AI and I

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 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 

Here’s the most compelling benchmark of AI progress:  A task that took 60 minutes a year ago now takes 60 seconds. In January 2024, Geoffrey Litt and I spent an hour coaxing ChatGPT and Replit to build an app live on my podcast.12 months later, Steve Krouse and I built the same app with one prompt in less than a minute.  Steve is the cofounder and CEO of Val Town, a cloud-based platform for developers to write, share, and deploy code directly in the browser. We used Townie, Val Town’s AI assistant, to build an app to keep track of time on the podcast, take notes, and generate questions for the guest.   Townie generated the app even before Steve could finish describing it on the show. As we demo Townie, we get into: Why Steve believes programming can rewire the way you think  The rise of the non-technical AI developer and what that means for the future of coding How Townie works under the hood, including the details of the system prompt  How Steve is evolving ValTown’s strategy as AI progress continues to unfold The power of small, dense engineering teams  This is a must-watch for founders building AI-powered developer tools, and anyone interested in the future of programming. 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 (00:00:55) How programming changes the way you think (00:03:24) Building an app in less than 60 seconds (00:11:22) How Val Town’s AI assistant works (00:17:19) Steve’s contrarian take on the non-technical AI programmer (00:23:05) The nuances of building software that isn’t deterministic (00:33:38) How to design systems that can capitalize on the next leap in AI (00:39:05) What gives Val Town a competitive edge in a crowded market (00:40:47) The power of small, dense engineering teams (00:47:34) How Steve is positioning Val Town in a strategic niche (00:52:26) Links to resources mentioned in the episode:  Steve Krouse: https://stevekrouse.com/, @stevekrouse  Val Town: https://www.val.town/  Townie, the AI assistant integrated into Val Town: https://www.val.town/townie/signup?next=%2Ftownie  Pieces on Val Town’s blog about how the team built Townie: How we built Townie—an app that generates fullstack apps, Building a code-writing robot and keeping it happy  The book by Seymour Papert about how programming changes the way you think: Mindstorms: Children, Computers, and Powerful Ideas

Over the last few months at Every, we’ve: Launched two AI products Acquired tens of thousands of users Released a new incubation in private alpha The weird thing is: We’re a media company with < 10 full-time employees, and we’re mostly bootstrapped. That’s not how things are supposed to work in startups. When we started our product incubation arm six months ago, many people told us it wouldn’t work: divided focus, not enough money, and the biggest one—it would be too hard to find talented people to run the products we build. Yesterday, we proved out one of the biggest risks to our strategy: We launched a brand-new version of our AI product Spiral (https://spiral.computer) with Danny Aziz as GM—who left a $200K salary to join us.  The question is: Why? Why did he join us, and why is the model working when it “shouldn’t” be? That’s why I invited Danny and Brandon Gell, Every’s head of Studio, on the show. We get into the details of Every’s business model, what makes our flywheel turn, where each of us sees ourselves one year from now, and what happens when you mix media, software, and AI under one roof. This is a must-watch for anyone who wants to build a business on their own terms, and have a lot of fun while doing it.  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: 00:01:08 All about Spiral, the tool we recently launched: 00:02:15 Why Danny left a $200,000 salary to work at a bootstrapped media company: 00:04:06 How we do a lot of things well at Every: 00:10:33 What makes Every’s flywheel turn: 00:14:44 The kind of people who fit right in at Every: 00:17:11 How Every is differentiated from a standard VC-backed startup: 00:23:25 How Danny found his way into the world of startups: 00:36:11 The tech industry’s affinity for potential over experience: 00:46:43  Where each of us sees ourselves in the next one year: 00:52:38 Links to resources mentioned in the episode:  Danny Aziz: @DannyAziz97 Brandon Gell: @bran_don_gell Try Spiral here: https://spiral.computer/   More about Every’s product incubation arm: https://every.to/p/introducing-every-studio 

Everyone told Vicente Silveira that his startup—a GPT wrapper—would fail.  Instead, one year later, it’s thriving—with about 500,000 registered users, nearly 3,000 paying subscribers, and over 2 million conversations in the GPT store.  Vicente is the cofounder and CEO of AI PDF, a tool that can help you summarize, chat with, and organize your PDF files. When OpenAI allowed users to upload PDFs to ChatGPT, the consensus was that his startup, and all the other GPT wrappers out there, were toast.  Some of his competitors even shut shop, but Vicente believed they could still create value for users as a specialized tool. The AI PDF team kept building.  A year later, AI PDF is one of the most popular AI-powered PDF readers in the world—and they did it all with a five-person team, and a friends and family round.  I sat down with Vicente to understand, in granular detail, the success of AI PDF. We get into: Why staying small and specialized is a bigger advantage than you think The power of building with your early adopters Why lean startups are better positioned than frontier AI companies to create radical solutions  When a growing startup should think about raising venture capital The emerging role of ‘AI managers’ who will be responsible for overseeing AI agents  We even demo an agent integrated into AI PDF, prompting it to analyze recent articles from my column Chain of Thought and write a bulleted list of the core thesis statements. This is a must-watch for small teams building profitable companies at the bleeding edge 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: (00:00:35) AI PDF’s story begins with an email to OpenAI’s Greg Brockman: (00:02:58) Why users choose AI PDF over ChatGPT: (00:05:41) How to compete—and thrive—as a GPT wrapper: (00:06:58) Why building with early adopters is key: (00:20:49) Being small and specialized is your biggest advantage: (00:27:53) When should AI startups raise capital: (00:31:47) The emerging role of humans who will manage AI agents: (00:34:53) Why AI is different from other tech revolutions: (00:45:25) A live demo of an agent integrated into AI PDF: (00:54:01)

Prompt engineering matters more than ever. But it’s evolving into something totally new:  A way for non-technical domain experts to solve complex problems with AI. I spent an hour talking to prompt wizard Jared Zoneraich, cofounder and CEO of PromptLayer, about why the death of prompt engineering is greatly exaggerated. And why the future of prompting is equipping non-technical experts with the tools to manage, deploy, and evaluate prompts quickly. We get into: His theory around why the “irreducible” nature of problems will keep prompt engineering relevant Prompt engineering best practices around prompts, evals, and datasets Why it’s important to align your prompts with the language the model speaks How to run evals when you don’t have ground truth Why he believes that the companies who have domain experts to scope out the right problems will win in the age of gen AI This is a must-watch for prompt engineers, people interested in building with AI systems, or anyone who wants to generate predictably good responses from LLMs. 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: 00:01:08 Jared’s hot AGI take: 00:09:54 An inside look at how PromptLayer works: 00:11:49  How AI startups can build defensibility by working with domain experts: 00:15:44 Everything Jared has learned about prompt engineering: 00:25:39 Best practices for evals: 00:29:46 Jared’s take on o-1: 00:32:42 How AI is enabling custom software just for you: 00:39:07 The gnarliest prompt Jared has ever run into: 00:42:02 Who the next generation of non-technical prompt engineers are: 00:46:39 Links to resources mentioned in the episode:  Jared Zoneraich: @imjaredz PromptLayer: @promptlayer, https://www.promptlayer.com/ A couple of Steven Wolfram’s articles on ChatGPT: What Is ChatGPT Doing … and Why Does It Work?, ChatGPT Gets Its “Wolfram Superpowers”!   

This episode is sponsored by Notion. I’ve been using Notion to manage my professional and personal life for almost 10 years. As a company, they pay attention to the craft and ideas underlying the software they build, and that comes through in the experience of using Notion every day. If you’re a startup, get up to 6 months of Notion Plus with unlimited AI—worth up to $6,000—for free by going to https://ntn.so/every, selecting Every in the drop-down partner list, and using the code EveryXNotion. Notion cofounder Simon Last told me everything he’s learned from integrating AI into a platform that has over 100 million users. Simon likes to keep a low profile, even though he’s the driving force behind Notion AI, one of the most widely scaled AI applications in the world. In his first-ever podcast interview, we get into: What he would build if he started Notion from scratch today with AI How to get high quality and reliable results from AI at scale The future of human creativity in a world with machines that think   This is a must-watch for anyone interested in building reliable AI products at scale. 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: 00:01:57 How AI changes the way we build the foundational elements of software: 00:02:28 Simon’s take on the impact of AI on data structures: 00:10:07 The way Simon would rebuild Notion with AI: 00:13:05 How to design good interfaces for LLMs: 00:23:39 An inside look at how Notion ships reliable AI systems at scale: 00:28:22 The tools Simon uses to code: 00:35:41 Simon’s thoughts on scaling inference compute as a new paradigm: 00:38:16 How the growing capabilities of AI will redefine human roles: 00:49:10 Simon’s AGI timeline: 00:50:28 Links to resources mentioned in the episode: Simon Last: @simonlast Notion AI: https://www.notion.so/product/ai The AI code editor Simon uses: Cursor OpenAI’s definition of AGI that Simon ascribes to: https://openai.com/charter/

Union Square Ventures is building an AI operating system to support their investment team.  But it’s not what you think: It’s a constellation of AI tools that captures and synthesizes the firm's collective wisdom. It’s evolving every day, and Matt Cynamon is the mad scientist in charge Matt calls himself a “regular” at USV. In practice that means he’s responsible for running experiments with AI for the firm. As an inherently curious person with the professional obligation to tinker, he’s built a suite of tools for the firm, including:  The Librarian, a chatbot trained on around 15,000 articles from USV’s blog Portfolio Tracker, a GPT that analyzes the investments made by the firm Meeting Notes, a tool that makes it possible for team members to interact with meetings   I sat down with Matt to talk about how AI is enabling him to bring his ideas to life as a generalist, get demos of the tools listed above, and exchange notes on all the other projects he has in the works at USV. We edit actionable insights extracted by an AI from meetings at USV and prepare them to be posted on the firm’s X handle live on the show. We even try out an art project at USV’s office called The Dream Machine, which generates art from conversations. Here’s a link to the episode transcript.    This is a must-watch for anyone interested in riding the AI wave by learning how to ship useful products quickly. 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: (00:00:52) How Matt became in charge of everything AI at USV: (00:01:56) How AI empowers generalists to be creators: (00:06:22) The Librarian, a chatbot trained on everything USV has published: (00:10:41) Portfolio Tracker, an AI tool to track USV’s investments: (00:21:09) The AI projects that Matt has in the pipeline at USV: (00:27:21) Meeting Notes, USV’s AI note-taking tool: (00:34:33) Prompting AI to generate a post for USV’s X handle: (00:44:57) Why it’s important to diversify ownership over data: (01:00:20) The Dream Machine, AI that generates images from conversations: (01:03:20) Links to resources mentioned in the episode: Matt Cynamon: @mattcynamon Union Square Ventures: @usv, https://www.usv.com/  More about the AI tools at USV: https://www.usv.com/people/the-librarian/, https://www.usv.com/writing/2024/02/ai-aesthetics/  The X post generated live on the show: https://x.com/usv/status/1847354782941663523

Yohei Nakajima leads a double life.  By day, he’s a general partner of a small venture firm, Untapped Capital.  By night, he’s one of the most prolific internet tinkerers in AI. (He also sometimes works on automating his job as a venture capitalist.) He’s the creator of BabyAGI (@babyAGI_), the first open-source autonomous agent that went viral in March 2023. Yohei has since released seven iterations of BabyAGI (each one named after a different animal), a coding agent called Ditto, a framework for building autonomous agents, and, most recently, BabyAGI 2o, a self-building autonomous agent (that follows OpenAI’s unfortunate naming convention). Even more incredible, Yohei isn’t a professional developer. His day job is as the general partner of Untapped Capital (@UntappedVC). I sat down with Yohei to talk about: What feeds Yohei’s drive to create new tools The evolution of BabyAGI into a more powerful version of itself  What Yohei learned about himself by tinkering on the internet Yohei’s personal philosophy about how the tools we build our extensions of ourselves Why founders in AI should think about their products from a modular lens, by addressing immediate problems while enabling growth in the future Yohei’s insight into a future where models will train themselves as you use them We experiment with Ditto live on the show, using the tool to build a game of Snake and a handy scheduling app. Yohei also screenshares a demo of BabyAGI 2o in action. This is a must-watch for anyone curious about autonomous agents, building cool AI tools on the internet, and the future of AI tooling. 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) BabyAGI and its evolution into a more powerful tool: (00:02:26) How better models are changing the way Yohei builds: (00:05:00) Using code building agent Ditto to build a game of Snake: (00:08:10) The ins and outs of how Ditto works: (00:13:24) How Yohei gets a lot done in little time: (00:19:21) Yohei’s personal philosophy around building AI tools: (00:21:50) How Yohei experiments with AI as a tech-forward parent: (00:33:13) Demo of Yohei’s latest release, BabyAGI 2.0: (00:39:29) Yohei’s insights on the future of AI tooling: (00:51:24) Links to resources mentioned in the episode:  Yohei Nakajima: @yoheinakajima, http://yohei.me  Untapped Capital: @UntappedVC, https://www.untapped.vc/  My first interview with Yohei, around the time he released BabyAGI: https://every.to/chain-of-thought/this-vc-is-slowly-automating-their-job  The other AI tools Yohei has created: Ditto, BabyAGI 2, BabyAGI 2o The tweet thread about AI bots being let loose on a Discord server: https://x.com/AISafetyMemes/status/1847312782049333701 

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