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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:
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:
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
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