AI and I

• OpenAI Launches Codex: An Autonomous Programming Agent

  OpenAI just launched Codex, a brand-new coding agent that can build features and fix bugs autonomously. We’ve been testing it at Every for a few days, and I’m impressed.I invited Alexander Embiricos, a member of the OpenAI product staff responsible for Codex, to demo the agent live on a special edition of AI & I. We talk through:What Codex is and how it works. Codex’s UI allows developers to see the list of tasks the agent is working on, how many lines were changed for each, and the status of the PR. It’s built for the senior software engineer who wants to delegate and review tasks efficiently.How OpenAI is thinking about agents. Codex is one piece of a unified super-assistant OpenAI wants to eventually build—an agent that helps users easily get things done by selecting the right tools for them behind the scenes. Why an “abundance mindset” is best for interacting with agents. Codex is designed to allow users to delegate many tasks at once without getting caught up in the details. This lets you point an abundance of agents at a specific task, like a difficult bug—it’s worth it even if only one of them succeeds.OpenAI’s vision for the future of programming. In the future developers will probably spend less time writing routine code and more time guiding agents, reviewing their work, and making strategy decisions. Programming will become more social, letting teams easily delegate multiple tasks at once, allowing people to focus on ideas and collaboration instead of routine coding.Timestamps:Introduction: 00:00:52The product decisions behind Codex’s interface: 00:01:40How Codex works under the hood: 00:06:20Why you need an abundance mindset to work well with agents: 00:14:06Setting Codex to work on a real task in “Ask” mode: 00:16:28How OpenAI is thinking about designing agents: 00:18:54The future of programming is social: 00:31:16Reviewing Codex’s work live: 00:37:21How the landscape of agents will evolve: 00:39:41

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• The $10B Hedge Fund CEO Who’s Betting Big on AI | Will England, Walleye Capital

  Will England just pivoted his $10B AUM hedge fund to go all in on AI with a firm-wide email:“I wrote this email using ChatGPT—you should too. As a hedge fund, we should be ashamed to leave money on the table by ignoring AI.”It’s working: 75% of his 400-person team are using ChatGPT daily—and Walleye is well on its way to transforming into an AI-first juggernaut. They record every meeting, use LLMs to ingest and analyze earnings reports, and are building “The Borg”—a firmwide intelligence layer.What’s surprising? Will isn’t some AI hype man: He’s the CEO, CIO, and managing partner of Walleye Capital, a multi-strategy hedge fund competing with firms like Citadel, Millenium, and Point72. He’s Princeton and Oxford educated, but he’s based in Minnesota, doesn’t have an X account, and rarely gives interviews.In my experience, teams go as their CEO goes—and Will is the best example of a CEO going all in on AI that I’ve seen. "It would be irresponsible not to go after AI with maximum discipline and intensity," Will told me—and in this episode he lays out his exact playbook for doing it.We get into:Why AI is essential operating leverage. At Walleye, using AI is treated like using email or Excel. Ignoring it means getting left behind—in an industry where information = money, every edge counts. England makes this not optional for anyone, backed by internal leaderboards and cash incentives.How Will uses AI for journaling and decision-making. Will journals every day using ChatGPT, which helps him with everything from decision-making at work to reflecting on his family life to tracking his workouts. How Will pivoted his billion dollar firm. Will’s commitment to AI isn’t theoretical—he announced AI as the new standard for work at Walleye, and made avoiding it unacceptable. How to lead during times of technological change. Will leads with an ethic of personal responsibility: "If we get disrupted by AI, that's on me.”Why students of history do better at handling the future. Will sees today like the 1860s–1910s era—when the Industrial Revolution introduced factories and railroads and the skills and roles needed inside of companies transformed quickly.How Will uses AI to write faster. Will uses ChatGPT to help him draft emails or memos that would have taken hours in 15 minutes. He bullets out of his thoughts and then uses LLMs to turn that into polished prose. Having AI handle the linguistic syntax gives him more time for conceptual thinking.This is a must-watch for anyone who wants to lead a team through change with clarity and conviction.  Sponsor:Attio: Go to⁠⁠⁠ https://www.⁠⁠⁠⁠attio.com/every⁠⁠⁠⁠ and get 15% off your first year on your AI-powered CRM.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: 00:00:51What pushed Will to go all in on AI: 00:03:25Inside the ‘AI-first’ memo Will shared at Walleye: 00:14:08Why you shouldn’t be afraid of using AI for work: 00:15:56How Will uses LLMs to sharpen his thinking: 00:31:01Walleye’s approach to using AI to reduce risk: 00:35:32What history can teach us about leading through change: 00:39:10Will’s first principles to making better decisions: 00:56:45Why Will journals everyday—and how AI makes it easier: 00:58:58 Links to resources mentioned in the episode:Will England: https://walleyecapital.com/bio/will-england Walleye Capital: https://walleyecapital.com/ Work with Every’s consulting team: https://every.to/consulting  Everything we’ve learned from consulting with clients like Walleye: "How We Built a 7-figure AI Consulting Business in Less Than a Year"

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• Jhana Meditation Silenced Her Mind—And Changed Her View On AI | Nadia Asparouhova, Author and researcher

  After two Jhana meditation retreats Nadia Asparouhova could silence her mind, change her emotional state at will, and even intentionally slip out of consciousness. It challenged the idea that our minds are not under our control—and made her wonder if we’re more like AI than we realize. Nadia is a writer and researcher of technology and culture. She published Working in Public, a book about the evolution of open-source development, with Stripe Press in 2020. Her latest book, Antimemetics, is about why some ideas don’t go viral even though they’re powerful. I had her on the show to talk about her experience with Jhana meditation and how it reshaped the way she thinks about being human in the age of AI. We get into:Jhana as a means to nurture profound joy and calm. Unlike many meditation practices that emphasize passive observation, Jhana is goal-oriented—practitioners proactively cultivate states of concentrated bliss. Apart from helping her regulate her emotions, it prompted Nadia to reexamine deep questions of our human existence. Self-talk is not essential as it seems. Nadia describes how advanced meditation quieted her inner voice—challenging the idea that self-talk is core to being human.How years of cultural evolution have shaped our sense of self. According to Nadia, our modern conception of “self”  isn’t as timeless as we assume. She draws on psychologist Julian Jaynes’s theory that our inner dialogue—what we often equate with consciousness—only emerged in humans a few thousand years ago; a provocation to reconsider the benchmarks we use to assess the intelligence or sentience of LLMs.What it is like to experience a “cessation.” On her last meditation retreat, Nadia experiences a cessation where your consciousness abruptly winks out—like suddenly flipping a switch. Nadia described it as slipping into nothingness, then returning with the jarring realization that even your sense of self can vanish and reappear.Why she likes the unknowability of AI. The mechanics of exactly how LLMs predict their next token remain a mystery. Driven by thousands of subtle, context-dependent correlations, they’re too complex to distill into a simple explanation. Nadia finds joy in the unknowability of it all, seeing the ambiguity as an invitation to explore. How she uses AI as a writing partner. Nadia believes the trope of the solitary, brooding writer is beginning to shift with the rise of LLMs. For her, ChatGPT has made writing feel less isolating. She turns to it at both ends of the process: to help make sense of early ideas, and later, to sharpen phrasing and land on just the right words.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: 00:01:15The beginning of Nadia’s journey with Jhana: 00:02:34How Jhana is different from other meditation practices: 00:05:51 Jhana reframed the way Nadia thinks about being human: 00:09:52How Nadia integrates her experience with Jhana into her life: 00:14:16Nadia describes her experience of the final stage of Jhana: 00:16:44Why our modern sense of self isn’t as timeless as you might assume: 00:19:11How new technologies can be a mirror to ourselves: 00:23:53Nadia embraces the feeling of not knowing how AI precisely works: 00:33:55How Nadia uses ChatGPT to make writing less isolating: 00:38:03Links mentioned:Nadia Asparouhova: https://nadia.xyz/ Her deep dive on Jhana meditation: https://nadia.xyz/jhanas Nadia’s book: Working in Public, AntimemeticsBooks about how new technology can change our sense of self: The WEIRDest People in the World, Listening to Prozac

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• The Next AI Wave Will Be Social, Not Solo | Sarah Tavel, Benchmark and ex-Pinterest

  Sarah Tavel thinks it's criminal that ChatGPT isn’t inherently social.There’s no easy way to discover great prompts or share the ones that worked. As a venture partner at Benchmark, Sarah believes that the next wave of consumer AI will be built on this missing social layer—by product-driven founders who understand people, not just models. Sarah has seen this shift before. As one of Pinterest’s first product managers, she saw the company grow from a niche consumer tool to a beloved global community. On this episode of Every's podcast AI & I, we talk about how she’s applying the lessons she learned to AI—and what it takes to build a breakout consumer AI app today. We get into:Why product geniuses win as new tech matures. In the early days of a new technology, companies win by wrangling raw innovation into something usable. But as the infrastructure matures, Sarah says the edge shifts to product thinkers—founders who turn new capabilities into delightful user experiences.The future of prompting is social. When Sarah had to dig through Reddit to find a prompt to help her interpret her blood test results, she saw a gap: The best prompt creators are invisible. Sarah bets that a social AI product that makes them discoverable and followable would gain traction.Sarah’s method to spot exceptional founders. Sarah backs founders for whom building a company feels like a calling—or even an affliction. These are people who have fallen in love with the process and are obsessed with learning how to grow alongside their companies.How to tell if your startup really has network effects. Founders raising money love to say that their business has “network effects.” Sarah has learned to look for early signs they’re real—like traction in a small, white-hot segment of the market. If there’s no evidence the flywheel is already starting to spin, it’s probably not a network effect.How LLMs change the way the best VCs invest. Sarah thinks the future of venture will be shaped by how well VCs can turn the decisions they make into training data. After every pitch, she logs what she liked, what she didn’t, the deal terms, and her reasoning. Over time, she’s building a dataset of her own judgment—one an LLM could help her use to pressure-test decisions and avoid past mistakes.This is a must-listen for if you’re building a consumer AI product and want to see ahead of the curve.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 Sponsor:Attio: Go to⁠⁠ https://www.⁠⁠⁠⁠attio.com/every⁠⁠⁠ and get 15% off your first year on your AI-powered CRM.Timestamps:Introduction: 00:01:10Why the future of consumer AI belongs to founders with product intuition: 00:02:26What Sarah sees as ChatGPT’s biggest weakness: 00:11:09How Sarah would design a consumer AI app with social DNA: 00:18:45The kind of founders Sarah invests in: 00:25:04How to know if your startup’s network-effects are real: 00:29:26What’s catching Sarah’s eye beyond AI: 00:36:33How AI will change the way top venture capitalists invest: 00:41:35Links to resources mentioned in the episode:Sarah Tavel: @sarahtavelSarah’s substack: https://www.sarahtavel.com/ Eugene Wei’s essay about Status-as-a-Service: https://www.eugenewei.com/blog/2019/2/19/status-as-a-service The book Sarah talks about in the context of founders who become CEOs in pursuit of status: The Five Temptations of a CEO

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• How to Predict the Future With Kevin Kelly, WIRED's Cofounder

  Kevin Kelly has spent more time thinking about the future than almost anyone else.From VR in the 1980s to the blockchain in the 2000s—and now generative AI—Kevin has spent a lifetime journeying to the frontiers of technology, only to return with rich stories about what’s next.Today, as Wired's senior maverick, his project for 2025 is to outline what the next century looks like in a world shaped by new technologies like AI and genetic engineering. He’s a personal hero of mine—not to mention a fellow Annie Dillard fan—and it was a privilege to have him on the show. We get into:How you can predict the future. According to Kevin, the draw of new frontiers—from the first edition of Burning Man and remote corners of Asia, to the early days of the internet and AI—isn’t staying at the edge forever; it's returning with a story to tell.Why history is so important to help you understand the future To stay grounded while exploring what’s new, Kevin balances the thrill of the future with the wisdom of the past. He pairs AI research with reading about history, and playing with an AI tool by retreating to his workshop to make something with his hands.From 1,000 true fans to an audience of one. Rather than creating for an audience, Kevin has been using LLMs to explore his own imagination. After realizing that da Vinci, Martin Luther, and Columbus were alive at the same time, he asked ChatGPT to imagine them snowed in at a hotel together, and the prompt spiraled into an epic saga, co-written with AI. But he has no plans to publish it because the joy was in creating something just for himself.What the history of electricity can teach us about AI. Kevin draws a parallel between AI and the early days of electricity. We could produce electric sparks long before we understood the forces that created them, and now we’re building intelligent machines without really understanding what intelligence is.Why Kevin sees intelligence as a mosaic—not a monolith. Kevin believes intelligence isn’t a single force, but a compound of many cognitive elements. He draws from Marvin Minsky’s “society of mind”—the theory that the mind is made up of smaller agents working together—and sees echoes of this in the Mixture of Experts architecture used in some models today.Your competitive advantage is being yourself. Don’t aim to be the best—aim to be the only. Kevin realized the stories no one else at Wired wanted to write were often the ones he was suited for, and trusting that instinct led to some of his best work.This is a must-watch for anyone who wants to make sense of AI through the lens of history, learn how to spot the future before it arrives, or grew up reading Wired.If you found this episode interesting, please like, subscribe, comment, and share! To hear more from Dan:Subscribe to Every: https://every.to/subscribe Follow him on X: https://twitter.com/danshipper SponsorsVanta: Get $1,000 off of Vanta at ⁠⁠⁠https://www.vanta.com/every⁠⁠⁠ and automate up to 90% of the work for SOC 2, ISO 27001, and more.Attio: Go to⁠ https://www.⁠⁠⁠⁠attio.com/every⁠⁠ and get 15% off your first year on your AI-powered CRM.Timestamps:Introduction: 00:00:50Why Kevin and I love Annie Dillard: 00:01:10Learn how to predict the future like Kevin: 00:12:50What the history of electricity can teach us about AI: 00:16:08How Kevin thinks about the nature of intelligence: 00:20:11Kevin’s advice on discovering your competitive advantage: 00:27:21The story of how Kevin assembled a bench of star writers for Wired: 00:31:07How Kevin used ChatGPT to co-create a book: 00:36:17Using AI as a mirror for your mind: 00:40:45What Kevin learned from betting on VR in the 1980s: 00:45:16Links to resources mentioned:Kevin Kelly: @kevin2kellyKelly’s books: https://kk.org/books Annie Dillard books that Kelly and Dan discuss: Pilgrim at Tinker Creek, Teaching a Stone to Talk, Holy the Firm, The Writing LifeDillard’s account of the total eclipse: "Total Eclipse"

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  53:41

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