Beyond RAG: Hybrid Search, Agentic Retrieval, and the Database Design Decisions That Actually Matter
· 8 min read
Most teams ship RAG and call it a retrieval strategy. They chunk documents, embed them, store the vectors, and run nearest-neighbor search at query time. It works well enough in demos. In production, users start reporting that the system can't find an article they know exists, misses error codes verbatim in the docs, or returns semantically similar but factually wrong passages.
The problem isn't RAG. The problem is treating retrieval as a one-dimensional problem when it's always been multi-dimensional.
