Tag: vector database metadata

Every RAG tutorial ends at the same two steps: embed and query. You chunk your documents, store (id, embedding), run a nearest-neighbour search, and the demo works. Then you put it in front of real users and it quietly falls apart. The vector was never the hard part. What you store next to it is.…