The Problem Wasn’t Triage Most AI workflows in software engineering still keep the human directly in the middle of triage. The AI might help write code. It might explain a stack trace. It might summarise a pull request. But the operational loop itself still depends on someone noticing the issue, prioritising it, investigating it, and deciding whether it matters. I recently shipped a new feature in one of my side projects. The feature itself worked well and was tested properly, but a reasonably significant crash slipped through because it never crossed the notification thresholds in Firebase Crashlytics. Had I not gone looking manually, I probably would never have known. That was the moment the idea started forming. Building the Workflow Hermes already had access to Crashlytics through MCP tooling, so I started experimenting with whether the entire discovery and investigation process could be automated.…