Publishing Your Own Accuracy: Making Verification the Product
Part 1 opened with a talk called “AIOps: Prove It!”, an open letter from Charity Majors and Fred Hebert asking vendors selling AI to SREs for data on how often their systems produce useful, actionable results. That question sat behind every decision in Part 2 and Part 3. This part tries to answer it. The short version: a tool that tells you what is wrong, and never checks whether it stayed wrong, is asking for trust it has not earned. So verification is not a feature bolted on at the end here. It is the output. ...