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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.
5:15:51ENDHH Did Not Write a Line of Omarchy QuattroGuest DHH · Host Lex FridmanThirteen months after a skeptical conversation with Lex Fridman, the Rails creator describes how Opus 4.5, a swarm of coding agents, and a one-minute Linux installer ended his era of hand-chiseled Ruby.
1:34:29ENThree IMO Golds Missed the Same Problem. Harmonic Wants Math to CompileHost Nathan LabenzVlad Tenev and Tudor Achim built Aristotle to emit Lean proofs a kernel can check—and they argue that is how mathematical superintelligence stays trustworthy.
1:41:34ENThey Owned the Camera Partition—and Still Couldn't Crash the HelicopterHost Nathan LabenzKathleen Fisher and Byron Cook tell Nathan Labenz how formal methods turn some software bugs into closed cases, from a DARPA helicopter to AWS policies checked a billion times a second.
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.
2:29:04ENKeep the Programmer in the Driver's Seat: Cursor's Founders on Tab, Agents, and Zero-Entropy EditingGuest Cursor Team · Host 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.
1:25:10ENWriting Code Is Only 30% of the Job. CodiumAI Wants the Other 70%Host 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.
32:48ENFourteen People, $200 Million of Compute, and the Reliability Bottleneck for AgentsHost Sarah Guo, Elad GilImbue co-founders Kanjun Qiu and Josh Albrecht on why agents fail, why language models cannot learn general algorithms, and why they are spending a giant round on GPUs rather than headcount.
1:25:13ENCodex Is Not Just a Coding Tool: OpenAI's Plan for an Agent That Behaves Like a TeammateHost 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.
1:16:17ENFaster, But for What? Nicole Forsgren on Measuring Developer Productivity in the AI EraGuest Nicole Forsgren · Host 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.
1:07:48ENMost Productivity Metrics Are a Lie: Nicole Forsgren on Measuring Developer Experience in the AI EraHost 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.
1:15:13ENShipping Real Apps Without Writing Code: A Non-Technical PM's Cursor and Claude Code WorkflowGuest Zevi Arnovitz · Host Lenny RachitskyZevi Arnovitz, a product manager with no technical background, walks Lenny Rachitsky through the slash-command workflow he uses to build and ship products with AI.









