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by Dan Shipper
The Every Podcast is Every's flagship show. Co-hosts Dan Shipper and Natalia Quintero talk with founders, researchers, writers, and operators about what they're building and how they use AI in their own work. The show also takes you behind the scenes at Every. We share how our team is using and exploring AI, including what we're trying, what's working, and what we're learning along the way. Formerly known as AI & I.
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- 3 days ago26 min
A New Vision for Human Work After Automation
Thesis: 2027 is made possible by our founding partners, Lovable and Notion. Lovable is the fastest way to turn ideas into software people love: https://link.lovable.dev/every Notion is the collaborative AI workspace where teams and agents work side by side: https://www.notion.com/?utm_source=youtube&utm_campaign=thesis-2027&utm_content=every-261111-video What does great human work look like after automation? It’s a question we try to answer every day at Every, and the one we built our conference, Thesis, around. In his closing keynote, Dan Shipper argues that as AI makes intelligence cheap and widely available, what matters most is human perspective. It’s your “non-consensus” point of view, plus your responsibility for a particular corner of the world, that helps you spot the insight no one else would. On this week’s episode of The Every Podcast, we’re sharing Dan’s full talk at Thesis: 2027. Dan explains why benchmark charts make the future of work look bleaker than it is, why picking the right idea still takes a human, and how we should really measure AI models. Subscribe to Every (free for 14 days): https://every.to/youtube-every-offer?utm_source=podcast&utm_medium=audio&utm_campaign= (https://every.to/youtube-every-offer?utm_source=podcast&utm_medium=audio&utm_campaign=companyagentepisode)thesistalkepisode Links to resources mentioned in the episode: Thesis: https://every.to/thesis-2027 Dan Shipper: https://x.com/danshipper OpenAI’s GDPval benchmark: https://openai.com/index/gdpval/ Timestamps: 0:00 Introduction 1:51 Work after automation 5:00 1 person vs 5 jobs 10:18 Why perspective matters 17:55 Better AI, more valuable humans
- 1 weeks ago46 min
The Inside Story of the 50 Who Built Modern AI With Kevin Roose
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
- 2 weeks ago50 min
Can You Use AI To Make Good Art? — With Fred Graver
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
- 3 weeks ago43 min
How a Frontier Team Can Help Your Company Keep Up With AI
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
- Oct 14, 202651 min
How Hugging Face’s Investor Spots Winners
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
- Oct 7, 202633 min
Why Every Traded Personal Agents for One Company Agent
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
- Sep 30, 202633 min
How Sam Altman Uses Dots to Take Back His Time
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
- Sep 2, 202647 min
How a Professional Writer Writes With AI
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: @NataliaZarinaGo to https://attio.com/every and get 15% off your first year.Timestamps: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: https://github.com/EveryInc/compound-writing Compound engineering plugin (Kieran Klassen): github.com/EveryInc/compound-engineering-pluginParrott’s companion piece on compound writing: https://every.to/guides/compound-writingParrott, “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
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About The Every Podcast
The Every Podcast is Every's flagship show. Co-hosts Dan Shipper and Natalia Quintero talk with founders, researchers, writers, and operators about what they're building and how they use AI in their own work. The show also takes you behind the scenes at Every. We share how our team is using and exploring AI, including what we're trying, what's working, and what we're learning along the way. Formerly known as AI & I.
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