Key Takeaways Automated post-mortem generation is the process of producing an incident retrospective from artifacts already collected during the incident — chat transcript, alert timeline, monitor data, and (in agentic systems) the investigation agent's own tool-call trace. The category is not a single technology; it's an output shared by three distinct architectures. We propose the Postmortem Provenance Model (PPM). Three source types: (1) chat-transcript postmortems (Rootly, incident.io, FireHydrant) summarize what humans said in the channel; (2) observability-stitched postmortems (Datadog Bits AI) summarize what monitors recorded; (3) agentic-investigation postmortems (Aurora) compose from the agent's causal reasoning trace. The three artifacts answer different questions and are not interchangeable. The standards that anchor this work are old, but unchanged by AI.…