This episode is sponsored by Reflect. It’s the ultra-fast note-taking app that’s about to change the way you take notes. To boost your productivity with advanced features like custom prompts and voice transcripts, give Reflect a try by clicking on this link: https://reflect.app/?utm_source=every&utm_medium=sponsorship&utm_campaign=september2024 Simon Eskildsen is a learning machine. I first interviewed him in 2020 about how he leveled up from an intern at Shopify to the company’s director of production engineering by reading and applying insights from hundreds of books. A lot has changed over the last four years. LLMs have made it possible to contextualize information like never before—and in this episode, I sat down with Simon to talk about how this changes the way he learns. Simon is now the cofounder and CEO of AI startup turbopuffer, which is building a search engine that makes vector search easy and affordable to run at scale. We get into: How Simon’s learning rituals have evolved over time, as the cofounder of a growing startup and a new parent The ways Simon has integrated ChatGPT, Claude, and Notion AI to do everything from writing legal documents to maintaining his rural cabin in Quebec The custom AI commands in productivity tool Raycast that Simon uses to learn new words and cook creative dishes Simon’s take on how language models will reshape the future of learning, especially skills like language acquisition, for the next generation As we talk, we screenshare through his Anki setup, including the flashcard template he finds most useful, and try out his custom AI commands in Raycast to understand the meaning of two of my favorite obscure words, “lambent” and “eigengrau.” This is a must-watch for note-taking aficionados and anyone who wants to supercharge their learning 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: 00:01:06 How entrepreneurship and parenthood changed Simon’s learning rituals: 00:02:51 How Simon accelerates his learning by using LLMs to find associations: 00:12:59 Simon’s Anki setup and the flashcard template he swears by: 00:18:24 The custom AI commands that Simon uses most often: 00:26:02 How Simon uses LLMs for DIY home projects: 00:37:45 Leveraging LLMs as intuitive translators: 00:40:48 Simon’s take on how AI is reshaping the future of learning: 00:51:38 How to use Notion AI to write: 00:59:10 The AI tools that Simon uses to write, read, and code: 01:08:53 Links to resources mentioned in the episode: Simon Eskildsen: @Sirupsen Simon’s startup, turbopuffer: turberpuffer.com, @turbopuffer My first interview with Simon in 2020: https://every.to/superorganizers/how-to-build-a-learning-machine-299655 The productivity tool through which Simon uses LLMs, Raycast: https://www.raycast.com/ The other AI tools that Simon is experimenting with: voice-to-text tool superwhisper, copilot for developers Supermaven, code editor Cursor
How do two professional writers use AI to do the best work of their lives? In today’s show, Every’s lead writer Evan Armstrong and I conduct an expert workshop on how we use ChatGPT, Claude, AI-powered word processor Lex, and the prompt builder that Every launched, Spiral, to feed our obsession with words—and help us write for more than 78,000 readers every day. We talk about how AI helps us: Understand our taste—understanding what good is Pick a topic—knowing what to write about Craft our words—everything from sketching out an outline to writing and editing Build an audience—learn how to reach people We get into: How I used Claude and ChatGPT to help me identify the kind of writing I like—and why that’s critically important for mastery How Evan uses ChatGPT to explore his taste across books, movies, and paintings The way I use Claude Projects to help me turn a vast amount of research into a clear thesis statement for major projects The routine Evan swears by to publish two pieces every week How Evan and I use Lex to push through writer’s block and catch common writing mistakes like passive voice My workflow inside Claude to craft emphatic metaphors How we use Spiral to write viral tweets Evan is the lead writer at Every who writes the column Napkin Math twice a week. He’s smart, funny, curious—and has the rare combination of business acumen, way with words, and crazy required to be a professional writer. This is a must-watch for aspiring writers, or anyone whose job involves writing more than six sentences in a row. 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: 00:01:04 How to develop good taste: 00:04:28 Dan uses Claude to articulate his taste in books: 00:13:34 How to use LLMs to explore art cross different mediums: 00:21:06 The way Evan chooses his next essay topic: 00:33:45 Go from research notes to clear thesis in Claude Projects: 00:38:20 How Evan uses AI to master new topics quickly: 00:46:51 Evan leverages AI to power through writer’s block: 00:59:21 How to use Claude to find good metaphors: 01:04:28 The role of AI in building an audience: 01:11:44 Links to resources mentioned in the episode: Evan Armstrong: @itsurboyevan The column Evan writes at Every: Napkin Math Evan’s upcoming course about how to write with AI: https://www.writewithai.xyz/ The piece Dan wrote about using LLMs to articulate his taste: "What I Do When I Can’t Sleep" Dan’s article about admitting that he wants to be a writer: "Admitting What Is Obvious"
The Browser Company isn’t just building a browser, they’re building a formidable brand—and they’re doing it with AI. I sat down with Nashilu Mouen-Makoua, the head of storytelling at The Browser Company, to talk about how they tell stories that capture the cultural zeitgeist and connect authentically with their users—and how she integrates AI into her process for both. We get into: Nash’s storytelling philosophy, and why she believes focusing on people is the key to a strong brand How to she uses ChatGPT to do deep research into past cultural moments—and the songs, movies, and products that resonated most deeply in those contexts The brass tacks of how the creative team at The Browser Company comes up with great ideas—including how they structure internal meetings How Nash has integrated ChatGPT to help her polish her words What Nash thinks the gestalt of the current age is—and how The Browser Company is trying to reach “laptop people” in a fresh way We also screen share through Nash’s conversation with ChatGPT as she conducted research for an exercise in how to position Arc, and use the LLM to simulate a typical Arc user and interview them live on the show to gather preliminary customer insights. This is a must-watch for people who want to use AI to tell compelling stories about what they’re building in tech. 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: 00:00:47 Nash’s philosophy around storytelling: 00:04:03 The Browser Company’s strategy to come up with creative ideas: 00:09:07 Why Nash thinks building brands people can relate to is important: 00:15:00 How to avoid the tired narrative around AI products: 00:18:47 The ways Nash has integrated ChatGPT into her workflow: 00:22:21 Why understanding social context is important to position your product: 00:33:35 How Nash uses ChatGPT to get a gut check on her writing: 00:41:10 What Nash thinks is the gestalt of the current age: 00:49:50 Nash and Dan use ChatGPT to simulate and interview a typical Arc user: 00:52:01 Links to resources mentioned in the episode: Nashilu Mouen-Makoua: https://twitter.com/lafillemouen The Browser Company: https://thebrowser.company/, https://twitter.com/browsercompany Arc, the browser that reimagines the way we use the internet: https://arc.net/, @arcinternet Tracy Chapman’s song, Talkin’ About a Revolution: https://www.youtube.com/watch?v=Xv8FBjo1Y8I
The journey to a calm, profitable business in the AI age We’re building a mini-AI media and software empire at Every. Today on AI & I, Brandon Gell joins the show to turn the tables on me and act as podcast host to explore what we’re doing as a company, how we got here, and where we’re going. Brandon is Every’s first entrepreneur in residence, and he was the perfect person to host, because he’s one of the key reasons for our recent acceleration. Before joining Every, Brandon was the cofounder and CEO of Clyde, a startup that helped brands launch their own insurance and warranty programs, where he raised $50 million and led a team of 100 before selling it to global insurance tech company Cover Genius in early 2023. In this episode, he interviews me about how I learned to code in middle school, how I built and sold my first startup coming out of college, and how it all led to Every. We also talk about Brandon’s story. He joined Every just four months ago—and it feels like we’ve done the work of years since. We’ve launched two new AI products, an incredible amount of great writing, a new course, and more. We get into: My candid thoughts on entrepreneurship in the AI age—including why you should ship fast, and how not to be misled by metrics like TAM How AI startups can find valuable niches—and live demos of our apps Spiral and Sparkle Brandon’s hard-earned lessons from running a insuretech business for seven years The confusing realities of being an exited founder, and how we navigated through those times What brought Brandon to Every—including the email he sent me before joining Every’s master plan and what we hope to build over the next few months and years This is a must-watch for anyone interested in building a calm, profitable business empire in the age of 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: 00:00:56 Dan’s childhood dream—to build a Microsoft competitor: 00:03:36 The first app Dan built in middle school: 00:07:07 The story of Dan’s first company that he sold in college: 00:18:52 How Every came to be: 00:33:56 The start of Brandon’s journey as a builder: 00:49:15 Brandon’s first software app—and why you should launch first, and iterate later: 00:57:05 Everything Brandon learned from running a B2B business for seven years: 01:08:49 What brought Brandon to Every—and the email he sent Dan before joining: 01:18:00 Every’s master plan to be a successful creator-run business: 01:29:15 Live demo of Spiral, the app that automates 80 percent of repetitive creative work: 01:38:11 Brandon and Dan’s take on how AI startups can find a valuable niche: 01:44:00 Live demo of Sparkle, the app that organizes your files for you: 01:50:52 Links to resources mentioned in the episode: Brandon Gell: https://twitter.com/bran_don_gell The piece Dan recently published about Every’s master plan: https://every.to/chain-of-thought/every-s-master-plan Dan’s piece about the unbundling of Excel, and why it serves as an important story in the age of AI: https://every.to/chain-of-thought/the-great-ai-unbundling Tomasz Tunguz, the VC who has also written about Excel: https://tomtunguz.com/ Every cofounder Nathan’s word processor, Lex: https://lex.page/ Spiral, the app that automates 80 percent of repetitive creative work: https://spiral.computer/ Sparkle, the app that automatically organizes your files: https://makeitsparkle.co/
Alex Wieckowski is on a mission to make you fall in love with reading again—and he thinks AI can help. Alex, who writes a newsletter that captures lessons from books he’s read and tips to become a better reader, Alex & Books, is a creator with over 1 million followers across social platforms. He’s also the author of a book of quotes that will inspire you to read more, Learn to Love Reading. We spent an hour talking about how Alex uses AI to be a smarter reader, and we tested out a few strategies live on the show, including: prompting ChatGPT to recommend books that will help me lead a creator-run business better, understanding the deeper themes in Hermann Hesse’s novel Siddhartha with large language models, and using AI to create an actionable strategy for Alex to build a course based on the frameworks in Alex Hormozi’s business strategy book $100M Offers. Alex clued me into what he’s learned about developing a good reading habit, and his best advice on how to reignite your passion for books. We also discuss Alex’s predictions on how companies like Neuralink, which make use of a brain-computer interface—a technology that allows users to control external devices through brain activity—will change the future of reading and books. Here’s a link to the transcript of this episode. This is a must-watch for book lovers, people struggling to finish books, and anyone who wants to take their reading to the next level 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: 00:00:34 Choose physical books over e-readers to boost your memory: 00:01:36 Alex’s take on how long books will stay relevant: 00:02:54 Prompt ChatGPT to find your next read: 00:07:40 Articulating Dan’s taste in books with AI: 00:13:50 Use AI to find books tailored to solve your problems: 00:15:46 How to use AI as a personal study buddy: 00:33:32 Prompt LLMs to turn insights from books into actionable strategies: 00:41:19 What Alex’s rule around buying a new book is: 01:02:10 Alex’s advice for anyone who feels like they don’t have time to read: 01:16:36 Links to resources mentioned in the episode: Alex Wieckowski: https://twitter.com/AlexAndBooks_ Alex’s newsletter: https://alexandbooks.beehiiv.com/ The self-improvement book that got Alex into reading: How to Win Friends & Influence People by Dale Carnegie The books that Dan is reading: Children of Memory by Adrian Tchaikovsky, Pragmatism as Anti-Authoritarianism by Richard Rorty The books that Alex is reading: Never Enough: From Barista to Billionaire by Andrew Wilkinson, $100M Offers by Alex Hormozi, Siddhartha by Hermann Hesse, Outlive by Peter Attia
One of the most influential voices in tech explains how AI helps him write and invest.This episode is sponsored by Create. If you want to maximize your gains, both with your body and with ChatGPT, try creatinine gummies from Create. Place your order through this link to get a 30 percent discount: https://trycreate.co/products/creatine-monohydrate-gummies-270-count?discount=every24Packy McCormick’s job is to find, articulate, and invest behind the next big idea.He writes Not Boring, a newsletter that analyzes technology and startups for 200,000 subscribers every week. He also invests in early stage companies through his fund Not Boring Capital and is an advisor at a16z crypto.I spent an hour with him to understand how he’s baked AI into the way he thinks, writes, and invests. We get into: How he uses AI to understand dense concepts and refine his arguments His thesis around vertically integrated businesses being the future of tech How Packy uses Claude Projects to edit his newsletter How he makes interactive graphics that represent concepts from his essays The tools Packy uses to research, write, and edit Not Boring When he thinks the next crypto bull run will take place We also use Projects to build an AI tool that grades Packy’s essays live on the show.This is a must-watch for writers, investors, and anyone trying to understand the cutting edge of technology.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/subscribeFollow him on X: https://twitter.com/danshipperTimestamps:00:00:00 - Teaser00:01:24 - Introduction00:02:40 - Packy's thesis about the future of technology00:07:42 - What Packy quick takes on your crypto portfolio00:14:31 - Use LLMs to validate your understanding of complex concepts00:18:26 - How Packy used Claude Projects to write an essay he published recently00:24:00 - Packy's process to make interactive visual graphics for his essays00:31:10 - How to use AI to be thorough in your research00:35:04 - How Packy uses Claude to edit his writing00:36:44 - The tools Packy uses to create his newsletter00:44:12 - Using Claude Projects to make a tool that grades Packy's essaysLinks to resources mentioned in the episode:Packy McCormick: https://twitter.com/packyMPacky’s newsletter, Not Boring: https://www.notboring.co/Packy’s fund, Not Boring Capital: https://www.notboring.co/p/introducing-not-boring-capitalOne of Packy’s first essays, about natively integrated companies: https://www.packym.com/natively-integrated-companiesAnduril, the company Packy thinks is an example of a Techno-industrial: https://www.anduril.com/Packy’s portfolio company that’s integration crypto into its product: https://v2.oncyber.io/The interactive tool Packy made for a recent newsletter: https://goventvectorsum.replit.app/ for https://www.notboring.co/p/the-american-millenniumPacky’s essay about America’s tolerance for risk: https://www.notboring.co/p/riskophiliaPacky’s essays about Blackbird: https://www.notboring.co/p/blackbird
Keeping up with AI is Nathaniel Whittemore’s full-time job—and I spent an hour with him to understand how he does it. Nathaniel is the host of a top-ranked AI podcast on the technology charts, The AI Daily Brief, which breaks down the most important news in AI every day. He is also the founder and CEO of Superintelligent, a platform that teaches you how to use AI for work and fun through interactive video tutorials. We talked about how he curates information with X bookmarks, Google News, news aggregator Feedly, and research tool Perplexity; the workflow that helps him record and produce two daily podcasts; and why he thinks optimizing your processes with AI remains one of its most underrated applications. Here’s what you’ll learn if you listen to or watch this episode: How to curates AI news using X bookmarks, Google News, Perplexity, and other specialized tools Nathaniel’s insights from producing 300-plus episodes of a top-ranked podcast The granular details of the workflow that helps Nathaniel produce two daily podcasts Actionable advice on how to get the most out of AI right now 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: 00:00:51 How you can get value of AI right now: 00:02:15 Nathaniel goes through his X bookmarks: 00:14:07 Why content should have a point of view: 00:20:25 Tools that Nathaniel uses to curate news about AI: 00:23:47 How to use LLMs to structure your thoughts: 00:31:27 Why the history of Excel is a good way to understand AI’s progress: 00:38:40 The AI features in Descript that Nathaniel uses: 00:45:46 AI-powered tools to help you generate content:00:49:11 Nathaniel’s tips on using Midjourney to generate YouTube thumbnails: 00:58:32 Links to resources mentioned in the episode: Nathaniel Whittemore: https://twitter.com/nlw The podcasts Nathaniel hosts: The AI Daily Brief, The Breakdown Podcast Nathaniel’s AI education platform: Superintelligent The tools Nathaniel uses to curate AI news: Google News, Feedly, Perplexity The AI-powered content generation tools Nathaniel likes: Hoppy Copy, SEO.ai
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: 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, 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
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: How she used AI to build ChatPRD over Thanksgiving break The part of product management that Claire thinks AI will disrupt Why the PMs of tomorrow will be “proto-managers” who create prototypes rather than just specs How junior PMs can use AI to upskill faster The ways in which ChatPRD is baked into her own workflow How building ChatPRD is making Claire a better PM How Claire uses AI as a tech-forward parent 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: Subscribe to Every: https://every.to/subscribe Follow him on X: https://twitter.com/danshipper Links to resources mentioned in the episode: Claire Vo: https://x.com/clairevo ChatPRD: https://www.chatprd.ai/; https://x.com/chatprd; https://www.linkedin.com/company/chatprd/; https://www.youtube.com/@ChatPRD Some of the AI tools that Claire used to build ChatPRD: http://Clerk.dev; https://tiptap.dev/ Greeking Out, the Greek mythology podcast that Claire’s son enjoys: https://www.nationalgeographic.com/podcasts/greeking-out
An interview with best-selling sci-fi novelist Robin SloanOne 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. NotebookLM condensed disparate 200,000 words of NASA transcripts into readable formats like FAQs and chronological timelines. It sifted through the material to identify the catalyst for the fire. The model even went through Steven’s Readwise notes to find a relevant, and unexpected, story from history that we could use to explain the history and origins of the fire 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
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
The NYT’s Kevin Roose has 18 new friends—none of whom are human. His new friends are AI personas that he made with Noma, Kindroid, and other AI companion apps. There’s fitness guru Jared, therapist Peter, trial lawyer Anna, and over a dozen more. Kevin talked to them every day for a month, sharing his feelings, asking for parenting advice, and even using them for “fit” checks. This isn’t the first time Kevin has had an…unusual interaction with an AI persona. A year ago, he was the target of Bing’s chatbot Sydney’s unhinged romantic affections. Kevin has gone deeper into the world of AI companions than anyone I know. He is a tech columnist at the New York Times, cohost of the Hard Fork podcast, and the author of three books. In this episode, I sat down with Kevin to learn more about his interactions with AI. We dive into: Why AI companions aren’t just for lonely people or shy teenagers Why AI personas are better friends than ChatGPT How AI companions can be used to safely explore different social contexts The risk of young people relying on AI for friendship The icks of AI dating and intimacy How to use AI to articulate what you value in your relationships This is a must-watch for anyone curious about how AI is changing the way we form relationships. 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 Links to resources mentioned in the episode: Kevin Roose Hardfork, the podcast that Kevin cohosts Kevin’s latest book about being human in a world designed for machines Kevin’s piece in the New York Times about his experience making AI friends Two of the apps that Kevin used to create AI companions: Kindroid and Nomi Dan’s piece that explains why AI writing will feel real through psychologist D.W. Winnicott’s theory Every’s piece that explores AI companion app Replika
Nick Dobos, maker of the #1 programming GPT, on prompt-gramming with AI Nick Dobos showed me how to ship a website with two words and a single click. He’s the creator of Grimoire, the #1 custom GPT for programming that has been used for over 1 million chats. All he gave Grimoire was two words: “coffee website.” Just a minute later, Grimoire built the website and pushed it live to the internet. It was wild. Grimoire can do a lot more than create websites—it’s a coding assistant with 75+ built-in hotkey commands and sample projects, a guide to learning how to code from scratch, and a tool for programmers to find answers to their questions in real-time. Before he created Grimoire, Nick was an iOS developer at Twitter. When ChatGPT came out, Nick started experimenting with it—and ended up building Grimoire. Today, he’s at the leading edge of experimenting and building with AI. I sat down with Nick to explore how people are using Grimoire and what it tells us about the age of programming by prompting. We dive into: How AI is massively lowering the barriers to code Why it’s important to solve the “blank canvas problem” that people experience while creating with AI How AI tools can streamline your creative process Why Grimoire has an edge over ordinary ChatGPT The best ways to use Grimoire to code smarter and faster This is a must-watch for coders, creative people, and anyone curious about how AI is changing the way we interact with computers. 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: 00:00:31 How Nick built Grimoire, the top-ranked GPT for programming: 00:05:20 Ship a website with two words and a single click: 00:10:25 How Grimoire is solving the “blank canvas problem” in AI creation: 00:14:57 The coding curriculum that can take you from zero to full programmer: 00:16:30 Why Grimoire has an edge over ordinary ChatGPT: 00:23:29 Nick’s thoughts on building the system prompt for a GPT: 00:34:10 The utility of AI as a new layer on top of existing apps: 00:40:04 How Nick uses a custom GPT to unpack his emotions: 00:43:11 How to use AI to break down tasks—from programming to daily to-do lists: 00:50:35 Links to resources mentioned in the episode: Nick Dobos: @NickADobos Grimoire: https://chat.openai.com/g/g-n7Rs0IK86-grimoire Nick’s website for his experiments with AI: https://mindgoblinstudios.com/ AI-first code editor Cursor: https://cursor.sh/ Open Interpreter: https://www.openinterpreter.com/ Lisa Feldman Barrett’s book: How Emotions Are Made Demo Hume, the empathetic AI voice: https://demo.hume.ai/
This AI can read emotions better than you can. It was created by Alan Cowen, the cofounder and CEO of Hume, an AI research lab developing models that can read your face and your voice with uncanny accuracy. Before starting Hume, Alan helped set up Google’s research into affective computing and has a Ph.D. in computational psychology from Berkely. Hume’s ultimate goal is to build AI models that can optimize for human well-being, and in this episode I sat down with Alan to understand how that might be possible. We get into: What an emotion actually is Why traditional psychological theories of emotion are inadequate How Hume is able to model human emotions How Hume's API enables developers to build empathetic voice interfaces Applications of the model in customer service, gaming, and therapy Why Hume is designed to optimize for human well-being instead of engagement The ethical concerns around creating an AI that can interpret human emotions The future of psychology as a science This is a must-watch for anyone interested in the science of emotion and the future of human-AI interactions. 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: Dan tells Hume’s empathetic AI model a secret: 00:00:00 Introduction: 00:01:13 What traditional psychology tells us about emotions: 00:10:17 Alan’s radical approach to studying human emotion: 00:13:46 Methods that Hume’s AI model uses to understand emotion: 00:16:46 How the model accounts for individual differences: 00:21:08 Dan’s pet theory on why it’s been hard to make progress in psychology: 00:27:19 The ways in which Alan thinks Hume can be used: 00:38:12 How Alan is thinking about the API v. consumer product question: 00:41:22 Ethical concerns around developing AI that can interpret human emotion: 00:44:42 Links to resources mentioned in the episode: Alan Cowen: @AlanCowen Hume: @hume_AI; hume.ai If you want to demo Hume: demo.hume.ai The nonprofit associated with Hume: Hume Initiative Lisa Feldman Barrett’s book: How Emotions Are Made The TV series based on Paul Ekman’s theory of emotion: Lie to Me
Learn how to use philosophy to run your business more effectively. Reid Hoffman thinks a masters in philosophy will help you run your business better than an MBA. Reid is a founder, investor, podcaster, and author. But before he did any of these things, he studied philosophy—and it changed the way he thinks. Studying philosophy trains you to think deeply about truth, human nature, and the meaning of life. It helps you see the big picture and reason through complex problems—invaluable skills for founders grappling with existential questions about their business. I usually bring guests onto my podcast to discuss the actionable ways in which people have incorporated ChatGPT into their lives. But this episode is different. I sat down with Reid to tackle a deeper question: How is AI changing what it means to be human? It was honestly one of the most meaningful shows I’ve recorded yet. We dive into: How philosophy prepares you to be a better founder The importance of interdisciplinary thinking Essentialism v. nominalism in the context of AI How language models are evolving to be more “essentialist” The co-evolution of humans and technology Reid also shares actionable uses of ChatGPT for people who want to think more clearly, like: Input your argument and ask ChatGPT for alternative perspectives Generate custom explanations of complex ideas Leverage ChatGPT as an on-demand research assistant This episode is a must-watch for anyone curious about some of the bigger questions prompted by the rapid development of AI. Thanks again to our sponsor CommandBar, the first AI user assistance platform, for helping make this video possible. https://www.commandbar.com/copilot/ 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 Links to resources mentioned in the episode: Reid Hoffman: @reidhoffman The podcasts that Reid hosts: Possible (possible.fm) and Masters of Scale (https://mastersofscale.com/) Reid’s book: Impromptu The book Reid recommends if you want to be more philosophically inclined: Gödel, Escher, Bach Reid’s article in the Atlantic: "Technology Makes Us More Human" The book about why psychology literature is wrong: The WEIRDest People in the World by Joseph Henrich The book about how culture is driving human evolution: The Secrets of Our Success by Joseph Henrich
Seth-Stephens Davidowitz wrote a book in 30 days—and he did it with ChatGPT. Seth is a data scientist, economist, and author who challenged himself to write a book—Who Makes the NBA?—in less than 1 month after realizing how fast he could work by using ChatGPT plugin Advanced Data Analysis. But along the way he discovered something else: Writing with AI wasn’t just faster, it was also way more fun. Seth outsourced the boring parts of data analysis—like cleaning data, merging files, and looking up code snippets—to AI. This left him to focus on what he loves: thinking up questions to ask the dataset. In a world where AI can answer any question humans know the answer to, asking the right questions is becoming increasingly important—a skill Seth isn’t just really good at, but also finds joy in. In this episode, Seth walks me through how he used AI to analyze data and write a book in 30 days. We get into: How to create and edit complex charts with AI in seconds Using ChatGPT to brainstorm creative ideas How AI is redefining who can be an artist Why ChatGPT is an excellent tool to get a quick ballpark estimate Developing a sixth sense about when ChatGPT is wrong The power of AI instantly answering hard questions that would normally take months of research We also use ChatGPT to analyze a dataset of Olympic athletes live on the show—in pursuit of finding out which sport I’m best suited for! This episode is a must-watch for anyone curious about data science and how AI is transforming the future of creativity (or who is just a fan of the NBA). 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: Seth Stephens-Davidowitz: https://twitter.com/SethS_D http://sethsd.com Seth’s books: Who Makes the NBA? , Everybody Lies and Don’t Trust Your Gut
Nicholas Thorne is building Squarespace for the AI age. It’s called Audos, and it’s an AI chatbot to help any entrepreneur go from idea to: - Pitch deck - Working website - Custom GPT - User interviews with real customers All in just a few minutes. And he did it using ChatGPTapp. It’s AI all the way down—and it’s one of the most impressive AI businesses I’ve ever seen. Nicholas is a general partner at Prehype, an incubator that launched Barkbox and Ro Health. It’s also where I started Every, so it was great to come full circle. Nicholas’s job at Prehype is to launch new companies. He’s taken everything he’s learned running an incubator and used it to help entrepreneurs start businesses at scale—with AI. As we talk, Nicholas walks me through the interactions of Audos’s chatbot with a user live on the show. Nicholas tells me that he used ChatGPT to prototype most of Audos’s features—despite being non-technical himself. He shares exactly how he did this by showing me how he’s using AI to create a new feature for the product. We get into: - Ways AI can make you a more effective founder - How to use ChatGPT to build your prototype - Strategies to refine problem statements with AI - Using GPTs to gather and synthesize customer feedback This episode is a must-watch for anyone who has ever toyed with the idea of starting a business—and wants to do it 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: https://every.ck.page/ultimate-guide-to-prompting-chatgpt 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 00:00:48 - Introduction 00:12:10 - How AI can make you a more effective founder 00:17:03 - Live demo of Audos! 00:24:07 - Why Nicholas built an AI tool to enable entrepreneurs 00:25:35 - How Audos puts you in “edit mode” instead of “create mode” 00:28:12 - Tools to gather customer feedback, generated by Audos 00:32:58 - How Audos actually works 00:35:07 - Nicholas uses ChatGPT to prototype a new feature 00:42:37 - How to establish checks and balances while using ChatGPT 00:57:20 - AI as a force for pushing entrepreneurship to new heights Links to resources mentioned in the episode: Nicholas Thorne: @thorneny; nicholas@prehype.com Audos: https://www.audos.com/ Nicholas’s book, Me, My Customer, and AI, is slated to publish next month. Follow him on X for updates: https://mmcai.super.site/
Adeola Elegbede
ChatGPT Nederlands currently has ChatGPT 4 and ChatGPT4-o. To use it for free you can go to: https://gptnederlands.com/