Pip: Welcome to Azure Advice, where the cloud is always partly cloudy and the root cause is always the database — until it isn't.
Mara: Christoph Corder has a post up this week on exactly that problem: how to interrogate AI-generated root-cause analysis before you act on a conclusion that only looks right.
Pip: Let's get into it.
Challenging AI Root-Cause Analysis
Mara: The core tension here is that AI-generated diagnoses are hypotheses, not findings — and the danger is that a wrong one looks identical to a right one.
Pip: The post puts it plainly: "Its wrong answers look exactly like its right ones. Same structure. Same confidence. Same clean timeline. It will tell you the SNAT ports were exhausted with the calm certainty of someone who has never opened a netstat."
Mara: So the upshot is: fluency is not evidence. A well-formatted RCA has earned nothing until someone has actually pushed back on it.
Pip: And pushing back is exactly what the CHRIS Protocol is for — five structured stages run against every AI conclusion before anyone acts on it.
Mara: Counter comes first: ask for the strongest argument against the conclusion before anything else. The post explains this breaks the model's anchor on its own answer while that anchor is still soft — otherwise you get a token objection that waves at itself and then agrees.
Pip: Then Hidden assumptions, which is where the protocol gets uncomfortable. Every RCA assumes the logs are complete, that the first event caused the second, that guidance for one SKU applies to this one.
Mara: The follow-up question the post recommends is: "Which of these is least certain, and how does your answer change if it is false?" That second clause is doing most of the work.
Pip: Reconcile comes third — paste actual log lines, name the counter, give the timestamp. Vague evidence gets a vague yes, and as the post notes, AI produces vague yes at industrial scale.
Mara: Invalidate is stage four: ask what observation would change the answer. A conclusion that cannot name its own falsifier is, in the post's words, "an opinion with formatting."
Pip: Stage five, Stress-test, moves the whole review to a fresh session on a different model — because the model that produced the answer is otherwise sitting on its own jury.
Mara: The post closes with a case library of real App Service RCAs that read well and were wrong: absence of an error treated as proof of health, alarming log lines promoted to root cause simply because they were alarming.
Pip: A conclusion that survives the protocol is worth acting on. One that didn't get the protocol is, as the post puts it, a future incident with a ticket number you haven't been assigned yet.
Mara: The through-line is evaluation over trust — turning a fluent answer into a checkable one.
Pip: Next time: presumably more ways to make the cloud slightly less on fire. See you then.
