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1:55:02ENAn Index Fund on AGI: How MATS Filters the Next 120 AI Safety ResearchersModeration: Nathan LabenzRyan Kidd, co-executive director of MATS, tells Nathan Labenz why he will not shout a timeline, why every safety technique is also a capabilities technique, and who actually gets hired.
1:32:41ENThere are maybe 5,000 people who can train frontier models. The rest need AI engineersModeration: 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.
1:26:22ENStart Small, Earn Autonomy: What 50+ AI Product Deployments Taught Two BuildersModeration: Lenny RachitskyAishwarya Naresh Reganti and Kiriti Badam explain why AI products need a different build process, and how to grow agent autonomy step by step without losing customer trust.
1:16:17ENFaster, But for What? Nicole Forsgren on Measuring Developer Productivity in the AI EraGast: Nicole Forsgren · Moderation: Lenny RachitskyThe creator of DORA and SPACE explains why most productivity metrics mislead, how AI changes flow and trust, and how to build a developer experience program that proves its value.
1:34:57ENFifteen People, Four Products, Zero Handwritten Code: Inside Every's AI-First CompanyGast: Dan Shipper · Moderation: Lenny RachitskyEvery CEO Dan Shipper explains how his small team uses Claude Code, an AI operations lead and compounding engineering to do the work of a much larger company.
1:38:45ENWhen Coding Stops Being the Bottleneck: Inside Anthropic's Claude Code and Cowork TeamsModeration: 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.
1:27:45ENCoding Is Solved, Says the Creator of Claude Code: Boris Cherny on What Comes NextModeration: 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 EraModeration: 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.
1:26:42ENInside Block's AI-Native Bet: Goose, Functional Orgs and Throwing Code AwayGast: Dhanji R. Prasanna · Moderation: Lenny RachitskyBlock CTO Dhanji Prasanna explains how a reorg, an open-source agent and a learning-first culture made the company unusually AI-forward.
1:30:00ENInside Stripe's Product Engineering Culture: Friction Logs, Engineer Occasions and 45-Minute DeploysGast: David Singleton · Moderation: Lenny RachitskyStripe CTO David Singleton explains how the company hires, builds with early users, sweats the details and ships constantly without breaking a business-critical system.
1:14:34ENInside the Frontier Lab: How Karina Nguyen Builds Products by Training the ModelGast: Karina Nguyen · Moderation: Lenny RachitskyOpenAI researcher Karina Nguyen explains synthetic data, evals, how Canvas and Tasks were made, and which human skills matter as models get smarter.
1:46:33ENFrom Chaos to a Failure Map: A Hands-On Primer on AI EvalsGast: Hamel Husain, Shreya Shankar · Moderation: Lenny RachitskyHamel Husain and Shreya Shankar walk Lenny Rachitsky through a real error-analysis workflow, from reading traces to building a trustworthy LLM judge.
1:19:39ENEngineers Become Sorcerers: OpenAI's Sherwin Wu on the Next 12 to 24 MonthsModeration: 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.









