A developer iterates through three rounds of building hybrid search (semantic + lexical) for their personal site. Pure vector search failed to surface exact-match results like library names and API identifiers. The solution combines Cloudflare Vectorize for semantic search with SQLite FTS5/D1 for lexical BM25 search, fused via Reciprocal Rank Fusion. A critical production bug emerged when synchronous SQLite writes blocked the entire Node.js server during foreground requests. The fix moved all search logic into a dedicated Cloudflare Worker with its own D1 database, then a third round unified both semantic and lexical search into a single worker. Key lessons: keep index maintenance off the request path, avoid split architectures when possible, and AI agents make iterative redesigns cheap enough to actually do.
