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
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."
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.
In Superagency, his book that was released yesterday, Reid examines how we’ve historically adopted new technologies and focuses on AI’s potential to increase our agency—the ability to make decisions that affect outcomes. He wrote the book for two audiences: anyone who is curious, or even skeptical, about AI; and technologists who are building in AI, with the hope that they will think about human agency as a design principle for their products. As someone who straddles both worlds, I read the book and really liked it.
Beyond being a prolific author, 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—and I was pleased to invite him onto AI & I again, this time in person.
We recorded an hour-long conversation, going deep on:
It’s 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. 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:
Reid Hoffman: @reidhoffman
Superagency, Reid’s newest book: https://www.superagency.ai/
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:
As a general partner at Spark Capital, Nabeel Hyatt backs just one or two companies each year.
But when he does invest, Nabeel picks winners. He was an early investor in Discord, video editor Descript, self-driving startup Cruise (acquired by General Motor for over $1 billion), and, recently, AI note-taking app Granola.
Nabeel’s investment thesis is to look for products like the Japanese toilet.
Don’t fret—Spark Capital hasn’t pivoted into the sanitaryware industry. Nabeel isn’t looking for startups that are disrupting plumbing.
Rather, just like Japanese toilets, he’s looking for products that delight users with new experiences they didn’t know they wanted—and if his past investments are anything to go by, Nabeel has a good eye for that.
On my recent trip to San Francisco, I sat down with Nabeel to talk about the qualities shared by remarkable products and the founders that build them, why he chooses not to invest in more than a couple of startups a year, and how he’s actually using AI in his daily life. Nabeel is one of my favorite people in AI, and this is one of my favorite recent conversations. It’s a must watch for founders who want to build useful AI products with soul.
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:
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
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?
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
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
Building an email client used to take many years and millions of dollars.
But Every’s Kieran Klaassen built Cora—a totally new way to manage your inbox with AI—in just 3 months. He even shipped the original MVP of the product in a single day—something that just wasn’t possible before the current state of generative AI.
Now, there are almost 10,000 people on the waitlist for Cora, and we’re onboarding new users every single day.
Every’s head of Studio Brandon Gell and I worked closely with Kieran as he built Cora, and to kick off my podcast, AI and I, in 2025, I invited both of them on the show to talk about it. We go behind the scenes, getting into how Kieran built the product with Cursor, o1, and o1 Pro, what we’re learning as we onboard new users every day, and the future of Cora and of Every as a multi-modal media company.
This is a must watch for anyone curious about our approach to building with AI at Every.
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:
Sign up for the Cora waitlist: https://cora.computer/
Learn more about Cora: Introducing Cora: Manage Your Inbox With AI
Kieran Klaassen: @kieranklaassen
Brandon Gell: @bran_don_gell
Building an email client used to take many years and millions of dollars.
But Every’s Kieran Klaassen built Cora—a totally new way to manage your inbox with AI—in just 3 months. He even shipped the original MVP of the product in a single day—something that just wasn’t possible before the current state of generative AI.
Now, there are almost 10,000 people on the waitlist for Cora, and we’re onboarding new users every single day.
Every’s head of Studio Brandon Gell and I worked closely with Kieran as he built Cora, and to kick off my podcast, AI and I, in 2025, I invited both of them on the show to talk about it. We go behind the scenes, getting into:
How Kieran built the product with Cursor, o1, and o1 Pro
What we’re learning as we onboard new users every day
The future of Cora and of Every as a multi-modal media company
This is a must watch for anyone curious about our approach to building with AI at Every.
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: 00:01:56
How the maker of Cora describes the product: 00:02:33
Our first mistake while building Cora: 00:06:31
The story of how Kieran shipped the first MVP overnight: 00:09:37
Why Dan believes software is becoming content: 00:13:44
Products with a point of view will win: 00:16:40
How Kieran approaches building a new product: 00:19:16
Best practices while using Cursor: 00:31:55
Hacking together a copy editor in Cursor live on the show: 00:41:05
The future of Cora, and the hardest challenge we face today: 00:53:58
AI is going to change science forever.
Small scale studies will give way to large scale open data gathering efforts. We’ll shift from seeking broad general theories to making contextual predictions in individual cases. The traditional research paper will change fundamentally.
That’s why I had Alice Albrecht on the show. Few people straddle the worlds of science and AI like she does: She holds a Ph.D. in cognitive neuroscience from Yale and is a machine learning researcher with almost a decade of experience. In 2021, she founded re:collect, an app that aimed to augment human intelligence with AI. It was acqui-hired by news curation app SmartNews in September of this year, and she is now the senior director of AI product.
We discuss the contours of this new paradigm of science: the growing importance of data in scientific discovery, how AI makes N-of-1 studies imperative—when they’re normally seen as unscientific, the case for big tech to open-source their data for research, and the power of unbundling data from interpretations, in both science and media. Here is a link to the episode transcript.
In January of this year, we published Alice’s thesis about how augmenting human intelligence with AI is more effective than attempting to achieve super intelligence through standalone AI systems, and in a happy coincidence, she’s our last podcast guest of 2024. Thank you for listening, and we’ll see you in the new year.
In the meantime, this is a must-watch for anyone interested in how AI is changing the future of scientific research.
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:
Alice Albrecht: @AliceAlbrecht
The company that recently acquired Alice’s startup: SmartNews
The piece Alice wrote for Every about how AI can augment human intelligence: The Case for Cyborgs
Every’s product incubations that we discuss in the context of how AI is changing media: Extendable Articles, TLDR
AI is going to change science forever. Small scale studies will give way to large scale open data gathering efforts. We’ll shift from seeking broad general theories to making contextual predictions in individual cases. The traditional research paper will change fundamentally. That’s why I had Alice Albrecht on the show. Few people straddle the worlds of science and AI like she does: She holds a Ph.D. in cognitive neuroscience from Yale and is a machine learning researcher with almost a decade of experience. Her startup re:collect built an app to augment human intelligence with AI and was acqui-hired by SmartNews earlier this year. She now heads up AI product there. We get into the contours of this new paradigm in science: - Whether research papers are still the best format to “release” science in - The increasing importance of data in scientific discovery - Why AI is making N-of-1 studies imperative—when they’re normally seen as unscientific - The case for big tech to open-source their data for scientific research - The power of unbundling data and interpretations, in science and media This is a must-watch for anyone interested in how AI is changing the future of scientific research. 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: (00:00:59)
Everything Alice learned about growing an AI startup: (00:04:50)
Alice’s thesis about how AI can augment human intelligence: (00:09:08)
Whether chat is the best way for humans to interface with AI: (00:12:47)
Ideas to build an AI model that predicts OCD symptoms: (00:23:55)
Why Alice thinks LLMs aren’t the right models to do predictive work: (00:37:12)
How AI is broadening the horizons of science: (00:38:39)
The new format in which science will be released: (00:40:14)
Why AI makes N-of-1 studies more relevant: (00:45:39)
The power of separating data from interpretations: (00:50:42)
Links to resources mentioned in the episode:
Alice Albrecht: @AliceAlbrecht
The company that recently acquired Alice’s startup: SmartNews
The piece Alice wrote for Every about how AI can augment human intelligence: The Case for Cyborgs
Every’s product incubations that we discuss in the context of how AI is changing media: Extendable Articles, TLDR
Chris Pedregal knows how to build AI products that people love.
Chris is the cofounder and CEO of Granola, an AI-powered notepad for meetings. We use it for many of our meetings at Every—the app listens in on the conversation, transcribes it in the background, and when the meeting ends, creates automated notes and a shareable transcript for anyone who missed it. If you take notes during the meeting, Granola polishes them to be more organized and complete.
Granola is one of my favorite consumer AI products because it’s equal parts delightful and useful. It’s not a bland chat interface. It’s not an over-the-top demo that you wouldn’t use more than once. Granola is a product with “soul,” imbued with the team’s vision for how AI can work alongside you to turn discursive conversations into clear insights. And I’m not the only one who thinks so—since Granola’s launch in May 2024, its user base has grown by 5x, with around 5,000 weekly active users, and half the people who try the app still use it 10 weeks later for an average of six meetings a week. The company also recently raised a $20 million Series A.
Granola has the marks of being built by a thoughtful, intentional team, which is why I was excited to have Chris on the show. We spent an hour talking about Chris’s product development philosophy, the role of intuition in making products with “soul” and how he balances this with user feedback, how you can become a better product thinker, and the kinds of consumer AI startups Chris thinks will succeed. Here is a link to the episode transcript.
This is a must-watch for anyone interested in building valuable, sticky AI products that users will love.
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:
Chris Pedregal: @cjpedregal
Granola: http://Granola.ai, @meetgranola
The piece Chris wrote for Every about building useful AI products: https://every.to/thesis/how-to-build-a-truly-useful-ai-product
Our TOPPODCAST Picks 
