Stay ConnectedThe Every Podcast is Every’s flagship show. Co-hosts Dan Shipper and Natalia Quintero talk with founders, researchers, writers, and operators about what they’re building and how they use AI in their own work. The show also takes you behind the scenes at Every. We share how our team is using and exploring AI, including what we’re trying, what’s working, and what we’re learning along the way.
Formerly known as AI & I.
Read more at every.to.
Copyright: © Dan Shipper
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.
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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:
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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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:
Timestamps:
Links to resources mentioned in the episode:
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."
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:
Timestamps:
Links to resources mentioned in the episode:
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:
Timestamps:
Links to resources mentioned in the episode:
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: 00:01:32
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!
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:
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
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 tool Roam Research, flipped real estate in Austin for a 6x return, and published a book with Random House. He’s now writing a book of science fiction and running a viral course 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:
Timestamps:
Links to resources mentioned in the episode:
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!
Want even more?
Sign up for Every to unlock our 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
Links to resources mentioned in the episode:
Guillermo Rauch: @rauchg
Vercel: https://vercel.com/
Last week’s 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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