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How did the race to build AGI really unfold, and who made the decisions that shaped it? Tech journalist Kevin Roose interviewed 150 people at the center of the AI industry to find out. The result is The AGI Chronicles, a riveting account of  how modern AI was built and the choices that will determine what comes next.  On this week’s episode of The Every Podcast, Natalia Quintero sits down with Roose to talk about how he got a secretive industry to open up, how he did (and didn’t) use AI in his book writing process, and why he sees his job as explaining the “very confusing and insular” world of Silicon Valley to everyone else. Links to resources mentioned in the episode: Follow Kevin Roose: https://x.com/kevinroose Get Kevin Roose’s book, The AGI Chronicles: https://theagichronicles.com/ Machine Gods: https://www.npr.org/podcasts/g-s1-143588/machine-gods  “The Big Blob of Compute Hypothesis” excerpt on Kevin’s Substack: https://kevinroose.substack.com/p/the-essay-that-started-the-ai-race  Profiles of the Future by Arthur C. Clarke: https://www.amazon.com/Profiles-Future-Inquiry-Limits-Possible/dp/0575402776  The Making of the Atomic Bomb by Richard Rhodes: https://www.amazon.com/Making-Atomic-Bomb-Richard-Rhodes/dp/1451677618  NotebookLM: https://notebook.google/ Timestamps: 0:00 Introduction  2:23 Are we doomed? Roose on AI risk and the case for mandatory safety testing 7:13 Why Roose raced to write the history of AGI before the records disappeared  10:45 How Roose got 150 sources in a secretive industry to open up  13:49 Dario Amodei’s “Big Blob of Compute” memo  19:12 How Roose’s mother’s book on the survivors of the atomic bomb influenced his work 21:40 The moment Roose first “felt the AGI”  23:24 How a “council of Claudes” fact-checked Roose’s book  31:59 Launching Machine Gods and reinventing video journalism  41:41 Weightlifting versus forklifting: How Roose decides what to hand off to AI

Subscribe to Every (free for 14 days): https://every.to/youtube-every-offer Can AI create good art?  Fred Graver thinks the answer depends on you. The Emmy Award–winning writer, producer, and founder of AI Writer’s Studio says AI can help with many parts of the creative process—but it can’t give you something to say. Without your own point of view, AI will only make your work more average. On this week’s episode of The Every Podcast, Natalia Quintero sits down with Graver. They discuss why every writer should have a ‘who I am as a writer’ document, the cast of AI collaborators he’s built into his own writers’ room, and the human quirks that make characters endearing—the part he insists AI can’t supply. Get Fred’s Skill: https://every.to/context-window/every-model-has-a-six-month-shelf-life-now Links to resources mentioned in the episode:  • Follow Every: https://x.com/every  • Follow Natalia Quintero: https://x.com/NataliaZarina  • Follow Fred Graver: https://x.com/fredgraver • AI Writers Studio: https://aiwritersstudio.substack.com/ • Compound Writing plugin: https://every.to/guides/compound-writing  • Compound Engineering plugin: https://every.to/guides/compound-engineering • Thesis conference: https://every.to/thesis-2027 • Follow Katie Parrott: https://x.com/kplikethebird  • Follow Kieran Klaassen: https://x.com/kieranklaassen • Follow Dan Shipper: https://x.com/danshipper Timestamps: 0:00 Introduction 2:22 Fred’s path from National Lampoon and Letterman to Twitter and Microsoft 7:47 The “I want in” instinct behind every career pivot 12:19 How Best Week Ever taught Fred to build with the audience 13:26 Using AI as a virtual writers’ room, not a ghostwriter 16:07 Codifying industry expertise and studio culture into an AI core 20:32 The three phases of making entertainment with AI 26:27 Why you should brain-dump your idea before opening AI 38:47 Fred’s thesis: Success is knowing what the audience wants before it does 43:44 Fred’s day-to-day workflow across Claude, ChatGPT, and NotebookLM

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! Go to https://attio.com/every and get 15% off your first year. 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

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

LLMs are a new medium for storytelling. That’s according to the creators of Portola, the company behind Tolan: an embodied AI companion that lives on its own planet and chats to you with a distinct personality. In 2025, Portola's founder and CEO Quinten Farmer and Head of Story Eliot Peper joined Dan Shipper to explain how they’re building this new medium from scratch. Their aim is to help users go from overwhelmed to grounded through conversations with Tolan that feel personal and spontaneous, not scripted.  On this week’s AI & I, Dan revisits his conversation with Quinten and Eliot. They discuss why response time is everything for voice-based AI interfaces, how Portola designs AI personalities users will click with, and why character-driven AI could become a new computing interface.  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 Go to https://attio.com/every and get 15% off your first year. Timestamps: 00:01:30 - Introduction 00:04:07 - Talking to the Portola CEO's Tolan, Clarence 00:09:11 - How Portola went from building software for kids to AI companions 00:23:40 - Why response time is everything for voice-based AI interfaces 00:29:54 - Tolans don't use scripted prompts—they're taught to improvise 00:37:23 - How to know which AI personalities your users will click with 00:42:27 - Developing the character traits of an AI companion 00:49:48 - What does it mean to build technology that makes us flourish 01:01:10 - How Portola evaluates whether Tolans are resonating with users 01:11:01 - Inside Portola's viral growth strategy

In 2025, Kevin Scott bet that the agentic web would be the next big thing in AI. The Microsoft CTO argued that for agents to be genuinely useful, they'd need to be able to take action on our behalf—which would mean giving them access to the same sprawl of tools, data, and systems that make up the internet. Today, that bet is starting to pay off, as the foundational infrastructure for the agentic web is now being built. On this week's AI & I, Dan Shipper revisits his conversation with Kevin. They discuss Microsoft's role in the agentic web, why openness doesn't have to come at the expense of security, and why programmers should stay curious about new tools rather than resist them on principle. 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 Go to https://attio.com/every and get 15% off your first year. Timestamps:  0:00 Start 1:44 Introduction 2:49 The race to close the "capability overhang" 4:31 How agents will evolve into practical, useful tools 6:48 The role Kevin sees Microsoft playing in the agent ecosystem 12:05 How robust security measures can coexist with open ecosystems 15:39 Kevin's philosophy on being a craftsman in the age of agents 20:52 How the landscape of software development agents will evolve 25:33 The future of agentic workflows Links to resources mentioned in the episode: Kevin Scott on X: https://twitter.com/kevin_scott Model Context Protocol (MCP): https://modelcontextprotocol.io NLWeb: https://github.com/microsoft/NLWeb GitHub Copilot: https://github.com/features/copilot

Most consumer AI so far has been single-player: you and a chatbot, alone. Benchmark partner Sarah Tavel, one of Pinterest's first 30 employees, is betting that's about to change. She's looking for a product genius who can build an AI product with social DNA: status, network effects, and multiplayer dynamics. That'll enable users of ChatGPT and other models to learn from how others use AI and level up. On this week’s AI & I, Dan Shipper revisits his conversation with Sarah. They talk about why technical founders dominate the early days of a platform shift while product-minded founders win later, what ChatGPT is still missing, and what separates a founder's real network effect from a slide with a flywheel diagram. 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 Timestamps for YouTube: 0:00 Start 1:10 Introduction 2:26 Why the future of consumer AI belongs to founders with product intuition 11:09 What Sarah sees as ChatGPT's biggest weakness 18:45 How Sarah would design a consumer AI app with social DNA 24:10 The kind of founders Sarah invests in 28:33 How to know if your startup's network effects are real 35:40 What's catching Sarah's eye beyond AI 40:41 How AI will change the way top venture capitalists invest Links to resources mentioned in the episode: Sarah Tavel on X: https://x.com/sarahtavel Benchmark: https://benchmark.com Agentio (marketplace for YouTube creators and brands): https://agentio.com/  Chainalysis: https://chainalysis.com The Five Temptations of a CEO by Patrick Lencioni: https://www.amazon.com/dp/B007BZBRB8 Thinking in Bets by Annie Duke: https://www.amazon.com/dp/B0HBBW23PM

Kevin Kelly has spent over 30 years experiencing the edge of new technology: from the earliest days of the internet to the first years of Burning Man. But he’s always treated the frontier as a place to visit, not somewhere to live. It’s partially how he’s been able to stay grounded through tech’s various hype cycles. As founding executive editor of Wired and author of The Inevitable, Kelly spends as much time analyzing the latest in AI as he does reading about significant moments in history. It’s a discipline he traces back to his work with the Long Now Foundation, which he cofounded to encourage long-term thinking, reaching from the last 10,000 years to the next.  On this week’s AI & I, Dan Shipper revisits his conversation with Kelly. They get into why historians can be the best futurists, and how our bid to understand what intelligence is has parallels with early scientists' attempts to figure out electricity.  Kelly also describes the joy he found in creating an AI-generated saga featuring Leonardo Da Vinci, Christopher Columbus, and Martin Luther—one that will only ever be read and enjoyed by him. 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 Timestamps for YouTube: 0:00 Start  0:50 Introduction  1:10 Why Dan and Kelly love Annie Dillard  12:52 How to predict the future like Kelly 16:10 What the history of electricity can teach us about AI  20:13 How Kelly thinks about the nature of intelligence  25:44 Kelly's advice on discovering your competitive advantage  29:33 How Kelly assembled a bench of star writers for Wired  34:43 How Kelly used ChatGPT to co-create a book  39:12 Using AI as a mirror for your mind  43:43 What Kelly learned from betting on VR in the 1980s Links to resources mentioned in the episode: Kevin Kelly on X: https://twitter.com/kevin2kelly The Inevitable by Kevin Kelly: https://www.amazon.com/Inevitable-Understanding-Technological-Forces-Future/dp/0525428089 Pilgrim at Tinker Creek by Annie Dillard: https://www.amazon.com/Pilgrim-Tinker-Harper-Perennial-Classics/dp/0061233323 1,000 True Fans by Kevin Kelly: https://www.amazon.com/1000-True-Fans-Kellys-Simple-ebook/dp/B01N9P9O4G Full episode transcript: https://every.to/podcast/transcript-be243312-ea22-4193-8c56-b9cd45a79a87

Yash Poojary, a growth engineer at Every, dropped an idea for a campaign in Slack at 7 p.m. Instead of building it himself, Every’s head of growth Austin Tedesco took a screenshot of the Slack thread, dropped it into Codex, typed "Can you do this?", and went to the gym. By the time he got back, Codex had built four audience segments, drafted emails for each one, and pulled a social image that had worked before. It took Austin 10 minutes to make some tweaks and schedule the whole thing to send the next morning. Within a few hours, it generated more than $25,000 in revenue.  That story came out of the launch week for All Access, Every’s new $625-a-year membership built around the Builder Pack. It includes $7,000 in credits and free usage from ten of the AI products Every uses every day, including Claude Max, Codex, Cursor Pro+, PostHog, Notion, Framer, Render, and Flora. On this episode of AI & I, four of Every's own builders—COO Brandon Gell, head of marketing Douglas Brundage, as well as Yash and Austin—sit down to show how they use AI, breaking down their personal stacks and giving insight into their own strategies and mindset for building. 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 Timestamps for YouTube: 0:00 Intro  0:35 All Access Explained  3:01 Yash's Tech Stack and How He's Automating Testing Pipelines  8:02 The Idea to Execution Loop  10:25 How an Agent Turned an Idea into $25K  17:50 The AI Sandwich Workflow  22:03 Making AI Tools Accessible to Solo Builders  28:50 Douglas on Brand and Design 34:51 Tips on What to Build First  43:46 What's Next for All Access Links to resources mentioned in the episode: Brandon Gell on X: https://x.com/bran_don_gell Yash Poojary on X: https://x.com/poojary_yash Austin Tedesco on X: https://x.com/tedescau?lang=en Douglas Brundage on X: https://x.com/DABrundage Introducing Every All Access: https://every.to/on-every/introducing-every-all-access Get the Builder Pack: every.to/builder-pack  Go to https://attio.com/every and get 15% off your first year.

“Running a startup is a knife fight whether things are going well or not,” says Chris Pedregal, cofounder and CEO of Granola. Granola recently raised a $125 million series C round at a $1.5 billion valuation on the strength of its AI meeting notetaker. That valuation hasn’t made Pedregal complacent. Granola built its name as the first to make good AI meeting notes, but Notion, OpenAI, and Zoom have all since released their own versions. Pedregal isn’t rattled—he never thought meeting notes were the real prize. The bigger fight, he says, is over “what interface we use for work, and what work looks like in an AI-native world.” That’s why Granola is betting on owning the entire meeting workflow: preparing people for a call, helping them act on it afterward, and making that context available to whatever agent—Claude, Codex, or anything else—people bring to the table. Over the next few months, the company plans to push hard on its API and MCP to make that possible. Dan Shipper talked with Pedregal for AI & I about why Granola pre-generates millions of meeting briefs, most of which go unopened, what “bring your own agent” software could look like, and why Pedregal still thinks “easy come, easy go” about Granola’s own success. If you found this episode interesting, please like, subscribe, comment, and share. More from Dan Shipper: Subscribe to Every: https://every.to/subscribe Follow him on X: https://twitter.com/danshipper Timestamps: 00:00:59 Introduction 00:01:57 Why starting a company feels like a knife fight 00:04:33 Granola's counterintuitive view on competition 00:10:44 Dan's "pirate and architect" framework for structuring early-stage product teams 00:13:09 How Granola's "shaping" and "validation" phases work for building new features 00:18:17 Why Dan lives almost entirely inside Codex 00:24:40 The case for "Codex-native apps" 00:35:37 Granola's "handrail" philosophy 00:38:12 Why Granola is betting on owning meeting-adjacent context instead of competing as a general agent 00:44:19 What a transcript alone can never capture Episode resources: Chris Pedregal on X: https://twitter.com/cjpedregal Granola on X: https://twitter.com/meetgranola Granola: https://granola.ai Granola hits $1.5B valuation (TechCrunch): https://techcrunch.com/2026/03/25/granola-raises-125m-hits-1-5b-valuation-as-it-expands-from-meeting-notetaker-to-enterprise-ai-app/ Go to https://attio.com/every and get 15% off your first year.

Craig Mod used to pay Campaign Monitor roughly $7,000 a year to send his newsletters. After rebuilding the tool himself with AI, his bill is closer to $150. It’s the kind of thing that convinces him we’re about to enter a “golden age of tool building”—one where anyone can build tools specifically suited to their needs, instead of settling for software from incumbents that are slow to innovate. Mod is the writer and photographer behind the newsletters Roden and Ridgeline and books like Things Become Other Things and Kissa by Kissa—as well as a lifelong technologist. He’s rebuilt the tax software Quicken, created a private alternative for Twitter for his members which he calls The Good Place, and used AI to build an archive for his pop-up newsletters. But while Mod is an advocate of using AI to build, he draws the line at using it to write. Mod talks to Dan Shipper about using AI as a research assistant, why he keeps a tech-free zone in the mornings for deep thinking, and why he’s resisting the pull of the “mainlining” AI era. 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 Timestamps: 0:00 Introduction 3:51 Rebuilding Quicken and Campaign Monitor with AI 6:24 Building The Good Place, a private Twitter alternative for Craig’s members 10:39 Why we’re entering a “golden age of tool building” 12:17 Why AI could help writers build audiences 17:35 Using AI to build a newsletter archive and a searchable board-meeting Q&A library 27:58 Creating a technology-free buffer to protect deep thinking 30:31 Why Craig is resisting the temptation to “mainline” AI for ten hours a day 39:44 Why anthropomorphizing AI is “psychotic,” and why Apple got Siri right 47:42 Being adopted, and making peace with humanity’s fragile place in an AI future Go to https://attio.com/every and get 15% off your first year. Links to resources mentioned in the episode: Craig Mod’s website: https://craigmod.com Roden (Craig’s monthly newsletter): https://craigmod.com/roden/