Add retrieval (RAG) when context isn't enough

Your Claude feature needs to answer from your own data — internal docs, a knowledge base, product specs — and the model doesn't have it. So it either makes things up or says nothing useful. RAG (retrieval-augmented generation) fixes that by fetching the relevant chunks of your data and putting them in the prompt at answer time. This is the full path: decide whether you even need it, chunk and embed your docs, store them in pgvector on Supabase, retrieve and rerank for a query, and build a grounded prompt that cites sources and admits when it doesn't know.