Why I used a 50-year-old algorithm instead of embeddings to cut Claude API token costs

I built Prism — a local proxy that routes only relevant knowledge to Claude per query using BM25, with zero extra API calls, zero embeddings, and zero vector databases. Every time you send a prompt to Claude, it considers its entire knowledge space. A question about a React bug still costs tokens on geography, cooking, history, and every other domain Claude was trained on. Nobody talks about this because the context window is large enough that it "works." But it's wasteful by design — and it pro