Lawrence Jones - Fighting AI with AI#

Lawrence Jones — incident.io

• Why: The most direct instance of "ML for infrastructure operations" in the program: an autonomous AI SRE that investigates production incidents by digging through logs, metrics, traces, and code changes, plus the meta-tooling needed to operate such a system.
• What: incident.io's AI SRE — a deeply nested tree of agents working ambiguous problems against nondeterministic telemetry — and the internal tooling built to debug it: an eval CLI with red-green runbooks agents can follow end-to-end; agent traces serialized as markdown so other agents can reason about them (turning hour-long debugging into five-minute conversations); a pipeline of 25 parallel agents each analyzing an investigation, then clustering results to surface systemic patterns; and AI dogfooding feedback loops.
• How: Give agents the same debugging information engineers use, in agent-readable formats (serialized traces, structured runbooks), then use parallel AI analysis to surface patterns humans act on.
• Where applicable: The speaker explicitly states none of it requires exotic infrastructure — patterns transfer to any team operating complex agent systems. The product context is incident.io-specific, the meta-tooling patterns are general.