I Built an AI SRE Agent That Diagnoses Incidents Before I Open My Laptop

Every on-call engineer knows the ritual.

An alert fires at 3 AM. You fumble for your laptop, pull logs from three services, check the last deploy, stare at a Grafana dashboard, and twenty minutes later discover the “critical incident” was a config typo.

Or worse, nothing at all.

The biggest problem in large-scale distributed systems is not always the outage itself. It is the noise around the outage: half-signals, misleading symptoms, cascading alerts, stale dashboards, and runbooks written during some ancient incident archaeology expedition.

So I spent a few weekends building a semi-autonomous SRE agent that investigates incidents and drafts fixes before I even reach the keyboard.

It combines an LLM’s ability to correlate signals across many sources with the Model Context Protocol for scoped infrastructure access. The agent can investigate, reason, and propose changes. It cannot merge or deploy without a human.

Here is the architecture at a high...

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