Stay ConnectedThe 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.
Copyright: © Dan Shipper
Dan Shipper runs one of the most AI-native companies today. Every has agents embedded in nearly every workflow—“if you swing a stick in our Slack, you're as likely to hit a human as an agent,” he says. And yet the company has grown from four people to 30 since GPT-3 came out, and is still hiring.
Why does Dan believe there's more human work to do than ever?
In a format flip for AI & I, Every's COO Brandon Gell turns the tables and interviews Dan about his latest essay, “After Automation”—an 8,000-word argument for why rising automation doesn't eliminate demand for human work, it increases it. The thesis: AI makes yesterday's expert competence cheap and widely available, which floods every field with output that's close but not quite right—and that creates more demand for the humans who can take it the rest of the way.
Dan talked with Brandon about the paradox at the heart of agent-native work: The more AI can do, the more humans are needed to direct it, refine its output, and decide what matters next.
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
Links to resources mentioned in the episode:
“After Automation” by Dan Shipper: https://every.to/chain-of-thought/after-automation
Brandon Gell on Every: https://every.to/@brandon_5263
Join the membership for where you live at joinbilt.com/dan
Timestamps:
00:00:51 Introduction
00:05:51 The AI paradox: more automation, more human work
00:10:00 How AI makes yesterday's expert competence cheap
00:18:00 AI can act autonomously but it does not have agency
00:20:39 Why Dan is all in on AGI
00:21:57 AI layoffs are a lie
00:25:42 Ride the models and you'll be fine
00:35:30 How to use AI as a long-form features editor
If your MCP server has dozens of tools, it's probably built wrong. You need tools that are specific and clear for each use case—but you also can't have too many. This creates an almost impossible tradeoff that most companies don't know how to solve.
That's why we interviewed Alex Rattray, the founder and CEO of Stainless. Stainless builds APIs, SDKs, and MCP servers for companies like OpenAI and Anthropic. Alex has spent years mastering how to make software talk to software, and he came on the show to share what he knows. We get into MCP and the future of the AI-native internet.
[Disclosure: Dan is a small investor in Stainless.]
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
Get started with Braintrust at https://www.braintrust.dev/
Timestamps:
00:01:15 - Introduction
00:05:09 - APIs and MCP, the connectors of the new internet
00:11:00 - Why MCP exists
00:17:15 - Why MCP servers are hard to get right
00:20:24 - Design principles for reliable MCP servers
00:25:06 - Using MCP for business ops at Stainless
00:40:57 - Alex's take on the security model for MCP
00:44:42 - How one-off AI actions become permanent production software
Links to resources mentioned in the episode:
Alex Rattray: Alex Rattray (@RattrayAlex), Alex Rattray
Stainless: https://www.stainless.com/
If your MCP server has dozens of tools, it's probably built wrong. You need tools that are specific and clear for each use case—but you also can't have too many. This creates an almost impossible tradeoff that most companies don't know how to solve.
That's why we interviewed Alex Rattray, the founder and CEO of Stainless. Stainless builds APIs, SDKs, and MCP servers for companies like OpenAI and Anthropic. Alex has spent years mastering how to make software talk to software, and he came on the show to share what he knows. We get into MCP and the future of the AI-native internet.
[Disclosure: Dan is a small investor in Stainless.]
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
Get started with Braintrust at https://www.braintrust.dev/
Timestamps:
00:01:15 - Introduction
00:05:09 - APIs and MCP, the connectors of the new internet
00:11:00 - Why MCP exists
00:17:15 - Why MCP servers are hard to get right
00:20:24 - Design principles for reliable MCP servers
00:25:06 - Using MCP for business ops at Stainless
00:40:57 - Alex's take on the security model for MCP
00:44:42 - How one-off AI actions become permanent production software
Links to resources mentioned in the episode:
Alex Rattray: Alex Rattray (@RattrayAlex), Alex Rattray
Stainless: https://www.stainless.com/Inside Stainless: The Developer Tools Startup Anthropic Just Bought for $300 Million
From time to time, we will republish episodes that you might have missed. This episode originally aired in September 2025.
Noah Brier uses Claude Code as his second brain—it’s the coolest notetaking setup we’ve ever seen.
He has Claude running on a server in his basement hooked up to a VPN. It stores, reads, and writes to thousands of notes in his Obsidian vault. He does it all from his phone.
We had him on the show to tell us exactly how he’s pulling this off.
Dan and Noah get into:
The nuts and bolts of the Claude Code-Obsidian setup: Noah set up Claude Code on top of his Obsidian root directory, and he walked me through how he uses it to prep for an upcoming speech—creating a project folder, pulling in relevant research from his notes, saving transcripts from chats with other LLMs, and generating daily progress updates.
The “thinking partner” that lives inside Noah’s second brain: Noah points out that in the hype around AI’s ability to write, the fact that it can read is overlooked. That’s why he has an agent inside Claude Code with strict guardrails to stay in “thinking mode.” It logs his questions, tracks insights, and catches him up on research if he returns to a project after a few days away.
How Noah does deep work on his phone: Noah rigged a home server in his basement, put his Obsidian vault in it—and then runs Claude Code on top. Noah says that being able to think, write, research, and ship code from his phone has fundamentally changed the way he works.
This episode is a must-watch for anyone curious about who wants to learn how to use Claude Code to build a true second brain.
If you found this episode interesting, please like, subscribe, comment, and share!
Timestamps:
00:00:52 - Introduction
00:02:10 - How you can do deep work on your phone
00:05:30 - Why Noah thinks Grok has the best voice AI
00:11:11 - The nuts and bolts of Noah's Claude Code-Obsidian setup
00:26:05 - Using an agent in Claude Code as a "thinking partner"
00:30:23 - Noah's Thomas' English Muffin theory of AI
00:39:47 - The white space still left to explore in AI
00:48:44 - How Noah is preparing his kids for AI
01:00:06 - How he brought his Claude Code setup to mobile
Links to resources mentioned in the episode:
Noah Brier: https://www.noahbrier.com/, Noah Brier (@heyitsnoah) / X
Alephic, his AI strategy consultancy: alephic.com
The conference he leads about marketing and AI: http://BRXND.AI
A newsletter he writes about AI: newsletter.brxnd.ai
The declassified relic from World War II they talk about: https://www.alephic.com/sabotage
The apps Noah used to set up Claude Code on his phone: Termius, Tailscale
From time to time, we will republish episodes that you might have missed. This episode originally aired in September 2025.
Noah Brier uses Claude Code as his second brain—it’s the coolest notetaking setup we’ve ever seen.
He has Claude running on a server in his basement hooked up to a VPN. It stores, reads, and writes to thousands of notes in his Obsidian vault. He does it all from his phone.
We had him on the show to tell us exactly how he’s pulling this off.
Dan and Noah get into:
The nuts and bolts of the Claude Code-Obsidian setup: Noah set up Claude Code on top of his Obsidian root directory, and he walked me through how he uses it to prep for an upcoming speech—creating a project folder, pulling in relevant research from his notes, saving transcripts from chats with other LLMs, and generating daily progress updates.
The “thinking partner” that lives inside Noah’s second brain: Noah points out that in the hype around AI’s ability to write, the fact that it can read is overlooked. That’s why he has an agent inside Claude Code with strict guardrails to stay in “thinking mode.” It logs his questions, tracks insights, and catches him up on research if he returns to a project after a few days away.
How Noah does deep work on his phone: Noah rigged a home server in his basement, put his Obsidian vault in it—and then runs Claude Code on top. Noah says that being able to think, write, research, and ship code from his phone has fundamentally changed the way he works.
This episode is a must-watch for anyone curious about who wants to learn how to use Claude Code to build a true second brain.
If you found this episode interesting, please like, subscribe, comment, and share!
Timestamps:
00:00:52 - Introduction
00:02:10 - How you can do deep work on your phone
00:05:30 - Why Noah thinks Grok has the best voice AI
00:11:11 - The nuts and bolts of Noah's Claude Code-Obsidian setup
00:26:05 - Using an agent in Claude Code as a "thinking partner"
00:30:23 - Noah's Thomas' English Muffin theory of AI
00:39:47 - The white space still left to explore in AI
00:48:44 - How Noah is preparing his kids for AI
01:00:06 - How he brought his Claude Code setup to mobile
Links to resources mentioned in the episode:
Noah Brier: https://www.noahbrier.com/, Noah Brier (@heyitsnoah) / X
Alephic, his AI strategy consultancy: alephic.com
The conference he leads about marketing and AI: http://BRXND.AI
A newsletter he writes about AI: newsletter.brxnd.ai
The declassified relic from World War II they talk about: https://www.alephic.com/sabotage
The apps Noah used to set up Claude Code on his phone: Termius, Tailscale
In the future, you’ll be able to accomplish a goal by just giving Claude an outcome and a budget.
That’s the direction Anthropic is building in with its new Managed Agents features, announced at this week’s Code with Claude developer event. The basic idea: Claude, wrapped in a computer in the cloud, that you can spin up, scale, and manage as needed. Anthropic is taking on the infrastructure that kills most agent products, and making sure that it scales to meet the needs of agents running 24/7.
On this week’s AI & I from @every, I talk with Angela Jiang (@angjiang), head of product for the Claude platform, and Katelyn Lesse (@katelyn_lesse), head of engineering for the Claude platform, about what Anthropic is building and what it takes to make agents reliable in production.
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:
00:01:48 - How the Claude platform evolved from API to agents
00:04:09 - The primitives that make up Claude Managed Agents
00:10:37 - Why the harness and the model are becoming a single unit
00:18:49 - The infrastructure wall that kills most agent projects in production
00:24:49 - Why team agents need a different shape than individual productivity tools
00:26:36 - How Anthropic's legal team uses an agent to review marketing copy
00:34:24 - Using multi-agent orchestration for advisor strategies, adversarial pairs, and swarms
00:35:50 - How to measure agent success with outcome and budget as the end state
00:39:11 - What the platform looks like a year from now, when Claude writes its own harness
In the future, you’ll be able to accomplish a goal by just giving Claude an outcome and a budget.
That’s the direction Anthropic is building in with its new Managed Agents features, announced at this week’s Code with Claude developer event. The basic idea: Claude, wrapped in a computer in the cloud, that you can spin up, scale, and manage as needed. Anthropic is taking on the infrastructure that kills most agent products, and making sure that it scales to meet the needs of agents running 24/7.
On this week’s AI & I from @every, I talk with Angela Jiang (@angjiang), head of product for the Claude platform, and Katelyn Lesse (@katelyn_lesse), head of engineering for the Claude platform, about what Anthropic is building and what it takes to make agents reliable in production.
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:
00:01:48 - How the Claude platform evolved from API to agents
00:04:09 - The primitives that make up Claude Managed Agents
00:10:37 - Why the harness and the model are becoming a single unit
00:18:49 - The infrastructure wall that kills most agent projects in production
00:24:49 - Why team agents need a different shape than individual productivity tools
00:26:36 - How Anthropic's legal team uses an agent to review marketing copy
00:34:24 - Using multi-agent orchestration for advisor strategies, adversarial pairs, and swarms
00:35:50 - How to measure agent success with outcome and budget as the end state
00:39:11 - What the platform looks like a year from now, when Claude writes its own harness
In January, Dan Shipper wrote that whoever wins vibe coding wins how you work on your computer—and OpenAI had some serious catching up to do.
Three months and the release of GPT-5.5 later, Codex has more than caught up. Austin Tedesco, Every's head of growth, now spends about 80 percent of his working time inside the Codex desktop app, doing everything from drafting go-to-market plans from a stack of meeting transcripts to rebuilding the company's KPI dashboard.
On this episode of AI & I, Dan sat down with Austin to discuss why the agent management interface—a desktop app built on top of a coding agent—is becoming the new operating system for knowledge work, and why Codex has become his daily driver.
If you found this episode interesting, please like, subscribe, comment, and share!
To hear more from Dan Shipper:
Subscribe to Every: every.to/subscribe
Follow him on X: twitter.com/danshipper
Join the membership for Where You Live at joinbilt.com/dan
Timestamps for YouTube:
00:00:00 Introduction
00:00:57 How Codex went from a tool for senior engineers to a daily driver for knowledge work
00:02:42 How Claude Code proved that a great coding agent works for any knowledge work
00:07:24 Austin's switch to Codex
00:13:48 How Austin set up Codex with folders, keys, and reviewer agents
00:18:24 Using Codex to brainstorm automations across Gmail, Slack, and Notion
00:22:42 How Austin manages the human review step when Codex is drafting communications
00:28:54 Using Codex to build specialized agents inspired by product executive Claire Vo
00:31:09 Synthesizing meeting transcripts and Slack threads into a go-to-market plan
00:40:15 Building a live KPI tracker in Notion that agents can read
00:44:54 Using Codex for recruiting
Links to resources mentioned in the episode:
Austin on X: @tedescau
Dan's January essay on OpenAI's catch-up problem: every.to/chain-of-thought/openai-has-some-catching-up-to-do
Every's vibe check on GPT-5.5: every.to/vibe-check/gpt-5-5
In January, Dan Shipper wrote that whoever wins vibe coding wins how you work on your computer—and OpenAI had some serious catching up to do.
Three months and the release of GPT-5.5 later, Codex has more than caught up. Austin Tedesco, Every's head of growth, now spends about 80 percent of his working time inside the Codex desktop app, doing everything from drafting go-to-market plans from a stack of meeting transcripts to rebuilding the company's KPI dashboard.
On this episode of AI & I, Dan sat down with Austin to discuss why the agent management interface—a desktop app built on top of a coding agent—is becoming the new operating system for knowledge work, and why Codex has become his daily driver.
If you found this episode interesting, please like, subscribe, comment, and share!
To hear more from Dan Shipper:
Subscribe to Every: every.to/subscribe
Follow him on X: twitter.com/danshipper
Join the membership for Where You Live at joinbilt.com/dan
Timestamps for YouTube:
00:00:00 Introduction
00:00:57 How Codex went from a tool for senior engineers to a daily driver for knowledge work
00:02:42 How Claude Code proved that a great coding agent works for any knowledge work
00:07:24 Austin's switch to Codex
00:13:48 How Austin set up Codex with folders, keys, and reviewer agents
00:18:24 Using Codex to brainstorm automations across Gmail, Slack, and Notion
00:22:42 How Austin manages the human review step when Codex is drafting communications
00:28:54 Using Codex to build specialized agents inspired by product executive Claire Vo
00:31:09 Synthesizing meeting transcripts and Slack threads into a go-to-market plan
00:40:15 Building a live KPI tracker in Notion that agents can read
00:44:54 Using Codex for recruiting
Links to resources mentioned in the episode:
Austin on X: @tedescau
Dan's January essay on OpenAI's catch-up problem: every.to/chain-of-thought/openai-has-some-catching-up-to-do
Every's vibe check on GPT-5.5: every.to/vibe-check/gpt-5-5
Emily Glassberg Sands leads data and AI at Stripe, which processes roughly 2% of global GDP, giving her a bird’s-eye view into how AI is upending the internet economy.
Dan Shipper talked with Glassberg Sands for Every's AI & I about what the data on Stripe's network actually shows: AI companies are scaling three times faster than the top SaaS cohort of 2018, fraud has moved from the checkout to the full funnel, and agents have started buying things, although mostly low-stakes commodities like Halloween costumes.
The conversation covers the new fraud types unique to AI companies, the AI-on-AI arms race between bad actors and fraud detectors, where AI revenue growth is actually coming from, and how Stripe is rebuilding the payments infrastructure for a world where the buyer is an agent.
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
Head to http://granola.ai/every and get 3 months free with the code EVERY
Timestamps
00:00:45 Introduction
00:01:27 New rules for an agent-driven economy
00:03:57 Compute theft is the new payment fraud
00:10:00 How Stripe expanded fraud detection from checkout to the full customer lifecycle
00:19:48 Why AI companies are scaling way faster than top SaaS companies
00:23:27 Outcome-based billing is replacing seat-based pricing
00:29:57 Where AI spending is coming from
00:36:45 How the developer experience changes when agents are the builders
00:41:00 The agentic commerce spectrum, from assisted buying to autonomous purchasing
00:51:06 Meet Link, a consumer wallet for delegated agent purchases
Links to resources mentioned in the episode:
Emily Glassberg Sands on X: https://x.com/emilygsands
Stripe: https://stripe.com
Stripe Radar: https://stripe.com/radar
Stripe Link: https://link.com
Lovable: https://lovable.dev
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