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20:58ENVinoo Ganesh on Making Financial AI Cite Every NumberVinoo Ganesh · KeplerKepler CEO Vinoo Ganesh explains why financial AI should retrieve and cite figures while deterministic software handles the math. His design makes traceability, retrieval quality, and tenant security part of the answer itself.
2:38:48ENA thousand searches for five cents, and a high score that did not require cheating진행자 Nathan LabenzOn a Cognitive Revolution morning show, Ceramic’s Anna Patterson collides cheap search with GPT-5.5’s clean Vending-Bench run, Zvi’s case for model welfare, and analog chips that cut matrix-multiply energy about thirtyfold.
1:25:10ENA Tenth of Google's Index, 99.9% Recall: How 20 People Built Brave Search진행자 Nathan LabenzJosep M. Pujol walks Cognitive Revolution through Brave's privacy-first index, hybrid retrieval stack, and the Search API Nathan Labenz now wants his own product team to use.
1:27:01ENThree Million Emails, Ten LLM Calls, Six Models: Shortwave's RAG Playbook진행자 Nathan LabenzFirebase founder Andrew Lee walks Nathan Labenz through the retrieval stack that turned a Gmail inbox into a working AI assistant.
1:23:09ENThe Right Size of an AI Task Is Whatever You Can Check진행자 Nathan LabenzElicit founders Andreas Stuhlmüller and Jungwon Byun walk through how a twelve-person research assistant cut summary hallucinations from 1.5 to 0.5, ships about every week and a half, and treats task decomposition as the way to spend more compute without a black box.
Google Gives You 33 Million Results. Exa Wants 54.진행자 Nathan LabenzWill Bryk, CEO of Exa, tells Nathan Labenz why search and research are different jobs, and why an AI librarian for the web has to be neural from the first filter.
1:32:19ENHis 2018 Prompting Paper Was Rejected. His Search API Now Beats Google진행자 Nathan LabenzRichard Socher traces You.com from a rejected unified NLP model to an LLM-native web index, three assistant modes, and a very low P(doom).
1:26:30ENMost of this data has never been in a database: Chroma's wartime CTO on RAG진행자 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.
58:54ENModels Are Commodities. Perplexity's CEO Says the Index Is the Moat진행자 Nathan LabenzAravind Srinivas returns to Cognitive Revolution to explain how a 25-person search startup is building its own crawler, index, and models before the big platforms raise the drawbridge.
1:44:19ENTen People Versus Google’s $282 Billion Search Machine진행자 Nathan LabenzPerplexity founder Aravind Srinivas tells Nathan Labenz why citations, speed, and value per minute — not chat bubbles — are how a tiny team competes with Google.
1:30:59ENThe SEO Playbook: Why Topics Beat Keywords and Shipping Beats Strategy진행자 Lenny RachitskyEthan Smith, CEO of Graphite, explains when SEO is worth investing in, how to reverse-engineer the page types Google rewards, and why most SEO strategies never get built.
37:00ENInside the YouTube Algorithm: Related Graphs, Satisfaction Surveys and the Viewers Who Are Part of the Code진행자 Lex FridmanYouTube's head of search and discovery, Cristos Goodrow, explains to Lex Fridman how search and recommendations work, which signals matter, and how the team measures whether viewers are better off.
51:55ENThe Search Engine Under AI Apps: Why Bigger Context Windows Aren't Enough진행자 Jacob EffronTurbopuffer CEO Simon on object-storage databases, vector-search trade-offs, and the AI features that will become SaaS table stakes.
1:06:22ENPerplexity's Bet: Search Becomes Answers, and Answers Become a Business진행자 Jacob EffronThe Perplexity CEO explains how a consumer AI search product is built, sequenced, and defended against Google.








