
Free Daily Podcast Summary
by Dan Shipper
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.
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Check out Gemini Audio: https://goo.gle/Every-Gemini-Audio Every time a new AI model drops, companies face the same dilemma: Figure out what’s new and how to use it, or focus on getting work done. Every solves this dilemma with a frontier team: a small group that tests new models and turns useful experiments into tools and workflows for the rest of the company. On this week’s episode of The Every Podcast, Natalia Quintero sits down with all seven members of Every’s frontier team to ask what they’re building—from a tabless browser that helps protect your attention to a personal agent orchestrator called Minga—and what they want to try next. Subscribe to Every (free for 14 days): https://every.to/youtube-every-offer?utm_source=podcast&utm_medium=audio&utm_campaign=companyagentepisode Links to resources mentioned in the episode: Follow Every: https://x.com/every Compound Writing plugin: https://every.to/guides/compound-writing Every’s vibe checks: https://every.to/vibe-check Follow Dan Shipper: https://x.com/danshipper Follow Natalia Quintero: https://x.com/NataliaZarina Follow Mike Taylor: https://x.com/hammer_mt Follow Jack Cheng: https://x.com/jackcheng Follow Arielle Shipper: https://x.com/ArielleShipper Follow Katie Parrott: https://x.com/kplikethebird Follow Jannik Jung: https://x.com/JannikJung 0:00 Introduction: Why every company needs a frontier team 2:42 Why the best frontier teams have pirates and architects 4:57 How Head of Evals Mike Taylor builds personal benchmarks 6:46 How Opus edited an explainer video using Slack messages and meeting notes 10:20 Working with AI means protecting other people’s attention 12:26 Why a frontier team needs a “wrangler” like Arielle Shipper 18:58 Why senior editor Jack Cheng built a tabless browser 24:37 How resident writer Katie Parrott teaches her AI writing plugin who the reader is 30:51 Inside engineer Jannik Jung’s personal AI orchestrator 35:41 Compound engineer Kieran Klaassen uses AI to build power tools
Check out Gemini Audio: https://goo.gle/Every-Gemini-Audio Bet on founders who understand the technology, because their first idea probably won’t be the one that sticks. That’s the view of Matt Hartman, founder and managing partner of Factorial Capital. In 2016, as a partner at Betaworks, Hartman was part of the team that wrote the first check into Hugging Face, which was then a chatbot app for teenagers. Today it’s the largest hub for open-source AI, and Nvidia has agreed to buy it for about $13 billion. On this week’s episode of The Every Podcast, Hartman tells Natalia Quintero how backing Hugging Face shaped his investment thesis, how Factorial grew into a “family tree” of technical founders who help him scout deals, and why vibe-coding his own app gave him a new respect for SaaS. Subscribe to Every (free for 14 days): https://every.to/podcast-every-offer?utm_source=podcast&utm_medium=audio&utm_campaign=matthartmanepisode Links to resources mentioned in the episode: Factorial Capital: https://factorialcap.com Ghost Pepper, Matt's open-source voice-to-text app: https://github.com/matthartman/ghost-pepper Superpowers, Jesse Vincent's skill for Claude Code: https://github.com/obra/superpowers Hugging Face: https://huggingface.co Follow Every: https://x.com/every Follow Natalia Quintero: https://x.com/NataliaZarina Follow Matt Hartman: https://x.com/MattHartman 0:00 Introduction 5:06 How Hugging Face went from a teen chatbot to the home of open-source AI 9:52 The three decisions that set Hugging Face on its path 12:49 Hartman’s approach to finding the newly technically possible 18:10 Why Hartman backs technical founders 21:10 How Factorial’s portfolio founders source its next deals 27:09 Why faster iteration makes product insight the most valuable skill 34:28 What Hartman learned building Ghost Pepper, an open-source voice-to-text app 40:02 Hartman’s current theses, from non-language models to full-stack AI apps 44:14 Why the best founders right now are experimenting
Subscribe to Every (free for 14 days): every.to/podcast-every-offer?utm_source=podcast&utm_medium=audio&utm_campaign=companyagentepisode On this week's episode of The Every Podcast, Dan Shipper sits down with Willie Williams, Every's head of platform and one of the driving forces behind the Every Agent, which launched this week. They discuss how Every went from everyone running their own OpenClaw to relying on one shared company agent—and where they think personal agents belong in everyday life. Links to resources mentioned in the episode: Willie Williams on X: https://x.com/bigwilliestyle The Every Agent: https://every.to/agent?utm_source=podcast&utm_campaign=podcast&utm_content=1006companyagent OpenClaw: https://openclaw.ai Tend, Dan's open-source feed app: https://every.to/tend?utm_source=podcast&utm_campaign=podcast&utm_content=1006companyagent Every’s Vibe Check on Dots: https://every.to/vibe-check/vibe-check-dots-always-on-agents-in-chatgpt?utm_source=podcast&utm_campaign=podcast&utm_content=1006companyagent Dot from OpenAI: https://openai.com/index/introducing-dots/ 0:00 Introduction 5:58 How OpenClaw spread through Every 11:13 Why everyone's personal agents eventually died 14:51 The difference between building for builders and building for operators 16:20 Why work will run on company agents while personal agents will stay personal 19:56 How engineering management has changed in the age of AI 21:43 Using an AI-powered feed to see everything happening across a product launch 23:53 Why Willie's token usage fell off a cliff 29:05 The benefit of having separate AI coaches for each part of your life 31:45 How Every is building its agent to surface information unprompted
Sam Altman's Dot, OpenAI's new always-on agent, gave him back the most productive part of his day. The OpenAI CEO would lose his early mornings—his window of "maximum creativity"—to whatever fire needed putting out. Now, his Dot triages those issues and flags only what's truly urgent. It's also gotten him building again: In spare moments, he gives his Dot ideas for a feature, and his Dot builds five or six versions for him to review. On the first episode of The Every Podcast (formerly AI & I), Dan Shipper interviews Altman at OpenAI's DevDay. They discuss how Altman uses his Dot to protect his time, why he only prompts on Ultrafast, and his belief that AI will spark a new Renaissance. If you found this episode interesting, please like, subscribe, comment, and share! To hear more from Dan Shipper: • Subscribe to Every: https://every.to/subscribe • Follow him on X: https://twitter.com/danshipper Chapters: 00:00:00 Introduction 00:00:55 Why AI hasn’t replaced developers 00:04:45 OpenAI’s platform bet on the rise of small-team companies 00:05:45 Why the AI era is more “Renaissance” than “Industrial Revolution” 00:07:40 How Sam’s Dot, OpenAI’s always-on AI agent, gave him back his mornings 00:12:00 Sam’s process for building new features with his Dot 00:16:00 Inside OpenAI’s “live documents” that agents and humans can build together 00:20:55 What bring-your-own-subscription changes for app developers 00:24:00 Why “OpenAI just killed X startup” never comes true 00:27:55 Sam’s life on Ultrafast and the push to make speed as cheap as intelligence Links to resources mentioned in the episode: • Sam Altman on X: https://x.com/sama • Codex: https://openai.com/codex • Space: https://help.openai.com/en/articles/20001549-getting-started-with-space-in-chatgpt • Every's Vibe Check on Dots: https://every.to/vibe-check/vibe-check-dots-always-on-agents-in-chatgpt?utm_source=podcast • Every's Vibe Check on OpenAI DevDay 2026: https://every.to/vibe-check/vibe-check-openai-devday-2026?utm_source=podcast
Two years ago, Katie Parrott was laid off from a crypto firm and couldn’t afford a career coach—so she turned to a $20-a-month ChatGPT subscription instead. The Every staff writer’s habit of feeding AI good context eventually became compound writing, a codified system for brainstorming, drafting, and editing with AI. Today, that system is a plugin any writer can use. On this week’s AI & I, Natalia Quintero talks with Katie about turning good ingredients into good writing, borrowing the taste of writers she admires, and why AI helped her fall back in love with the page. If you found this episode interesting, please like, subscribe, comment, and share! To hear more from Natalia Quintero: Subscribe to Every: https://every.to/subscribe Follow her on X: @NataliaZarina Go to https://attio.com/every and get 15% off your first year. Timestamps: 0:00 Start 0:49 Introduction 1:21 How Katie went from being laid off to using ChatGPT as a career coach 8:06 Turning AI into a “content agency of one” 10:59 Building the context files and style guides that make AI outputs useful 14:15 What makes a Claude project actually work 21:18 How AI helped with a mental health crisis and “computer errands” 27:03 Katie’s career coach, now a fully autonomous Codex project 32:27 What compounding means, and building the Compound Writing plugin 38:00 Borrowing Vonnegut, Hitchcock, and Sorkin as AI editing skills 44:49 Katie’s thesis: education and access will matter more than ever Links to resources mentioned in the episode: Katie Parrott on X: @kplikethebird Compound writing plugin: https://github.com/EveryInc/compound-writing Compound engineering plugin (Kieran Klassen): github.com/EveryInc/compound-engineering-plugin Parrott’s companion piece on compound writing: https://every.to/guides/compound-writing Parrott, “I Hired ChatGPT as My Career Coach”: every.to/working-overtime/i-hired-chatgpt-as-my-career-coach Parrott, “AI Turned Me Into a Content Agency of One”: every.to/working-overtime/ai-turned-me-into-a-content-agency-of-one
Two years ago, Katie Parrott was laid off from a crypto firm and couldn’t afford a career coach — so she turned to a $20-a-month ChatGPT subscription instead.The Every staff writer’s habit of feeding AI good context eventually became compound writing, a codified system for brainstorming, drafting, and editing with AI. Today, that system is a plugin any writer can use.On this week’s AI & I, Natalia Quintero talks with Katie about turning good ingredients into good writing, borrowing the taste of writers she admires, and why AI helped her fall back in love with the page.If you found this episode interesting, please like, subscribe, comment, and share!To hear more from Natalia Quintero:Subscribe to Every: https://every.to/subscribeFollow her on X: @NataliaZarinaTimestamps for YouTube:0:00 Start0:49 Introduction1:21 How Katie went from being laid off to using ChatGPT as a career coach8:06 Turning AI into a “content agency of one”10:59 Building the context files and style guides that make AI outputs useful14:15 What makes a Claude project actually work21:18 How AI helped with a mental health crisis and “computer errands”27:03 Katie’s career coach, now a fully autonomous Codex project32:27 What compounding means, and building the Compound Writing plugin38:00 Borrowing Vonnegut, Hitchcock, and Sorkin as AI editing skills44:49 Katie’s thesis: education and access will matter more than everLinks to resources mentioned in the episode:Katie Parrott on X: @kplikethebirdCompound writing plugin: [LINK COMING SOON]Compound engineering plugin (Kieran Klassen): github.com/EveryInc/compound-engineering-pluginParrott’s companion piece on compound writing: [LINK COMING SOON]Parrott, “I Hired ChatGPT as My Career Coach”: every.to/working-overtime/i-hired-chatgpt-as-my-career-coachParrott, “AI Turned Me Into a Content Agency of One”: every.to/working-overtime/ai-turned-me-into-a-content-agency-of-one
Will England is the CEO of Walleye Capital, a hedge fund managing nearly $10 billion in assets. An engineer by training with a math background from Oxford, he has spent his career at the intersection of machines and markets—and has made AI fluency mandatory for all 400 employees.England believes refusing to use AI is like refusing to use the internet in 1995 because it wasn’t perfect. His use of AI is public and effusive, including in a firm-wide email that opened with “I used ChatGPT to write this email. You should be using it, too, and be proud of it.” AI informs how Walleye drafts memos and selects stocks.On Every’s AI & I, Dan Shipper spoke with England about why he’s betting his entire organization on AI, why “results are what matter” more than blood, sweat, and tears, and what the American frontier can teach us about leading through technological change.Like, subscribe, comment, and share!To hear more from Dan Shipper:Subscribe to Every: https://every.to/subscribeFollow Dan Shipper on X: https://twitter.com/danshipperGo to https://attio.com/every and get 15% off your first year. Timestamps:0:00 Start0:51 Introduction3:25 What pushed Will to go all in on AI15:15 Inside the ‘AI-first’ memo Will shared at Walleye17:02 Why you shouldn’t be afraid of using AI for work31:25 How Will uses LLMs to sharpen his thinking35:57 Walleye’s approach to using AI to reduce risk39:35 What history can teach us about leading through change57:10 Will’s first principles for making better decisions59:23 Why Will journals every day—and how AI makes it easierLinks to resources mentioned in the episode:Will England/Walleye Capital: https://walleyecapital.com/bio/will-englandEvery’s AI tools—Monologue, Cora, Spiral, and Sparkle: https://every.to/studioEvery’s AI consulting: https://every.to/consulting
Will England is the CEO of Walleye Capital, a hedge fund managing nearly $10 billion in assets. An engineer by training with a math background from Oxford, he has spent his career at the intersection of machines and markets—and has made AI fluency mandatory for all 400 employees. England believes refusing to use AI is like refusing to use the internet in 1995 because it wasn’t perfect. His use of AI is public and effusive, including in a firm-wide email that opened with “I used ChatGPT to write this email. You should be using it, too, and be proud of it.” AI informs how Walleye drafts memos and selects stocks. On Every’s AI & I, Dan Shipper spoke with England about why he’s betting his entire organization on AI, why “results are what matter” more than blood, sweat, and tears, and what the American frontier can teach us about leading through technological change. Like, subscribe, comment, and share! To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe Follow Dan Shipper on X: https://twitter.com/danshipper Go to https://attio.com/every and get 15% off your first year. Timestamps: 0:00 Start 0:51 Introduction 3:25 What pushed Will to go all in on AI 15:15 Inside the ‘AI-first’ memo Will shared at Walleye 17:02 Why you shouldn’t be afraid of using AI for work 31:25 How Will uses LLMs to sharpen his thinking 35:57 Walleye’s approach to using AI to reduce risk 39:35 What history can teach us about leading through change 57:10 Will’s first principles for making better decisions 59:23 Why Will journals every day—and how AI makes it easier Links to resources mentioned in the episode: Will England/Walleye Capital: https://walleyecapital.com/bio/will-england Every’s AI tools—Monologue, Cora, Spiral, and Sparkle: https://every.to/studio Every’s AI consulting: https://every.to/consulting
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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.
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