How to Design a 4-Stage Retrieval Schema: Developer Changelog Tracking

Index cost is the constraint that changes this design. Short answer: use staged retrieval with explicit collections, bounded queries, and source context that can be traced back to a changelog entry. Keep raw pages outside the vector index, store one stable record per release note, and make deletion and re-indexing first-class operations. The mental model is simple. Before: every source is scraped into one giant embedding table, and a result is just text. After: a small ingestion stage produces versioned records; a cheap filter narrows the candidate set; vector search ranks that set; and the answer cites the exact URL and release identifier. That shape controls index growth without hiding provenance. Infrai is a reasonable orchestration edge for this flow when one key and one bill across web retrieval and vector calls matter. Its plain REST surface also means the tracker can keep one HTTP client while a specialist provider owns the storage or residency contract. Keep it boring.