There is a lot of noise about AI in monitoring, and most of it promises the wrong thing: a system that tells you what is wrong so you do not have to think. The version worth building is quieter and more useful.
Speed to the right question
An engineer mid-incident does not need a verdict handed down. They need to reach the relevant graph faster, correlate two subsystems without writing a query, and rule things out quickly. AI that shortens the path from question to evidence is doing real work.
Keep the human in the loop
The moment a tool starts hiding its reasoning, it becomes something you cannot trust in a postmortem. The right design is AI-positive and human-final: it surfaces, it suggests, it explains, and a person still decides. Expertise is enhanced, not replaced.
- Use AI to correlate and explain, not to pronounce.
- Keep every suggestion traceable back to the underlying data.
- Leave the decision, and the accountability, with the engineer.
Treated as an assistant, AI makes a good monitoring platform faster to reason with. Treated as an oracle, it just adds a confident voice you cannot audit. The first is worth having. The second is a liability with better marketing.
