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...
How AI Startups Can Win With Better Strategy - Ep. 50 with Mike Maples
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: 00:02:20Innovate the business model, not just the product: 00:06:02How startups can compete against the likes of OpenAI: 00:15:49Mike’s take on DeepSeek: 00:19:34Why the future has always belonged to the tinkerers: 00:21:44How small teams today can make big money: 00:24:03Find niches that incumbents can’t or don’t want to enter: 00:28:55The qualities of the truly AI-native: 00:47:08How AI changes the funding model for software companies: 00:53:46Knowledge work is moving toward systems-level thinking: 00:58:23Links to resources mentioned in the episode:Mike Maple: @m2jrThe fund Mike confounded, Floodgate: @floodgatefundEvan’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."
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1:02:51
He Built an AI Audience Simulator. It’s the Future of Customer Research. - Ep. 49 with Michael Taylor
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?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: 00:01:32AI can simulate human personalities with remarkable precision: 00:04:30How Michael simulated a Hacker News audience: 00:08:15Push AI to be a good judge of your work: 00:15:04Best practices to run evals: 00:19:00How AI compresses years of learning into shorter feedback loops: 00:23:01Why prompt engineering is becoming increasingly important: 00:27:01Adopting a new technology is about risk appetite: 00:44:59Michael demos Rally, his market research tool: 00:47:20The AI tools Michael uses to ship new features: 00:55:03Links to resources mentioned in the episode: Michael Taylor: @hammer_mtJoin 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 HumansMichael’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”
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1:06:34
How Nat Eliason Made $200,000 in a Week Teaching AI - Ep. 48
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:Introduction: 00:01:45The origins of Nat’s viral course on building apps with AI: 00:10:15How coding with AI has evolved over the last two years: 00:17:16Nat creates an app using Composer, Cursor’s AI assistant: 00:20:52Tactical tips for coding with Cursor: 00:24:36How coding with AI is creating new behaviors in programming: 00:27:36What excites Nat the most about the future of AI: 00:31:11A demo of Hubbard, the AI editor Nat built for his science fiction writing: 00:37:28When does it make sense to build custom software: 00:43:22Nat’s take on the future of writing with AI: 00:47:48Links to resources mentioned in the episode: Nat Eliason: @nateliasonNat’s viral course about building apps with AI:Build Your Own Apps with AIThe 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
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59:22
Vercel’s Guillermo Rauch on What Comes After Coding - Ep. 47
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.
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: 00:01:33
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."
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56:15
How to Prepare for AGI According to Reid Hoffman - Ep. 46
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:
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.
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