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.
Read more at every.to.
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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?
Itβs 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. Itβs your βnon-consensusβ 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 weekβs episode of The Every Podcast, weβre sharing Danβs 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
OpenAIβs 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
The Inside Story of the 50 Who Built Modern AI With Kevin Roose
Wednesday, November 4, 2026 β’ Duration 46:14
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 ofΒ how modern AI was built and the choices that will determine what comes next.Β
On this weekβs 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 didnβt) use AI in his book writing process, and why he sees his job as explaining the βvery confusing and insularβ world of Silicon Valley to everyone else.
Links to resources mentioned in the episode:
Follow Kevin Roose: https://x.com/kevinroose
Get Kevin Rooseβs book, The AGI Chronicles: https://theagichronicles.com/
Machine Gods: https://www.npr.org/podcasts/g-s1-143588/machine-godsΒ
βThe Big Blob of Compute Hypothesisβ excerpt on Kevinβs Substack: https://kevinroose.substack.com/p/the-essay-that-started-the-ai-raceΒ
Profiles of the Future by Arthur C. Clarke: https://www.amazon.com/Profiles-Future-Inquiry-Limits-Possible/dp/0575402776Β
The Making of the Atomic Bomb by Richard Rhodes: https://www.amazon.com/Making-Atomic-Bomb-Richard-Rhodes/dp/1451677618Β
NotebookLM: https://notebook.google/
Timestamps:
0:00 IntroductionΒ
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 disappearedΒ
10:45 How Roose got 150 sources in a secretive industry to open upΒ
13:49 Dario Amodeiβs βBig Blob of Computeβ memoΒ
19:12 How Rooseβs motherβs book on the survivors of the atomic bomb influenced his work
21:40 The moment Roose first βfelt the AGIβΒ
23:24 How a βcouncil of Claudesβ fact-checked Rooseβs bookΒ
31:59 Launching Machine Gods and reinventing video journalismΒ
41:41 Weightlifting versus forklifting: How Roose decides what to hand off to AI
Can You Use AI To Make Good Art? β With Fred Graver
Wednesday, October 28, 2026 β’ Duration 50:51
Subscribe to Every (free for 14 days): https://every.to/youtube-every-offer
Can AI create good art?Β
Fred Graver thinks the answer depends on you. The Emmy Awardβwinning writer, producer, and founder of AI Writerβs Studio says AI can help with many parts of the creative processβbut it canβt give you something to say. Without your own point of view, AI will only make your work more average.
On this weekβs episode of The Every Podcast, Natalia Quintero sits down with Graver. They discuss why every writer should have a βwho I am as a writerβ document, the cast of AI collaborators heβs built into his own writersβ room, and the human quirks that make characters endearingβthe part he insists AI canβt supply.
Get Fredβs Skill: https://every.to/context-window/every-model-has-a-six-month-shelf-life-now
Links to resources mentioned in the episode:Β
β’ Follow Every: https://x.com/everyΒ
β’ Follow Natalia Quintero: https://x.com/NataliaZarinaΒ
β’ Follow Fred Graver: https://x.com/fredgraver
β’ AI Writers Studio: https://aiwritersstudio.substack.com/
β’ Compound Writing plugin: https://every.to/guides/compound-writingΒ
β’ Compound Engineering plugin: https://every.to/guides/compound-engineering
β’ Thesis conference: https://every.to/thesis-2027
β’ Follow Katie Parrott: https://x.com/kplikethebirdΒ
β’ Follow Kieran Klaassen: https://x.com/kieranklaassen
β’ Follow Dan Shipper: https://x.com/danshipper
Timestamps:
0:00 Introduction
2:22 Fredβs path from National Lampoon and Letterman to Twitter and Microsoft
7:47 The βI want inβ 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 writersβ 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 Fredβs thesis: Success is knowing what the audience wants before it does
43:44 Fredβs day-to-day workflow across Claude, ChatGPT, and NotebookLM
How a Frontier Team Can Help Your Company Keep Up With AI
Wednesday, October 21, 2026 β’ Duration 43:01
Check out Gemini Audio: https://goo.gle/Every-Gemini-Audio
Every time a new AI model drops, companies face the same dilemma: Figure out whatβs 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 weekβs episode of The Every Podcast, Natalia Quintero sits down with all seven members of Everyβs frontier team to ask what theyβre buildingβfrom a tabless browser that helps protect your attention to a personal agent orchestrator called Mingaβand 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
Everyβs 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 architectsΒ
4:57 How Head of Evals Mike Taylor builds personal benchmarksΒ
6:46 How Opus edited an explainer video using Slack messages and meeting notesΒ
10:20 Working with AI means protecting other peopleβs attentionΒ
12:26 Why a frontier team needs a βwranglerβ like Arielle ShipperΒ
18:58 Why senior editor Jack Cheng built a tabless browserΒ
24:37 How resident writer Katie Parrott teaches her AI writing plugin who the reader is
30:51 Inside engineer Jannik Jungβs personal AI orchestratorΒ
35:41 Compound engineer Kieran Klaassen uses AI to build power tools
How Hugging Faceβs Investor Spots Winners
Wednesday, October 14, 2026 β’ Duration 51:02
Check out Gemini Audio: https://goo.gle/Every-Gemini-Audio
Bet on founders who understand the technology, because their first idea probably wonβt be the one that sticks.
Thatβs 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 itβs the largest hub for open-source AI, and Nvidia has agreed to buy it for about $13 billion.
On this weekβs episode of The Every Podcast, Hartman tells Natalia Quintero how backing Hugging Face shaped his investment thesis, how Factorial grew into a βfamily treeβ 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 Hartmanβs approach to finding the newly technically possible
18:10 Why Hartman backs technical founders
21:10 How Factorialβs 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 Hartmanβs current theses, from non-language models to full-stack AI apps
44:14 Why the best founders right now are experimenting
Why Every Traded Personal Agents for One Company Agent
Wednesday, October 7, 2026 β’ Duration 33:46
Subscribe to Every (free for 14 days): every.to/podcast-every-offer?utm_source=podcast&utm_medium=audio&utm_campaign=companyagentepisodeΒ
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 agentβand where they think personal agents belong in everyday life.Β
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
Everyβs 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 EveryΒ
11:13 Why everyone's personal agents eventually diedΒ
14:51 The difference between building for builders and building for operatorsΒ
16:20 Why work will run on company agents while personal agents will stay personalΒ
19:56 How engineering management has changed in the age of AIΒ
21:43 Using an AI-powered feed to see everything happening across a product launchΒ
23:53 Why Willie's token usage fell off a cliffΒ
29:05 The benefit of having separate AI coaches for each part of your lifeΒ
31:45 How Every is building its agent to surface information unprompted
How Sam Altman Uses Dots to Take Back His Time
Wednesday, September 30, 2026 β’ Duration 33:10
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 morningsβhis window of "maximum creativity"βto 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:
β’ Subscribe to Every: https://every.to/subscribeΒ
β’ Follow him on X: https://twitter.com/danshipper
Chapters:
00:00:00 Introduction
00:00:55 Why AI hasnβt replaced developers
00:04:45 OpenAIβs platform bet on the rise of small-team companies
00:05:45 Why the AI era is more βRenaissanceβ than βIndustrial Revolutionβ
00:07:40 How Samβs Dot, OpenAIβs always-on AI agent, gave him back his mornings
00:12:00 Samβs process for building new features with his Dot
00:16:00 Inside OpenAIβs βlive documentsβ that agents and humans can build together
00:20:55 What bring-your-own-subscription changes for app developers
00:24:00 Why βOpenAI just killed X startupβ never comes true
00:27:55 Samβs life on Ultrafast and the push to make speed as cheap as intelligence
Links to resources mentioned in the episode:
β’ Sam Altman on X: https://x.com/samaΒ
β’ Codex: https://openai.com/codexΒ
β’ Space: https://help.openai.com/en/articles/20001549-getting-started-with-space-in-chatgpt
β’ Every's Vibe Check on Dots: https://every.to/vibe-check/vibe-check-dots-always-on-agents-in-chatgpt?utm_source=podcast
β’ Every's Vibe Check on OpenAI DevDay 2026: https://every.to/vibe-check/vibe-check-openai-devday-2026?utm_source=podcast
How a Professional Writer Writes With AI
Episode 129
Wednesday, September 2, 2026 β’ Duration 47:58
Two years ago, Katie Parrott was laid off from a crypto firm and couldnβt afford a career coachβso she turned to a $20-a-month ChatGPT subscription instead.
The Every staff writerβs 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 weekβs 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 βcontent agency of oneβ
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 βcomputer errandsβ
27:03 Katieβs 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 Katieβs 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-writingβ
Compound engineering plugin (Kieran Klassen): github.com/EveryInc/compound-engineering-plugin
Parrottβs companion piece on compound writing: https://every.to/guides/compound-writing
Parrott, βI Hired ChatGPT as My Career Coachβ: every.to/working-overtime/i-hired-chatgpt-as-my-career-coach
Parrott, βAI Turned Me Into a Content Agency of Oneβ: every.to/working-overtime/ai-turned-me-into-a-content-agency-of-one
A $10B Hedge Fundβs AI Playbook (Best of the Pod)
Episode 128
Wednesday, August 26, 2026 β’ Duration 01:07:06
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 marketsβand 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 wasnβt perfect. His use of AI is public and effusive, including in a firm-wide email that opened with βI used ChatGPT to write this email. You should be using it, too, and be proud of it.β AI informs how Walleye drafts memos and selects stocks.
On Everyβs AI & I, Dan Shipper spoke with England about why heβs betting his entire organization on AI, why βresults are what matterβ 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.Β
Timestamps:
0:00 Start
0:51 Introduction
3:25 What pushed Will to go all in on AI
15:15 Inside the βAI-firstβ memo Will shared at Walleye
17:02 Why you shouldnβt be afraid of using AI for work
31:25 How Will uses LLMs to sharpen his thinking
35:57 Walleyeβs approach to using AI to reduce risk
39:35 What history can teach us about leading through change
57:10 Willβs first principles for making better decisions
59:23 Why Will journals every dayβand how AI makes it easier
Links to resources mentioned in the episode:
Will England/Walleye Capital: https://walleyecapital.com/bio/will-england
Everyβs AI toolsβMonologue, Cora, Spiral, and Sparkle: https://every.to/studio
Everyβs AI consulting: https://every.to/consulting
The AI Alien Companion App That's Bringing In $4M a Year (Best of the Pod)
Episode 127
Wednesday, August 19, 2026 β’ Duration 01:22:08
LLMs are a new medium for storytelling.
Thatβs 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 theyβre 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.Β
On this weekβs 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.Β
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 promptsβthey'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
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