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1:29:02ENShe Never Sees a Row of Your Data. The Answers Still Clear 95%.Moderation: Nathan LabenzIllumex CEO Inna Tokarev Sela tells Nathan Labenz how a Platonic industry ontology, trained only on metadata, collapses enterprise software into one conversation.
1:24:48ENCanva's AI Features Have Been Used 10 Billion Times. The Playbook Is Not a Chat BoxModeration: Nathan LabenzJohn Milinovich, Canva's generative-AI product lead, walks Nathan Labenz through automation versus augmentation, concept-level interfaces, evals without a design arena, and why application-layer companies still have a decade of room.
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.
1:09:09EN30 Percent on SWE-bench: Cosine Taught Genie How Engineers Actually ThinkModeration: Nathan LabenzAlistair Pullen tells Latent Space how Cosine reconstructed human problem-solving, fine-tuned on billions of tokens, and took the top score on software engineering’s hardest public test.
37:47ENWorking Backwards from AGI: Magic's Five-Million-Token BetModeration: Sarah Guo, Elad GilEric Steinberger wants a coding colleague you trust like a teammate — and a world that is still a good place thirty years after AGI.
46:09ENOriol Vinyals: The Days of Burning 90% of Compute on Pretraining Are NumberedModeration: Sarah Guo, Elad GilGoogle DeepMind’s VP of research on Gemini, long context, the coming shift from pretraining to RL, and why AGI may never have a finish line.
1:21:53ENHippoRAG Matches Iterative Retrieval at One-Tenth the Online CostModeration: Nathan LabenzA hippocampus-inspired knowledge graph lets multi-hop questions skip the brute-force document crawl.
36:20ENA Hundred Million Tokens in Context Would Cost $10 Million. Tengyu Ma Runs the RAG MathModeration: Sarah Guo, Elad GilThe Stanford professor and Voyage AI founder argues that retrieval, not a giant context window, is how enterprises should manage private knowledge.
29:09ENThe Hyperscalers Are Spending $200 Billion — and the Next Bottleneck Is a Power PlantModeration: Sarah Guo, Elad GilSarah Guo and Elad Gil walk through music models, on-device LLMs, long context, and why AI capex now sits beside oil and broadband.
1:27:01ENThree Million Emails, Ten LLM Calls, Six Models: Shortwave's RAG PlaybookModeration: Nathan LabenzFirebase founder Andrew Lee walks Nathan Labenz through the retrieval stack that turned a Gmail inbox into a working AI assistant.
27:32ENFrom a side project to 700 integrations: Harrison Chase on what still blocks agentsModeration: Sarah Guo, Elad GilThe LangChain CEO walks through a two-year churn of patterns, and why memory, planning, and few-shot data still matter more than swapping models.
31:28ENBolt Memory onto GPT-4 and Cut Hallucinations by up to 50%Moderation: Sarah Guo, Elad GilPinecone CEO Edo Liberty tells Sarah Guo and Elad Gil how RAG, serverless vectors, and keeping knowledge outside the model make LLMs more reliable.
42:07ENNotion’s Ivan Zhao: RAG Will Make Organizing OptionalModeration: Sarah Guo, Elad GilThe Notion CEO tells No Priors why he bet the company on GPT-4, why embeddings matter as much as agents, and why software is entering a bundling cycle.
1:43:07ENAn Agent Posted Five Tweets — and 5,000 People Didn't NoticeModeration: Nathan LabenzMultiOn founder Div Garg walks Cognitive Revolution through what web agents can actually do in early 2024, what they cost, and why guardrails have to sit outside the model.
46:36ENAfter a decade of code search, Sourcegraph’s CTO says the coding-AI fight is outside the modelModeration: Sarah Guo, Elad GilBeyang Liu on Cody, why keyword search still does most of RAG, and why CS fundamentals get more valuable as AI compresses the middleware.
1:53:08ENWhen GPT-4 Writes SQL, Four Tables Is the Breaking PointModeration: Nathan LabenzJuan Sequeda on why a knowledge graph is the accurate, explainable brain that foundation models do not have.
1:18:39ENThe GPT-4 Red-Teamer Who Got Unstuck by a Mediocre OutlineModeration: Nathan LabenzDan Shipper shows Nathan Labenz how to use ChatGPT as a copilot for thinking, not as a ghostwriter for his own voice.
1:25:11EN105 lines of code, a million impressions, and a VC who refused to found the companyModeration: Nathan LabenzBabyAGI creator Yohei Nakajima tells Nathan Labenz how a weekend prototype set off the agent wave — and why he went back to writing checks.
1:26:30ENMost of this data has never been in a database: Chroma's wartime CTO on RAGModeration: Nathan LabenzAnton Troynikov returns to The Cognitive Revolution to argue that retrieval quality is mostly the embedding, that Chroma should own the RAG loop, and that GPT still fails a basic Game of Life test of reasoning.
1:40:44ENGive the Model Time, Memory, and Tools: Nathan Labenz’s 2023 Field Guide to Using GPT-4Moderation: Nathan LabenzPart two of the AI Scouting Report walks from H100 clusters and RLHF through chain-of-thought, retrieval, agents, and mixture-of-experts.
1:47:05ENEdit Meaning, Not Tokens: Linus Lee on Latent-Space InterfacesModeration: Nathan LabenzThe Notion AI product lead walks Nathan Labenz through the interfaces, model autopsies, and agency questions behind his research prototypes.
17:22ENDon't Become a Software Factory: Why Context Is the Real ProductModeration: Lenny RachitskyLinear CEO Karri Saarinen argues that as AI automates execution, product teams must protect the learning that makes great products possible.
1:36:57ENDo the Dumb Thing First: A CTO's Playbook for Building an AI Coding AssistantModeration: Jacob EffronSourcegraph CTO Beyang Liu on which AI coding features actually earn daily use, how new models get shipped and evaluated, and why retrieval is still a search problem.
21:31ENRowing or Steering: How Atlassian's PMs Became AI BuildersModeration: Lenny RachitskyAtlassian CPO Tamar Yehoshua explains, through three internal projects, when product managers should write code and when they should guide the team.
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