# Vector Search and RAG: A Primer (opens in new tab)

A short learning path from a weekend project: I indexed my personal markdown notes (~800 chunks), tried a few local embedding models, stored the same vectors in four different backends, and wired up simple RAG. Not a production guide — just the basics, with honest results from a corpus small enough to reason about. The idea, without the jargon pile Keyword search looks for shared words. Vector search converts text into a list of numbers (an embedding), treats that list as a point in space, an...