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GOTO Conferences· 23. Okt. 2026Anatoliy 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.
5:15:51EN
Lex Fridman· 26. Aug. 2026Podcast · 2 StimmenDHH Did Not Write a Line of Omarchy QuattroGast: DHH · Moderation: 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.
1:34:36EN
Jane Street· 1. Juni 2026Nate Foster: Treating the Network as a ProgramYaron Minsky, Nate Foster · Jane StreetFrom programmable switches to BGP, a programming-languages researcher explains how higher-level policies and formal models can make networks easier to change.
1:48:21ENJane Street· 17. März 2026Will Wilson on Deterministic Simulation and the Hard Problems of Software TestingYaron Minsky, Will Wilson · Jane StreetThe Antithesis co-founder explains how replayable simulations explore complex software, why properties matter and where testing meets its limits.
2:29:04ENLex Fridman· 6. Okt. 2024Podcast · 2 StimmenKeep 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.
32:48EN
No Priors: AI, Machine Learning, Tech, & Startups· 16. Nov. 2023Podcast · 2 StimmenFourteen People, $200 Million of Compute, and the Reliability Bottleneck for AgentsModeration: 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.
23:58ENJane Street· 31. März 2016Effective ML: Errors, Abstraction and Managing ComplexityYaron Minsky · Jane StreetA Jane Street engineer discusses explicit failure, boilerplate, type-system restraint and the practical role of side effects.
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Lenny's PodcastPodcast · 2 StimmenFaster, 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.
1:15:13ENLenny's PodcastPodcast · 2 StimmenShipping Real Apps Without Writing Code: A Non-Technical PM's Cursor and Claude Code WorkflowGast: Zevi Arnovitz · Moderation: 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.