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Developer Builds Incident-Response AI Agent Trained on 104 Real Tech Postmortems

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A software developer built an AI incident-response agent using the OpenSRE dataset of 114 real postmortems from companies including Slack, GitHub, AWS, and Cloudflare. The developer retained 104 incidents in a memory bank, which were processed into 946 discrete memories connected by over 7,000 links. The core motivation was teaching the agent to recognize 'trap actions' — remediation steps like rollbacks or restarts that historically worsened outages rather than resolved them. In a test scenario involving a checkout service returning errors after a deployment, the memory-equipped agent correctly identified a likely dependency issue and warned against rollback, while the same model without memory fabricated details and recommended the potentially harmful rollback. The developer acknowledges no formal comparison was run against synthetic data, framing the project as a practical experiment rather than a rigorous benchmark.

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