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18:27ENDaksh Gupta on Building a Better AI Code Review AgentDaksh Gupta · GreptileGreptile co-founder Daksh Gupta explains why a webhook plus a coding agent is not enough for reliable pull-request review—and how targeted prompts, incident data, model inversion, codebase context, browser testing, and task-specific model routing can help.
34:11ENAnatoliy Bilenko and Alberto Carretero: Making Database Protocols Reliable with Formal Methods and AIAnatoliy Bilenko, Alberto Carretero · CanonicalCanonical’s database engineers connect executable specifications, model-based tests, failure exploration, and reconstructed execution histories—and explain why none of these techniques proves a real system correct on its own.
1:01:33ENSpec-Driven Development with Coding Agents: Write the Spec, Let the Agent BuildAndrew Ng, Paul Everitt · DeepLearning.AIJetBrains developer advocate Paul Everitt walks through a full spec-driven workflow: a project constitution, feature loops of plan–implement–validate, and agent skills that travel across tools. The alternative to vibe coding is a markdown contract the agent cannot forget.
40:13ENAs long as humans still need to read code, the IDE is not dyingZed founder Nathan Sobo argues that source code is a language for people, that terminal agents still need a visual editor, and that conversations should be anchored to every edit.
27:19ENThe Turing Test Passed. Warp's CEO Says Nobody Seemed to CareModeration: Sarah Guo, Elad GilZach Lloyd on distilling intelligence without consciousness, why a 40-year-old terminal is the front door for coding agents, and why senior engineers just got more expensive.
37:45ENCodex Is a Thought Experiment: What If the Agent Worked on Its Own Computer?OpenAI’s Codex team on training o3 to write mergeable PRs, running four copies of a 1 a.m. bug, and why the product only clicks once you stop pairing and start delegating.
5:20:08ENThePrimeagen Would Rather Redesign the Room Than Trust WillpowerGast: ThePrimeagen · Moderation: Lex FridmanLex Fridman talks with Michael Paulson about linked lists, Netflix, Neovim, ADHD, addiction, AI, and the night he says God gave him a conscience.
50:35ENCopilot Already Writes Half the Code. GitHub's CEO Says Agents Still Have Four Gates to ClearModeration: Sarah Guo, Elad GilThomas Dohmke on agent mode, why median developers are not going anywhere, and how AI is repricing the tools that write software.
54:47ENNinety Thousand Games a Day: Roblox's Bet That AI Should Wash the DishesStef Corazza, head of generative AI at Roblox, tells Sequoia how a free Studio assistant, a community data bargain, and a 3D foundation model are meant to teach AI game development.
38:28ENHalf of Production AI Is RAG. Fine-Tuning Almost Disappeared.Moderation: Sarah Guo, Elad GilBraintrust CEO Ankur Goyal tells No Priors what Notion, Zapier, and Vercel actually ship — and which hyped techniques they quietly dropped.
2:29:04ENKeep the Programmer in the Driver's Seat: Cursor's Founders on Tab, Agents, and Zero-Entropy EditingGast: Cursor Team · Moderation: Lex FridmanMichael Truell, Aman Sanger, Sualeh Asif, and Arvid Lunnemark tell Lex Fridman why they forked VS Code, how Tab and Apply actually work, and why most programming still needs a human iterating in real time.
59:11ENDon't Train a Model. Factory's Founders Say Go Dig for GoldMatan Grinberg and Eno Reyes tell Sequoia's Training Data why they sell a fleet of job-specific droids on top of other people's models — and how that stack just took SWE-bench from 14% to 19%.
1:25:10ENWriting Code Is Only 30% of the Job. CodiumAI Wants the Other 70%Moderation: Nathan LabenzItamar Friedman argues that completion is already a commodity, that code integrity is where AI still lags, and that flow engineering—not fancier prompts—is how GPT-4 doubled its score on coding contests.
1:15:39ENAfter 20 Years of Frontend, v0 Wrote Better Code Than Guillermo Rauch DidModeration: Nathan LabenzThe Vercel CEO tells Nathan Labenz why every product needs ghost text, why Software 2.0 will ossify the old stack, and why betting against open source is still the expensive mistake.
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.
38:13ENChatGPT Runs on His Framework. He Still Doesn't Want You Training a ModelModeration: Sarah Guo, Elad GilVercel founder Guillermo Rauch tells No Priors why frontend is the last mile of AI, why first-generation AI frameworks will be rewritten, and why bots are already stealing your tokens.
43:45ENEight Years of No Growth, Then OpenAI and NVIDIA Became His CustomersModeration: Sarah Guo, Elad GilWeights & Biases CEO Lukas Biewald tells No Priors how a labeling company with no chasm to cross funded the ML developer tools that trained most of the large language models.
50:03ENCopilot Is a Copilot, Not a Pilot: Inbal Shani on the Future of AI in Software DevelopmentModeration: Lenny RachitskyGitHub's chief product officer explains what AI changes for developers, what it does not replace, and how teams should adopt it.
1:21:34ENGitLab’s Public-by-Default Playbook: Short Toes, Clear Outcomes, and a Platform Built to ShipModeration: Lenny RachitskyDavid DeSanto explains how GitLab turns radical transparency, remote-first operations, and breadth-then-depth product strategy into a faster DevSecOps platform.
1:08:07ENContext Is All You Need: Inside OpenAI with Logan KilpatrickGast: Logan Kilpatrick · Moderation: Lenny RachitskyOpenAI's head of developer relations on GPTs, prompting, how the company ships fast, and where startups can build without being steamrolled.
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.
1:19:48ENBigger Models, Cleaner Splits and Human Baselines: Andrew Ng's Practical Recipe for Applied Deep LearningModeration: Lex FridmanIn a 2016 Deep Learning School talk, Andrew Ng distills lessons from leading Baidu's AI team into a workflow for diagnosing models, handling data and building a career.
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.
17:32ENOver-Automating, Googling Doctors and Neural Nets: George Hotz Reviews Programming MemesModeration: Lex FridmanLex Fridman and George Hotz rate printed programming memes, and the jokes turn into candid talk about testing, hiring, social media and the power of neural networks.
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