Use Retrieval Auditing to Make Agents Aware of Gaps
thisguyknowsai · x · 2026-07-11
This continues with Technique 8: Retrieval Auditing.
The core practice is to record confidence and reasons for each retrieval decision, not just for debugging, but so the model/agent itself can see its retrieval trajectory. This allows the model to determine, 'Although I retrieved relevant chunks, they only partially answered the question; I need to search again.'
The author emphasizes that such a design—letting the system know what it retrieved and what it lacks—makes retrieval agents more proactive in supplementing context.
More from coding & agent
- Security tip: use AI agents to build a NIST CSF knowledge base for incident response — prasanna_says · 2026-10-26
- Google Cloud Adds Self-Learning Context Enrichment to Knowledge Catalog for AI Agents — rseroter · 2026-10-26
- Cloudflare Previews Spend Limits for Workers and Durable Objects, Early Access Open — ritakozlov · 2026-10-26
- Shopify design lead on AI-era workflow: designers are becoming full-stack editors — KlausCodes · 2026-10-26
- Nace AI launches Drex for Search, cutting agent steps 62% and tokens 56% — testingcatalog · 2026-10-26
- Ultrametric open-sources Open Startup Repo to let AI agents run startup operations — garrytan · 2026-10-26