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1:32:41ENThere are maybe 5,000 people who can train frontier models. The rest need AI engineers진행자 Nathan LabenzSwyx of Latent Space tells Nathan Labenz how a new job is forming, why OpenAI will Sherlock its developers, and what still does not count as an agent.
2:17:30ENGemini Became the Daily Driver. A GPT-5 Worthy of the Name Would Make Agents Work.진행자 Nathan LabenzZvi Mowshowitz returns to Cognitive Revolution to unpack Gemini 1.5, Sora, superalignment, sleeper agents, and the live-player map of frontier labs.
1:39:53ENUnder 100 People, 24 Million Users: Replit's Bet on Artificial Developer Intelligence진행자 Nathan LabenzMichele Catasta, Replit's new VP of AI, lays out a generate-execute-learn loop he will not call AGI, a 2x-to-1000x productivity ladder, and a keystroke-level data advantage.
1:45:46ENReplit's $10 AI Programmer Already Pays for Itself. The Ambition Is Bots Hiring Bots진행자 Nathan LabenzTyler Angert, Replit's first product designer, explains Ghostwriter, a virtual developer, and why the company calls itself the perfect substrate for AGI.
32:48ENA Hundred Million to Train, a Penny to Infer진행자 Nathan LabenzIn a February 2023 roundtable, two founders argue on mic over whether AGI ends humanity — and who actually captures the value if it does not.
1:25:13ENCodex Is Not Just a Coding Tool: OpenAI's Plan for an Agent That Behaves Like a Teammate진행자 Lenny RachitskyCodex product lead Alexander Embiricos explains the 20x growth, why every useful agent may need to write code, and why human review speed is the real bottleneck.
1:39:51ENAfter the Inflection Point: Simon Willison on Agentic Engineering, Dark Factories and the Coming AI Challenger Disaster진행자 Lenny RachitskyDjango co-creator Simon Willison explains what changed in November 2025, how he works with coding agents, and why prompt injection remains the field's biggest unsolved risk.
1:33:50ENEvals Are the New PRDs: Inside Anthropic's Research Product Team진행자 Lenny RachitskyDianne Penn, Anthropic's head of product for research and Labs, explains how the company found its identity, how her team turns user feedback into evals, and why human judgment still matters.
1:11:06ENReplit's Amjad Masad on Building Your Own Model, Latency, and the Next Billion Software Creators진행자 Jacob EffronThe Replit founder explains why AI should be native to the product, why he trained a small in-house model, and why he thinks software engineering is about to split in two.
1:53:14ENWorth Thousands, Priced at $20: Zvi Mowshowitz on OpenAI's Flurry, Gemini Bets, Deepfakes and a Compute Cap진행자 Nathan LabenzZvi Mowshowitz and Nathan Labenz survey OpenAI's launch spree, AI pricing and bundling, data pollution, deepfakes, the reversal curse, calls to cap training compute, and Amazon's Anthropic deal.
1:04:25ENInside GitHub's Copilot Bet: Agents, Open Source, and Why the Developer Job Endures진행자 Jacob EffronGitHub CEO Thomas explains how Copilot went from a research bet to 1.3 million developers, and what agents, fine-tuning and a multi-model world mean for the next five years of software.
50:03ENCopilot Is a Copilot, Not a Pilot: Inbal Shani on the Future of AI in Software Development진행자 Lenny RachitskyGitHub's chief product officer explains what AI changes for developers, what it does not replace, and how teams should adopt it.
1:38:45ENWhen Coding Stops Being the Bottleneck: Inside Anthropic's Claude Code and Cowork Teams진행자 Lenny RachitskyFiona Fung, who leads the teams behind Claude Code and Cowork, describes how an engineering org that ships roughly eight times more code manages quality, hiring, metrics and culture.
1:36:57ENDo the Dumb Thing First: A CTO's Playbook for Building an AI Coding Assistant진행자 Jacob EffronSourcegraph CTO Beyang Liu on which AI coding features actually earn daily use, how new models get shipped and evaluated, and why retrieval is still a search problem.
1:27:45ENCoding Is Solved, Says the Creator of Claude Code: Boris Cherny on What Comes Next진행자 Lenny RachitskyBoris Cherny, head of Claude Code at Anthropic, on the tool's origin, the principle of latent demand, and how work changes when engineers stop writing code by hand.
1:07:48ENMost Productivity Metrics Are a Lie: Nicole Forsgren on Measuring Developer Experience in the AI Era진행자 Lenny RachitskyThe creator of DORA and SPACE explains why lines of code and old pipeline metrics fall short with AI, and how to start improving developer experience by listening, surveying and tying results to what leaders care about.
1:41:26ENThe AI Scouting Report, Part 3: What AI Can Already Do, Who Will Win, and Why Nathan Labenz Wants Caution on Scaling진행자 Nathan LabenzNathan Labenz closes his AP-course tour of AI with capabilities, market moats, jobs, law, safety plans and a stance on what to do next.
1:25:34ENShipping in Days: How Claude Code's Head of Product Runs a Team at AI Speed진행자 Lenny RachitskyCat Wu, Head of Product for Claude Code and Cowork at Anthropic, explains how the PM role, hiring, tooling and culture change when features go from idea to users in a week or less.
1:09:56ENWhen Anyone Can Build Anything, Taste Becomes the Product Job진행자 Lenny RachitskyCodex desktop lead Andrew Ambrosino on how AI has inverted product development, why roles are blurring but shouldn't vanish, and where Codex and ChatGPT are headed.
37:23ENFrom Chat to Always-On Agents: OpenAI's Tibo Sottiaux on Dots, Open Ecosystems and What Comes Next진행자 Lenny RachitskyThe head of ChatGPT and Codex, speaking hours after a DevDay launch of more than 20 products, explains the vision for a personal agent that works around the clock.
1:11:13ENAfter Code: Cursor's CEO on Logic Design, Custom Models and Why One Winner Will Take the Market진행자 Lenny RachitskyMichael Truell explains how Cursor went from a mechanical-engineering pivot to a $300M ARR product, and where he thinks programming is heading.
1:06:22ENWhen AI Writes 90% of the Code: Anthropic's CPO on New Bottlenecks, Builders and MCP진행자 Lenny RachitskyMike Krieger on how product work changes inside Anthropic, why he shut down Artifact, and where AI founders can build without being squashed.
1:19:39ENEngineers Become Sorcerers: OpenAI's Sherwin Wu on the Next 12 to 24 Months진행자 Lenny RachitskyThe head of engineering for OpenAI's API and developer platform describes life with Codex, how management is changing, and why builders should aim for where the models are going.
54:52ENCoding Agents Are Breaking Containment: The 2026 AI Stack, the Coding Wars, and the Next Frontier진행자 Jacob EffronJacob Effron and Swyx map the state of AI engineering, from agent harnesses and infrastructure churn to coding-market economics, open models, dark factories, and world models.
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