How a Professional Writer Writes 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

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.

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