rag-freshnesslisted

# RAG freshness A retrieval index is a snapshot that starts drifting immediately. The failure is quiet and serious: an answer confidently cites a policy that was superseded last month, with a citation that makes it look verified. ## Method 1. **State the staleness budget per source.** Minutes for operational data, days for documentation. It determines the whole update strategy (see search-indexing-pipeline). 2. **Update incrementally on change events.** Reindexing everything on a schedule is expensive and still leaves a window; capturing changes as they happen is both cheaper and fresher. 3. **Propagate deletions immediately.** A removed document that stays retrievable is worse than a stale one, especially where the removal was for accuracy or permission reasons. 4. **Re-chunk and re-embed on substantive change.** A minor edit may not warrant it; a rewrite does, and treating all edits alike either wastes work or leaves stale vectors (see chunking-strategies). 5. **Carry the source timestamp into the chunk.** The model can then qualify its answer, and users can judge for themselves (see citation-grounding). 6. **Detect drift by sampling.** Periodically compare indexed content against the source to catch pipeline failures that produce silent staleness. 7. **Alert on indexing lag.** A stalled pipeline looks identical to a working one from the answer side until someone notices a wrong answer. ## Boundaries Freshness costs indexing wo