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44:26ENAn AI Application Is Still an ApplicationMongoDB's Sahir Azam tells Sequoia why vector search is a new primitive for unstructured data, not a replacement for transactions, and why retrieval quality is the last mile that gets AI into conservative enterprises.
1:27:01ENThree Million Emails, Ten LLM Calls, Six Models: Shortwave's RAG PlaybookHost Nathan LabenzFirebase founder Andrew Lee walks Nathan Labenz through the retrieval stack that turned a Gmail inbox into a working AI assistant.
Google Gives You 33 Million Results. Exa Wants 54.Host 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.
31:28ENBolt Memory onto GPT-4 and Cut Hallucinations by up to 50%Host 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.
1:26:20ENForty Dollars to Index Joe Rogan: Chroma, Shovels, and the Wright Flyer Era of MLHost Nathan LabenzChroma co-founder Anton Troynikov on embeddings as the storage layer for language-model apps, Stable Attribution, and why machine learning is still flying on intuition.
51:55ENThe Search Engine Under AI Apps: Why Bigger Context Windows Aren't EnoughHost Jacob EffronTurbopuffer CEO Simon on object-storage databases, vector-search trade-offs, and the AI features that will become SaaS table stakes.
1:01:13ENPinecone's Vector Database Bet: Scaling Through the ChatGPT TsunamiHost 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.








