Episode Details

Most RAG implementations are fundamentally broken; and the company that coined "vector search" just told us why. In this episode, Roie from Pinecone breaks down the "Franken answer" problem plaguing AI systems, why naive retrieval falls apart at scale, and what most teams are getting wrong about evaluation. He reveals how the AutoGPT explosion nearly took down Pinecone's infrastructure overnight — and the radical architecture shift it forced them to build. We dig into why LLMs can't be trusted without grounding, what AI memory will actually look like in the age of agents and robots, and where the line between useful hallucination and dangerous fiction really sits. If you're building anything with RAG, vectors, or agents, this conversation will change how you think about it.

https://www.pinecone.io/