Northbound AI Summit 2026

Retrieval went from research afterthought to the load-bearing wall of production AI, and most of what made it work for us was not in any paper. This keynote traces one retrieval stack over three years: naive vector search, the hybrid rebuil…

Vector search is a great first chapter and a terrible whole book. In production, the retrieval systems that hold up are hybrids: lexical search for precision, embeddings for recall, structured filters for correctness, and a reranker to arbi…

The fastest and cheapest LLM call is the one you never make. But semantic caching — reusing an answer because the question is "close enough" — is a correctness gamble that has burned every team that treated it as a drop-in. This talk maps…

SQLite at the edge changes what a migration even is: no maintenance window, no replica to fail over to, and a write path you share with live traffic. We have run 40+ schema migrations on D1 databases serving production requests, and this ta…