We fed 300 real incidents to an AI pipeline. The context patterns that emerged changed how we think about agent knowledge.
The Experiment
We had a hypothesis: if you feed real operational incidents to an AI agent pipeline, the agent's failures would tell you exactly what context your enterprise is missing.
Not what context you think you need. What context you actually need, proven by evidence.
So we ran the experiment. 300 real incidents from a complex enterprise domain — 12 teams, 80+ microservices, multiple vendor systems, a 6-year transformation in progress. We built a pipeline that processed each incident and asked: what context did the agent need to resolve this? What context was available? Where did it fail?
