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 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!
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To hear more from Dan Shipper:
Subscribe to Every: https://every.to/subscribe
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Timestamps:
Introduction: 00:01:29
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:
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1:09:23
The Venture Capitalist Who Finds the Best AI Products—Before They Win - Ep. 45 with Nabeel Hyatt
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
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1:01:35
An Inside Look at Building an Email Client in 3 Months - Ep. 44 with Kieran Klaassen, Brandon 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
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1:15:21
How AI Will Change Science Forever - Ep. 43 with Alice Albrecht
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
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1:00:02
The Secret to Building Sticky AI Products - Ep. 42 with Chris Pedregal
Chris Pedregal knows how to build AI products that people love.
Chris is the cofounder and CEO of Granola, an AI notepad for meetings. We use it all the time at Every—Granola listens in on a meeting and, when it ends, generates notes and a shareable transcript for anyone who missed it.
Granola is one of my favorite consumer AI products because it’s equal parts delightful and useful. So my question for Chris was:
How do you do it? How do you make an excellent product in AI?
We spent an hour talking about:
How Chris uses intuition while making product decisions
The importance of building products with “soul”
How to develop your product thinking muscles
When Chris trusts his gut over listening to user feedback
How fewer users gives startups a leg up over big tech
Why Chris is bullish on founders building specialized AI tools for professionals
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 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 (00:00:48)
How Chris made early product decisions at Granola (00:09:14)
Chris’s philosophy around product development (00:13:36)
When to follow your intuition v. listen to your users (00:19:24)
How to build a product with “soul” (00:20:40)
Chris’s advice on becoming a better product thinker (00:25:12)
The role travel plays in shaping Chris’s intuition (00:31:17)
Why having fewer users is an advantage for AI startups (00:45:52)
Why Chris is bullish on startups building specialized AI tools (00:52:09)
Where Chris sees Granola in the next year (00:56:52)
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
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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