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1:11:56ENHow to Get ChatGPT to Recommend Your Product: A Practical Guide to Answer Engine OptimizationInvitado: Ethan Smith · Presenta: Lenny RachitskyGraphite CEO Ethan Smith explains how AEO differs from SEO, which levers move the needle, and how to measure and test what works.
1:36:57ENDo the Dumb Thing First: A CTO's Playbook for Building an AI Coding AssistantPresenta: 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.
23:54ENBeyond GPT-7: The Customization Toolkit, Meta's Open Source Bet and the Return of Consumer AIPresenta: Sarah Guo, Elad GilIn a host-only episode, the No Priors hosts map the six levers for 10x to 100x better AI, explain fine-tuning, RAG and AI feedback, and ask why consumer social is suddenly interesting again.
57:25ENFrom RAG to Reasoning: Why the Future of AI Is a System, Not a ModelPresenta: Jacob EffronDouwe Kiela explains what OpenAI's o1 reveals about test-time compute, why enterprise AI must be specialized, and where post-training and evaluations are heading.
51:55ENThe Search Engine Under AI Apps: Why Bigger Context Windows Aren't EnoughPresenta: Jacob EffronTurbopuffer CEO Simon on object-storage databases, vector-search trade-offs, and the AI features that will become SaaS table stakes.
46:48ENSnowflake's AI Stack: Small Models, the Text-to-SQL Iceberg, and Why Governance Comes FirstPresenta: Jacob EffronSnowflake head of AI Baris Gekken explains how Arctic and Cortex were built, where enterprise AI actually works today, and why precision, governance and evaluation matter more than raw model capability.
1:06:22ENPerplexity's Bet: Search Becomes Answers, and Answers Become a BusinessPresenta: Jacob EffronThe Perplexity CEO explains how a consumer AI search product is built, sequenced, and defended against Google.
32:41ENHow IBM Watson Won Jeopardy: A Moonshot Built on Engineering, Not a BreakthroughInvitado: David Ferrucci · Presenta: Lex FridmanDavid Ferrucci tells Lex Fridman how he talked IBM into the Jeopardy challenge and how his team built Watson's search, scoring and confidence machinery in about four years.
1:01:13ENPinecone's Vector Database Bet: Scaling Through the ChatGPT TsunamiPresenta: Jacob EffronEdo Liberty explains how Pinecone scaled through the generative AI boom, why vector search is more than a database add-on, and where he sees the next AI infrastructure shifts.









