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
This episode is sponsored by Command Bar, an embedded AI copilot designed to improve user experience on your web or mobile site. Find them here: https://www.commandbar.com/copilot/ Dwarkesh Patel is on a quest to know everything. He’s using LLMs to enhance how he reads, learns, thinks, and conducts interviews. Dwarkesh is a podcaster who’s interviewed a wide range of people, like Mark Zuckerberg, Tony Blair, and Marc Andreesen. Before conducting each of these interviews, Dwarkesh learns as much as he can about his guest and their area of expertise—AI hardware, tense geopolitical crises, and the genetics of human origins, to name a few. The most important tool in his learning arsenal? AI—specifically Claude, Claude Projects, and a few custom tools he’s built to accelerate his workflow. He does this by researching extensively, and as his knowledge grows, each piece of new information builds upon the last, making it easier and easier to grasp meaningful insights. In this interview, I turn the tables on him to understand how the prolific podcaster uses AI to become a smarter version of himself. We get into: - How he uses LLMs to remember everything - His podcast prep workflow with Claude to understand complex topics - Why it’s important to be an early adopter of technology - His taste in books and how he uses LLMs to learn from them - How he thinks about building a worldview - His quick takes on the AI’s existential questions—AGI and P(doom) We also use Claude live on the show to help Dwarkesh research for an upcoming podcast recording. This is a must-watch for curious people who want to use AI to become smarter. 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. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: - Subscribe to Every - Follow him on X Timestamps: 00:00:00 - Teaser 00:01:44 - Introduction 00:05:37 - How Dwarkesh uses LLMs to remember everything 00:11:50 - Dwarkesh's taste in books and how he uses AI to learn from them 00:17:58 - Why it's important to be an early adopter of technology 00:20:44 - How Dwarkesh uses Claude to understand complex concepts 00:26:36 - Dwarkesh on how you can compound your intelligence 00:28:21 - Why Dwarkesh is on a quest to know everything 00:39:19 - Dan and Dwarkesh prep for an upcoming interview 01:04:14 - How Dwarkesh uses AI for post-production of his podcast 01:08:51 - Rapid fire on AI's biggest questions—AGI and P(doom) Links to resources mentioned in the episode: - Dwarkesh Patel - Dwarkesh’s podcast and newsletter - Dwarkesh’s interview with researcher Andy Matuschak on spaced repetition - The book about technology and society that both Dan and Dwarkesh are reading: Medieval Technology and Social Change - Dan’s interview with Reid Hoffman - The book by Will Durant that inspires Dwarkesh: Fallen Leaves - One of the most interesting books Dwarkesh has read: The Great Divide - Upcoming guests on Dwarkesh’s podcast: David Reich and Daniel Yergin
Steph Smith is the ultimate internet explorer. I spent an hour talking to her about the future of creating on the internet in the age of AI. She’s our first-ever repeat guest, and if you watch the episode you’ll see why: It’s a curious, fun, experimental romp through the best of the digital world. We try out four underrated AI products, go through a list of Steph’s favorite niche internet creators, and follow her creative process in Midjourney in granular detail. We had a wide-ranging discussion about:
If you don’t know her, Steph is the host of the @a16z podcast and the creator behind Internet Pipes, a toolkit to surface useful insights on the internet, and many other cool internet projects. This is a must-watch if you make things on the internet and are interested in how AI is changing what it means to be a creator—and how creator businesses work. 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: 00:00:00 - Teaser 00:00:46 - Introduction 00:09:08 - How Steph uses Midjourney to find her aesthetic 00:20:45 - Steph predicts how creating on the internet will evolve with AI 00:32:51 - Rapid-fire rundown of Steph's favorite niche creators 00:42:58 - How Steph trains her brain on better data 00:48:19 - The AI research tool Steph uses for health information 00:56:25 - The future of AI tools—and one of Steph's top picks 01:01:20 - Dan and Steph use AI to create a simulation of the internet 01:05:09 - How LLM hallucinations can be useful 01:12:06 - Dan and Steph make a song about what they learned on the show Links to resources mentioned in the episode: Steph Smith: https://twitter.com/stephsmithio Internet Pipes: https://internetpipes.com/ Doing Content Right: https://doingcontentright.com/#features A few of Steph’s favorite niche creators: India Rose Crawford, Blackforager, David Zinn, David Bird, WatchMaggiePaint The podcast episode Dan did with filmmaker Dave Clark: https://every.to/chain-of-thought/how-a-hollywood-director-uses-ai-to-make-movies The AI tools Dan and Steph use on the show: Consensus, Globe Explorer, websim.ai, Granola, Suno
Steph Smith is the ultimate internet explorer.
I spent an hour talking to her about the future of creating on the internet in the age of AI. She’s our first-ever repeat guest, and if you watch the episode you’ll see why: It’s a curious, fun, experimental romp through the best of the digital world.
We try out four underrated AI products, go through a list of Steph’s favorite niche internet creators, and follow her creative process in Midjourney in granular detail.
We had a wide-ranging discussion about:
- How AI changes what humans perceive as valuable in art and creativity
- The type of AI tools that are poised for success
- How AI narrows the gap between ideas and execution
If you don’t know her, Steph is the host of the @a16z podcast and the creator behind Internet Pipes, a toolkit to surface useful insights on the internet, and many other cool internet projects.
This is a must-watch if you make things on the internet and are interested in how AI is changing what it means to be a creator—and how creator businesses work.
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:
00:00:00 - Teaser
00:00:46 - Introduction
00:09:08 - How Steph uses Midjourney to find her aesthetic
00:20:45 - Steph predicts how creating on the internet will evolve with AI
00:32:51 - Rapid-fire rundown of Steph's favorite niche creators
00:42:58 - How Steph trains her brain on better data
00:48:19 - The AI research tool Steph uses for health information
00:56:25 - The future of AI tools—and one of Steph's top picks
01:01:20 - Dan and Steph use AI to create a simulation of the internet
01:05:09 - How LLM hallucinations can be useful
01:12:06 - Dan and Steph make a song about what they learned on the show
Links to resources mentioned in the episode:
Steph Smith: https://twitter.com/stephsmithio
Internet Pipes: https://internetpipes.com/
Doing Content Right: https://doingcontentright.com/#features
A few of Steph’s favorite niche creators: India Rose Crawford https://www.instagram.com/indiarosecrawford/?hl=en , Blackforager https://www.instagram.com/blackforager/?hl=en , David Zinn https://www.instagram.com/davidzinn/?hl=en , David Bird https://www.instagram.com/davidmbird/ , WatchMaggiePaint https://www.instagram.com/watchmaggiepaint/?hl=en
The podcast episode Dan did with filmmaker Dave Clark: https://every.to/chain-of-thought/how-a-hollywood-director-uses-ai-to-make-movies
The AI tools Dan and Steph use on the show: Consensus https://consensus.app/ , Globe Explorer https://explorer.globe.engineer/ , websim.ai http://websim.ai , Granola https://www.granola.so/ , Suno https://suno.com/
Dr. Bradley Love is building a tool that can predict the future.
Dr. Bradley Love is transforming neuroscience research with AI.
He's the creator of BrainGPT, a large language model that can predict the results of neuroscience studies—before they’re conducted. And it performs better than human experts.
We spent 90 minutes exploring how AI is reshaping scientific research and our understanding of the brain.
Bradley argues that as scientific knowledge grows exponentially, we need new tools to make sense of it all. BrainGPT isn't just summarizing existing research—it's predicting future discoveries.
We get into: • How BrainGPT outperforms neuroscience professors • Why clean scientific explanations may be a thing of the past • The challenges of interpreting complex biological systems • How AI could change the way we approach scientific research • The limitations of our intuitive understanding of the brain
This is a must-watch for anyone interested in the future of science, AI, and how we understand the human mind.
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. 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: 00:00:00 - Teaser 00:01:00 - Introduction 00:01:58 - The motivations behind building a LLM that can predict the future 00:11:14 - How studying the brain can solve the AI revolution’s energy problem 00:13:32 - Dr. Love and his team have developed a new way to prompt AI 00:18:27 - Dan’s take on how AI is changing science 00:22:54 - Why clean scientific explanations are a thing of the past 00:29:49 - How our understanding of explanations will evolve 00:37:31 - Why Dr. Love thinks the way we do scientific research is flawed 00:40:42 - Why humans are drawn to simple explanations 00:45:03 - How Dr. Love would rebuild the field of science
Links to resources mentioned in the episode: Dr. Bradley Love: https://bradlove.org/; https://twitter.com/ProfData BrainGPT: https://braingpt.org/ Thomas Nagel’s book on the philosophy of science that Dr. Love recommends: The View From Nowhere The essay that Thomas Nagel is famous for: What is it like to be a bat?
Dr. Bradley Love is building a tool that can predict the future.
Dr. Bradley Love is transforming neuroscience research with AI.
He's the creator of BrainGPT, a large language model that can predict the results of neuroscience studies—before they’re conducted. And it performs better than human experts.
We spent 90 minutes exploring how AI is reshaping scientific research and our understanding of the brain.
Bradley argues that as scientific knowledge grows exponentially, we need new tools to make sense of it all. BrainGPT isn't just summarizing existing research—it's predicting future discoveries.
We get into:
• How BrainGPT outperforms neuroscience professors
• Why clean scientific explanations may be a thing of the past
• The challenges of interpreting complex biological systems
• How AI could change the way we approach scientific research
• The limitations of our intuitive understanding of the brain
This is a must-watch for anyone interested in the future of science, AI, and how we understand the human mind.
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. 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:
00:00:00 - Teaser
00:01:00 - Introduction
00:01:58 - The motivations behind building a LLM that can predict the future
00:11:14 - How studying the brain can solve the AI revolution’s energy problem
00:13:32 - Dr. Love and his team have developed a new way to prompt AI
00:18:27 - Dan’s take on how AI is changing science
00:22:54 - Why clean scientific explanations are a thing of the past
00:29:49 - How our understanding of explanations will evolve
00:37:31 - Why Dr. Love thinks the way we do scientific research is flawed
00:40:42 - Why humans are drawn to simple explanations
00:45:03 - How Dr. Love would rebuild the field of science
Links to resources mentioned in the episode:
Dr. Bradley Love: https://bradlove.org/; https://twitter.com/ProfData
BrainGPT: https://braingpt.org/
Thomas Nagel’s book on the philosophy of science that Dr. Love recommends: The View From Nowhere
The essay that Thomas Nagel is famous for: What is it like to be a bat?
Claire Vo built ChatPRD—an on-demand chief product officer powered by AI. It’s now used by over 10,000 product managers and is pulling in six figures in revenue.
The best part? Claire has a demanding day job as the CPO at LaunchDarkly. So she built all of ChatPRD herself—over the weekend—with AI. I sat down with Claire to talk about how ChatPRD works, how she built it as a side hustle using AI, and all of the ways she’s using AI tools to accelerate her work and life. We get into:
This is a must-watch for anyone interested in turning their side hustle into a thriving business or who works in product.
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. It’s usually only for paying subscribers, but you can get it here for free.
To hear more from Dan Shipper:
Links to resources mentioned in the episode:
Claire Vo built ChatPRD—an on-demand chief product officer powered by AI. It’s now used by over 10,000 product managers and is pulling in six figures in revenue.
The best part?
Claire has a demanding day job as the CPO at LaunchDarkly. So she built all of ChatPRD herself—over the weekend—with AI.
I sat down with Claire to talk about how ChatPRD works, how she built it as a side hustle using AI, and all of the ways she’s using AI tools to accelerate her work and life.
We get into:
This is a must-watch for anyone interested in turning their side hustle into a thriving business or who works in product. 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. It’s usually only for paying subscribers, but you can get it here for free.
To hear more from Dan Shipper:
Links to resources mentioned in the episode:
An interview with best-selling sci-fi novelist Robin Sloan
One of my favorite fiction writers, New York Times best-selling author Robin Sloan, just wrote the first novel I’ve seen that’s inspired by LLMs.
The book is called Moonbound, and Robin originally wanted to write it with language models. He tried doing this in 2016 with a rudimentary model he built himself, and more recently with commercially available LLMs. Both times Robin found himself unsatisfied with the creative output generated by the models. AI couldn’t quite generate the fiction he was looking for—the kind that pushes the boundaries of literature.
He did, however, find himself fascinated by the inner workings of LLMs
Robin was particularly interested in how LLMs map language into math—the notion that each letter is represented by a unique series of numbers, allowing the model to understand human language in a computational way. He thinks LLMs are language personified, given its first heady dose of autonomy.
Robin’s body of work reflects his deep understanding of technology, language, and storytelling. He’s the author of the novels Mr. Penumbra’s 24-hour Bookstore and Sourdough, and has also written for publications like the New York Times, the Atlantic, and MIT Technology Review. Before going full-time on fiction writing, he worked at Twitter and in traditional media institutions.
In Moonbound, Robin puts LLMs into perspective as part of a broader human story. I sat down with Robin to unpack his fascination with LLMs, their nearly sentient nature, and what they reveal about language and our own selves. It was a wide-ranging discussion about technology, philosophy, ethics, and biology—and I came away more excited than ever about the possibilities that the future holds.
This is a must-watch for science-fiction enthusiasts, and anyone interested in the deep philosophical questions raised by LLMs and the way they function.
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:
Links to resources mentioned in the episode:
An interview with best-selling sci-fi novelist Robin Sloan
One of my favorite fiction writers, New York Times best-selling author Robin Sloan, just wrote the first novel I’ve seen that’s inspired by LLMs.
The book is called Moonbound, and Robin originally wanted to write it with language models. He tried doing this in 2016 with a rudimentary model he built himself, and more recently with commercially available LLMs. Both times Robin found himself unsatisfied with the creative output generated by the models. AI couldn’t quite generate the fiction he was looking for—the kind that pushes the boundaries of literature.
He did, however, find himself fascinated by the inner workings of LLMs
Robin was particularly interested in how LLMs map language into math—the notion that each letter is represented by a unique series of numbers, allowing the model to understand human language in a computational way. He thinks LLMs are language personified, given its first heady dose of autonomy.
Robin’s body of work reflects his deep understanding of technology, language, and storytelling. He’s the author of the novels Mr. Penumbra’s 24-hour Bookstore and Sourdough, and has also written for publications like the New York Times, the Atlantic, and MIT Technology Review. Before going full-time on fiction writing, he worked at Twitter and in traditional media institutions.
In Moonbound, Robin puts LLMs into perspective as part of a broader human story. I sat down with Robin to unpack his fascination with LLMs, their nearly sentient nature, and what they reveal about language and our own selves. It was a wide-ranging discussion about technology, philosophy, ethics, and biology—and I came away more excited than ever about the possibilities that the future holds.
This is a must-watch for science-fiction enthusiasts, and anyone interested in the deep philosophical questions raised by LLMs and the way they function.
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:
Robin Sloan: https://www.robinsloan.com/
Robin’s books: Mr. Penumbra's 24-Hour Bookstore, Sourdough, Moonbound
Dan’s first interview with Robin four years ago: https://every.to/superorganizers/tasting-notes-with-robin-sloan-25629085
Anthropic AI’s paper about how concepts are represented inside LLMs: https://www.anthropic.com/news/mapping-mind-language-model
Dan’s interview with Notion engineer Linus Lee: https://www.youtube.com/watch?v=OeKEXnNP2yA
Big Biology, the podcast that Robin enjoys listening to: https://www.bigbiology.org/
We use it to find bestselling author Steven Berlin Johnson’s next project.
I sat down with bestselling author Steven Johnson to see if we could come up with a concept for his next project—using AI. The results were amazing.
We loaded 200,000 words of NASA transcripts and all of Steven’s reading notes since 1999 into NotebookLM, Google’s personalized research assistant. We wanted to see if it could help us explore the Apollo 1 fire and find relevant and surprising ideas from history that could work to explain it.
If you’re a fan of Steven Johnson’s work or you’re interested in AI as a creative tool, you need to watch this episode.
All of this happens as a live exploration of NotebookLM, and it’s a seriously wild ride.
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 Follow him on X
Links to resources mentioned in the episode: Follow Steven JohnsonNotebookLM Steven’s newsletter, Adjacent Possible Steven’s latest book about the rise of the modern detective: The Infernal Machine A few of Steven’s other books: How We Got to NowWhere Good Ideas Come FromThe Ghost MapEmergenceThe Invention of Air
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