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What Actually Makes AI Infrastructure Agents More Reliable (It's Not More Agents)
I keep seeing the same pattern. Someone builds an "AI agent" for infrastructure monitoring — it answers questions about Prometheus metrics, pulls logs from ELK, suggests restarts. Impressive in a demo. Then you push on it: what happens when its logs query times out mid-investigation? What happens when the context window fills up while correlating signals across four systems? What happens when a tool call hallucinates a metric name that doesn't quite exist?Usually it doesn't fail catastrophically. It fails quietly, in ways that are hard to debug. And quiet failures during incident response are the worst kind.