineering.
He’s a personal hero of mine—not to mention a fellow Annie Dillard fan—and it was a privilege to have him on the show. We get into:
How you can predict the future. According to Kevin, the draw of new frontiers—from the first edition of Burning Man and remote corners of Asia, to the early days of the internet and AI—isn’t staying at the edge forever; it's returning with a story to tell.
Why history is so important to help you understand the future To stay grounded while exploring what’s new, Kevin balances the thrill of the future with the wisdom of the past. He pairs AI research with reading about history, and playing with an AI tool by retreating to his workshop to make something with his hands.
From 1,000 true fans to an audience of one. Rather than creating for an audience, Kevin has been using LLMs to explore his own imagination. After realizing that da Vinci, Martin Luther, and Columbus were alive at the same time, he asked ChatGPT to imagine them snowed in at a hotel together, and the prompt spiraled into an epic saga, co-written with AI. But he has no plans to publish it because the joy was in creating something just for himself.
What the history of electricity can teach us about AI. Kevin draws a parallel between AI and the early days of electricity. We could produce electric sparks long before we understood the forces that created them, and now we’re building intelligent machines without really understanding what intelligence is.
Why Kevin sees intelligence as a mosaic—not a monolith. Kevin believes intelligence isn’t a single force, but a compound of many cognitive elements. He draws from Marvin Minsky’s “society of mind”—the theory that the mind is made up of smaller agents working together—and sees echoes of this in the Mixture of Experts architecture used in some models today.
Your competitive advantage is being yourself. Don’t aim to be the best—aim to be the only. Kevin realized the stories no one else at Wired wanted to write were often the ones he was suited for, and trusting that instinct led to some of his best work.
This is a must-watch for anyone who wants to make sense of AI through the lens of history, learn how to spot the future before it arrives, or grew up reading Wired.
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Timestamps:
Introduction: 00:00:50
Why Kevin and I love Annie Dillard: 00:01:10
Learn how to predict the future like Kevin: 00:12:50
What the history of electricity can teach us about AI: 00:16:08
How Kevin thinks about the nature of intelligence: 00:20:11
Kevin’s advice on discovering your competitive advantage: 00:27:21
The story of how Kevin assembled a bench of star writers for Wired: 00:31:07
How Kevin used ChatGPT to co-create a book: 00:36:17
Using AI as a mirror for your mind: 00:40:45
What Kevin learned from betting on VR in the 1980s: 00:45:16
Links to resources mentioned:
Kevin Kelly: @kevin2kelly
Kelly’s books: https://kk.org/books
Annie Dillard books that Kelly and Dan discuss: Pilgrim at Tinker Creek, Teaching a Stone to Talk, Holy the Firm, The Writing Life
Dillard’s account of the total eclipse: "Total Eclipse"
500K people are confiding in an AI alien—and it's on track to generate $4M this year.
It’s called a Tolan: an animated AI character that can talk to you like your best friend. The company behind it, Portola, has 4x’d their ARR in the last month from viral growth on TikTok and Instagram.
Tolan isn’t just a hyper-growth startup—they’re also exploring AI as a completely new creative tool, and storytelling medium. Their goal is to help their users go from overwhelmed to grounded, and it’s working.
Today, on AI & I, I sit down with two of the minds behind Tolans:
My good friend Quinten Farmer, Portola’s cofounder and CEO, and Eliot Peper, their head of story and a best-selling science fiction novelist. We get into:
How to build AI personalities users love. During user onboarding, the team gathers information—through a light-touch personality quiz—and then uses frameworks like the Big Five and Myers-Briggs to shape a Tolan that mirrors the user; like an older sibling might. The aim is to create someone who feels familiar enough to be safe, but different enough to be interesting.
Why AI characters are “improv actors”. Rather than scripting detailed prompts, the team trains Tolans to improvise—inspired by Keith Johnstone’s book Impro, where he talks about building strong narratives through free association and recombination.
How “memory” is critical to developing compelling characters. Tolans develop their personalities through “situations”: small narrative setups (a memory, a joke, an embarrassing moment) the Tolan reacts to, remembers, and gradually weaves into its character; accumulating into something that feels like a real lived experience.
Why response time is everything for voice AI interactions. A Tolan has at most two seconds to curate the right context about a user and deliver a reply that feels genuine—the team has found that even half a second slower can break the user’s immersive interaction with the AI.
The future of AI as a totally new creative medium. New technologies bring about new formats and new mediums. AI creates the opportunity for creatives to tell completely new kinds of stories—if they’re brave enough to try it.
“White mirror” technologies that make you feel more like yourself. Amid concerns that tech drives polarization and isolation, Tolan offers a counterexample: a tool designed to make the best of what humanity knows about being a flourishing individual available on demand. The company’s north star is helping users go from feeling overwhelmed to feeling grounded.
This is a must-watch for anyone exploring AI as a creative medium—or curious about the future of human-AI relationships.
If you found this episode interesting, please like, subscribe, comment, and share!
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To hear more from Dan Shipper:
Subscribe to Every: https://every.to/subscribe
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Timestamps:
Introduction: 00:01:30
Talking to the Portola CEO’s Tolan, Clarence: 00:04:07
How Portola went from building software for kids to AI companions: 00:09:11
Why response time is everything for voice-based AI interfaces: 00:23:40
Tolans don’t use scripted prompts—they’re taught to improvise: 00:29:54
How to know which AI personalities your users will click with: 00:37:23
Developing the character traits of an AI companion: 00:42:27
What does it mean to build technology that makes us flourish: 00:49:48
How Portola evaluates whether Tolans are resonating with users: 01:01:10
Inside Portola’s viral growth strategy: 01:11:01
Links to resources mentioned in the episode:
Quinten Farmer: @quintendf
Eliot Peper: @eliotpeper
Make your own Tolan: https://www.tolans.com/
Keith Johnston’s book about improvisation: Impro
Stephen King’s book about writing: On Writing
This episode is sponsored by Vanta. Achieving SOC 2 compliance can help you win bigger deals, enter new markets, and deepen trust with your customers—but it can cost you real time and money. Vanta automates up to 90% of the work for SOC 2, ISO 27001, and more, getting you audit-ready in weeks instead of months and saving you up to 90% of associated costs—and Every listeners can get $1,000 off of Vanta at https://www.vanta.com/every.
Lucas Crespo is the mastermind behind Every's visual vibe—and he does it one prompt at a time.
As our creative lead, Lucas uses tools like native image gen in ChatGPT and Midjourney to generate the cover images you see every day. He also designs the interfaces for our products—Cora, Spiral, and Sparkle—and makes everything on our site feel as thoughtful and delightful as possible.
We get into:
Why Every’s aesthetic feels familiar and new at the same time. Every’s aesthetic plays with the tension between the old (like Greek statues and Baroque symbols) and the new (like saturated colors and modern motifs) to make the glamor of the past feel fresh.
Art direction matters more than ever today. As AI makes it easier to generate images, Lucas says the real work of design is shifting toward art direction, specifically, curating an aesthetic that feels “organic;” on his X timeline that’s showing up as clouds, earthy landscapes, and textures.
Reimagining what a website can be with AI. Lucas compares most websites to identical buildings—predictable, efficient, and forgettable—and wonders how AI can help us break that mold by designing experiences that prioritize serendipity over speed, and curiosity over control.
Behind the scenes of Cora’s visual aesthetic. How Lucas designed the landing page and launch video for Cora by rooting it in the product’s philosophy: turning the inbox from a source of chaos into something that feels calm, thoughtful—like stepping into spring.
The future of internet interfaces. Lucas believes the future of digital interfaces will be curated with the same care as a film set or ad campaign, where every detail is chosen with intention.
Lucas also walks us through how he created the headline image for Every’s consulting page—a human and robotic hand fist-bumping—using Midjourney to iterate from rough prompt to polished visual.
This is a must watch for anyone interested in the future of design and making the internet a little more beautiful every day.
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:
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Timestamps:
Introduction: 00:01:41
How AI changed the course of Lucas’s career: 00:04:02
Why Every’s aesthetic feels both familiar and fresh: 00:08:00
Why Lucas thinks minimalism is overrated: 00:14:53
Art direction matters more than ever in the age of AI: 00:20:38
How to reimagine what a website can be with AI: 00:23:42
Lucas’s process in Midjourney to generate cover images: 00:33:08
Midjourney v. image generation in ChatGPT: 00:42:30
Behind the scenes of Cora’s design language: 00:49:07
How AI is rewriting the role of a designer: 00:59:18
Links to resources mentioned in the episode:
Lucas Crespo: @lucas__crespo
The pieces Lucas has written for Every: “When An AI Tool Finally Gets You”, “A Definitive Guide to Using Midjourney”
Dan’s piece on the allocation economy: “The Knowledge Economy Is Over. Welcome to the Allocation Economy”
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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:
Introduction: 00:01:18
Science can deepen your sense of the spiritual: 00:02:36
The nature of consciousness: 00:11:31
AI might appear to be conscious, but it isn’t: 00:13:11
Why AI can be considered to be “natural”: 00:19:50
AI shifts the focus of science from explanations to predictions: 00:30:40
How modern neural networks simulate thinking: 00:33:48
Lightman’s vision for how humans and machines will merge: 00:39:38
Does AI know more about love than you?: 00:43:11
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?
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: 00:01:31
Dan and Jonny’s approach to running non-traditional businesses: 00:02:18
How Jonny uses ChatGPT to deepen his meditation practice: 00:12:04
Jonny uses AI to research a theory of how trauma is stored in our bodies: 00:25:44
Dan’s theory around how AI is changing science: 00:31:28
Jonny’s method to build personalized AI coaches: 00:32:35
How Jonny used OpenAI’s deep research to plan a move to Costa Rica: 00:47:07
Dan is developing an app that can predict his OCD symptoms: 00:52:50
AI makes the idea of a “quantified self” useful: 00:55:42
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:
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Timestamps for Spotify:
Introduction: 00:02:00
Why there should be a nation-wide framework to regulate AI: 00:04:31
How 61,000 state employees in New Jersey are adopting AI: 00:10:34
Why new tech is key to transforming government services: 00:12:20
The Governor is bringing startups back to New Jersey: 00:17:30
How to stimulate innovation at scale: 00:25:28
The Governor is making New Jersey a top choice for the best talent: 00:33:07
Balancing technological progress while ensuring the workforce isn’t left behind: 00:36:56
We’re moving toward an “allocation economy”: 00:41:39
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!
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
Introduction: 00:01:07
The power of treating your startup as an evolving entity: 00:03:00
Building a business as a means of self-expression: 00:05:27
Prompting ChatGPT to do Jungian dream work: 00:17:45
Why you should listen to this episode, especially if it feels too “woo’” for you: 00:21:44
Visualizing Steve’s dream with ChatGPT: 00:36:31
Creating living records of meaning experiences with AI: 00:47:38
If you tend to think faster than you can type, lean into voice interfaces: 00:49:37
How Steve writes with AI: 00:52:13
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?
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 for Spotify:
Introduction: 00:02:20
Innovate the business model, not just the product: 00:06:02
How startups can compete against the likes of OpenAI: 00:15:49
Mike’s take on DeepSeek: 00:19:34
Why the future has always belonged to the tinkerers: 00:21:44
How small teams today can make big money: 00:24:03
Find niches that incumbents can’t or don’t want to enter: 00:28:55
The qualities of the truly AI-native: 00:47:08
How AI changes the funding model for software companies: 00:53:46
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:
Introduction: 00:01:32
AI can simulate human personalities with remarkable precision: 00:04:30
How Michael simulated a Hacker News audience: 00:08:15
Push AI to be a good judge of your work: 00:15:04
Best practices to run evals: 00:19:00
How AI compresses years of learning into shorter feedback loops: 00:23:01
Why prompt engineering is becoming increasingly important: 00:27:01
Adopting a new technology is about risk appetite: 00:44:59
Michael demos Rally, his market research tool: 00:47:20
The AI tools Michael uses to ship new features: 00:55:03
Links to resources mentioned in the episode:
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!
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Subscribe to Every:https://every.to/subscribe
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Timestamps:
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:
One of the most important keys to his success is taste—and developing taste is all about paying better attention to everything you experience day to day.
He’s great at recognizing bleeding-edge technologies with extremely practical applications but that have bad user experiences. If you can learn to recognize those and build with them, you might build the next NextJs or SocketIO.
He’s already seeing enterprises use Vercel’s AI coding copilot v0 to replace all of their programming—they just send v0 demos back and forth to iterate on new prototypes.
Why prototype cultures are becoming common in AI—and the benefits of written cultures like Amazon vs. prototype cultures like Apple for different kinds of companies.
For developers building frameworks, always put the product first; a framework in isolation without a “customer zero” is never going to be a good tool.
The theory of “recursive founder mode”—if you want to build a scalable business, you have to scale yourself by creating an atmosphere that nurtures talent and ambition.
AI tools are shifting software toward consumption-based billing models, making us capital allocators who decide how much compute the AI consumes.
The future of AI is agents with the taste, knowledge, and tools to perform specialized tasks.
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Timestamps:
Introduction: 00:01:33
How to spot trends early: 00:03:18
Why you should be your own customer: 00:07:34
How to create an ecosystem of talent and ambition: 00:14:55
Why Guillermo doesn't identify as a coder: 00:17:29
AI is gearing us toward an allocation economy: 00:20:50
How Vercel’s copilot compares with other coding agents: 00:28:34
Guillermo’s advice on having better taste: 00:40:35
The future of AI agents is specialized: 00:42:46
How AI startups can compete with big tech: 00:47:50
Links to resources mentioned in the episode:
Guillermo Rauch: @rauchg
Vercel: https://vercel.com/
Our episode with Nabeel Hyatt: "🎧 The Venture Capitalist Who Finds the Best AI Products—Before They Win"
Dan’s essay about the allocation economy: "The Knowledge Economy Is Over. Welcome to the Allocation Economy."