필터 결과
13개정렬
1:55:02EN
Cognitive Revolution "How AI Changes Everything"· 2026년 1월 4일팟캐스트An Index Fund on AGI: How MATS Filters the Next 120 AI Safety Researchers진행자 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.
1:32:41ENCognitive Revolution "How AI Changes Everything"· 2023년 10월 5일팟캐스트There 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.
1:26:22EN
Lenny's Podcast팟캐스트Start Small, Earn Autonomy: What 50+ AI Product Deployments Taught Two Builders진행자 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.
1:16:17ENLenny's Podcast팟캐스트 · 2명Faster, But for What? Nicole Forsgren on Measuring Developer Productivity in the AI Era게스트 Nicole Forsgren · 진행자 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.
1:34:57ENLenny's Podcast팟캐스트 · 2명Fifteen People, Four Products, Zero Handwritten Code: Inside Every's AI-First Company게스트 Dan Shipper · 진행자 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.
1:38:45ENLenny's Podcast팟캐스트When 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.
1:27:45ENLenny's Podcast팟캐스트Coding 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.
1:07:48ENLenny's Podcast팟캐스트Most 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.
1:26:42ENLenny's Podcast팟캐스트 · 2명Inside Block's AI-Native Bet: Goose, Functional Orgs and Throwing Code Away게스트 Dhanji R. Prasanna · 진행자 Lenny RachitskyBlock CTO Dhanji Prasanna explains how a reorg, an open-source agent and a learning-first culture made the company unusually AI-forward.
1:30:00ENLenny's Podcast팟캐스트 · 2명Inside Stripe's Product Engineering Culture: Friction Logs, Engineer Occasions and 45-Minute Deploys게스트 David Singleton · 진행자 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.
1:14:34ENLenny's Podcast팟캐스트 · 2명Inside the Frontier Lab: How Karina Nguyen Builds Products by Training the Model게스트 Karina Nguyen · 진행자 Lenny RachitskyOpenAI researcher Karina Nguyen explains synthetic data, evals, how Canvas and Tasks were made, and which human skills matter as models get smarter.
1:46:33ENLenny's Podcast팟캐스트 · 3명From Chaos to a Failure Map: A Hands-On Primer on AI Evals게스트 Hamel Husain, Shreya Shankar · 진행자 Lenny RachitskyHamel Husain and Shreya Shankar walk Lenny Rachitsky through a real error-analysis workflow, from reading traces to building a trustworthy LLM judge.
1:19:39ENLenny's Podcast팟캐스트Engineers 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.