AI and I

Hosted by Dan Shipper

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119

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Aug 2026

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About the show

Learn how the smartest people in the world are using AI to think, create, and relate. Each week I interview founders, filmmakers, writers, investors, and others about how they use AI tools like ChatGPT, Claude, and Midjourney in their work and in their lives. We screen-share through their historical chats and then experiment with AI live on the show. Join us to discover how AI is changing how we think about our world—and ourselves. For more essays, interviews, and experiments at the forefront of AI: https://every.to/chain-of-thought?sort=newest.

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August 19, 20261 hr 22 min

The AI Alien Companion App That's Bringing In $4M a Year (Best of the Pod)

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/subscribeFollow him on X: https://twitter.com/danshipperGo 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

August 12, 202628 min

Microsoft’s Vision for an Internet Made for Agents With CTO Kevin Scott (Best of the Pod)

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

August 5, 202648 min

Why the Next Hit AI Product Will Be Social Why the Next Hit AI Product Will Be Social (Best of the Pod)

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

July 29, 202653 min

Best of the Pod: Wired's Kevin Kelly on Why AI Is a 50-year Overnight Success

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

July 22, 202646 min

How Every's Team Used AI to Ship Its Biggest Launch Ever

Yash Poojary, a growth engineer at Every, dropped an idea for a campaign in Slack at 7 p.m. Instead of building it himself, Every’s head of growth Austin Tedesco took a screenshot of the Slack thread, dropped it into Codex, typed "Can you do this?", and went to the gym. By the time he got back, Codex had built four audience segments, drafted emails for each one, and pulled a social image that had worked before. It took Austin 10 minutes to make some tweaks and schedule the whole thing to send the next morning. Within a few hours, it generated more than $25,000 in revenue. That story came out of the launch week for All Access, Every’s new $625-a-year membership built around the Builder Pack. It includes $7,000 in credits and free usage from ten of the AI products Every uses every day, including Claude Max, Codex, Cursor Pro+, PostHog, Notion, Framer, Render, and Flora. On this episode of AI & I, four of Every's own builders—COO Brandon Gell, head of marketing Douglas Brundage, as well as Yash and Austin—sit down to show how they use AI, breaking down their personal stacks and giving insight into their own strategies and mindset for building. 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 Intro 0:35 All Access Explained 3:01 Yash's Tech Stack and How He's Automating Testing Pipelines 8:02 The Idea to Execution Loop 10:25 How an Agent Turned an Idea into $25K 17:50 The AI Sandwich Workflow 22:03 Making AI Tools Accessible to Solo Builders 28:50 Douglas on Brand and Design 34:51 Tips on What to Build First 43:46 What's Next for All Access Links to resources mentioned in the episode: Brandon Gell on X: https://x.com/bran_don_gell Yash Poojary on X: https://x.com/poojary_yash Austin Tedesco on X: https://x.com/tedescau?lang=en Douglas Brundage on X: https://x.com/DABrundage Introducing Every All Access: https://every.to/on-every/introducing-every-all-access Get the Builder Pack: every.to/builder-pack Go to https://attio.com/every and get 15% off your first year.

June 24, 202643 min

Building a School Where AI Models Learn About Humanity

If scaling laws hold—and Surge AI CEO Edwin Chen believes they do—we’re hurtling toward a future where there’s nothing humans can do that AI can’t do better. When OpenAI’s models disproved an open conjecture posed by mathematician Paul Erdős using novel algebraic geometry techniques, Fields medalist Timothy Gowers felt the shift acutely. He initially thought the model had proved an upper bound, and braced himself: that would mean it was “all over for mathematicians very soon.” When he realized it had only found a counterexample, he was relieved—it bought him another year or two before the thing he’s devoted his life to becomes something AI does better. As founder and CEO of the company behind the data environments and evals the major model companies use to train their models, Chen has a unique perspective on how quickly AI models are absorbing tasks we used to think of as uniquely human. Dan Shipper talked with Chen for AI & I about what the act of creating or building means when AI can do it better—and whether an answer to that question already exists within science fiction. If you found this episode interesting, please like, subscribe, comment, and share! Join the membership for Where You Live at ⁠https://www.joinbilt.com/dan To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe Follow him on X: https://twitter.com/danshipper Timestamps: 00:00:54 Introduction 00:01:49 Surge as a "school for AGI" 00:04:46 What AI's capacity for novel mathematics says about human achievement 00:07:29 Motivation in an era when AI can do everything 00:14:34 The trap of optimizing AI models for engagement 00:29:34 Training using datasets versus training using environments 00:35:09 The value of personal data 00:39:40 Why models are bad at writing 00:42:00 Chen's AGI timeline Links to resources mentioned in the episode: Edwin Chen on X: https://x.com/echen Surge: https://surgehq.ai Riemann-bench (research-level math benchmark): https://surgehq.ai/leaderboards/riemann-bench Hemingway-bench (creative writing benchmark): https://surgehq.ai/leaderboards/hemingway-bench Talkie-1930 (language model trained on pre-1930 text): https://huggingface.co/talkie-lm/talkie-1930-13b-it Ted Chiang, “What’s Expected of Us”: https://www.nature.com/articles/436150a Every is the most AI-native startup on the internet. Through ideas, software and education, subscribers get the tools to work at the frontier of AI. Start your free trial today: https://every.to/subscribe?utm_source=youtube Follow Every: https://x.com/every Follow Dan Shipper: https://x.com/danshipper

June 17, 202628 min

GitHub’s COO Explains Why AI Hasn’t Replaced Developers

Last year, there were 1 billion commits on GitHub. This year, Kyle Daigle expects that number to exceed 14 billion, a two-component explosion caused by more humans—and their agents—issuing pull requests. In March alone, 17 million pull requests on GitHub were created by agents. Daigle is the COO of GitHub and Microsoft’s chief marketing officer for developer products. He’s been at GitHub for 13 years, and is paying close attention to how AI is expanding the platform’s user base. Along with agents, legal, sales, and marketing professionals are building apps with the GitHub Copilot app. The line between developer and non-developer is disappearing. On this episode of AI & I, guest host Mike Taylor sat down with Daigle at Microsoft Build to discuss how GitHub is building infrastructure for an agent-native world: agentic code review, model routers that automatically select the right model for the task, and a philosophy that the most durable advantage in this market is developer choice. If you found this episode interesting, please like, subscribe, comment, and share! Want even more? To hear more from Mike Taylor: Subscribe to Every: https://every.to/subscribe Follow him on X: https://x.com/hammer_mt Timestamps for YouTube: 00:00:52: Introduction 00:03:27: The agentic PR flood 00:04:33: GitHub's approach to helping open-source maintainers manage the surge 00:06:15: What 14 billion commits means for code quality 00:08:03: Moving from per-seat licensing to usage-based pricing 00:09:45: Kyle's dual role as GitHub COO and Microsoft's chief marketing officer for developers 00:13:03: Developer choice as competitive moat 00:14:57: How to balance dogfooding your own tools with staying honest about the competition 00:19:45: Hill climbing, frontier tuning, and solving the model-routing problem 00:24:45: Kyle's agentic communication hack Links to resources mentioned in the episode: Kyle Daigle on X: https://x.com/kdaigle Mike Taylor on Every: https://every.to/@mike_2114 Mike’s piece on building an AI version of Kyle Daigle: https://every.to/also-true-for-humans/i-interviewed-an-ai-version-of-github-s-coo-then-spoke-to-the-real-one GitHub Copilot: https://github.com/features/copilot

June 10, 202652 min

How Anthropic Uses Claude Fable 5 With Mike Krieger

Mike Krieger built one of the most consequential consumer apps of the last two decades as the cofounder of Instagram. He is now at the frontier of AI-native product development as head of Anthropic Labs, the team responsible for figuring out what the most capable AI models can do in the hands of real builders.When Krieger first got access to Fable 5 months before its public release, it was exciting and disorienting. “I feel like a total newbie again,” he remembers telling his team. The way he’d been thinking about productivity, strategy, and time management was out of date. The model had outpaced his workflows.Dan Shipper talked with Krieger for AI & I about what it looks like to build with a model as capable as Fable 5, including the new rhythms, challenges, and possibilities it reveals.If you found this episode interesting, please like, subscribe, comment, and share!To hear more from Dan Shipper:Subscribe to Every: https://every.to/subscribeFollow him on X: https://twitter.com/danshipperGet started with Braintrust at https://www.braintrust.dev/ Timestamps:0:03 Introduction1:48 How Fable completely reshaped Mike's workflow4:48 When to use Sonnet versus Fable10:06 What the media tracker Mike built over a weekend reveals about agent-native architecture15:00 The cost to build has collapsed19:03 Is software engineering over?21:48 How Anthropic's engineering teams work today38:39 The mechanics of verification44:39 What people should use the model to build47:24 Dynamic workflowsLinks to resources mentioned in the episode:Mike Krieger on X: https://x.com/mikeykAnthropic Labs: https://www.anthropic.comClaude Code: https://claude.ai/codeEvery: https://every.to Timestamps:0:03 Introduction1:48 How Fable completely reshaped Mike's workflow4:48 When to use Sonnet vs. Fable10:06 What the media tracker Mike built over a weekend reveals about agent-native architecture15:00 The cost to build has collapsed19:03 Is software engineering over?21:48 How Anthropic's engineering teams work today38:39 The mechanics of verification44:39 What people should use the model to build47:24 Dynamic workflowsLinks to resources mentioned in the episode:Mike Krieger on X: https://x.com/mikeykAnthropic Labs: https://www.anthropic.comClaude Code: https://claude.ai/codeEvery: https://every.to

June 3, 202633 min

The SaaS Apocalypse Is a Goldmine With Figma’s Matt Colyer

The "SaaSpocalypse"—the panic that AI will make software-as-a-service obsolete—hasn't rattled Figma’s Matt Colyer. As the company’s director of product management for developers, he's been building his own agents for two years and is buying more software services than ever. In addition to making the case that AI is a “goldmine” for SaaS companies, Colyer talked with Dan Shipper for AI & I about why great design requires a diamond-shaped process: First you diverge, generating as many ideas as possible, then you converge around the best ones. Chat is linear, which makes it good for iterating on one design but bad at generating lots of options. Figma's new on-canvas agent is a first attempt at fixing that. They also get into why AI design tools need to break free of the text box, how Figma's MCP server is closing the loop between code and design, and why "review" has become the biggest bottleneck in AI-assisted product work. 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: 1:03 - Introduction 2:15 - Why the SaaSpocalypse narrative has it backwards 5:27 - Matt’s email agent origin story 13:21 - Divergent vs. convergent design thinking 17:39 - Figma’s MCP server 19:45 - Why design agents need personalization 22:09 - Every problem is a context problem 25:12 - Apple and Google as the reigning kings of context 28:18 - Why review is the new bottleneck Links to resources mentioned in the episode: Matt Colyer on X: https://x.com/mcolyer Figma: https://figma.com Figma MCP server: https://www.figma.com/blog/introducing-figma-mcp-server/

May 27, 202641 min

We Automated Everything With AI and Tripled Our Headcount

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