I read a post on Lobste.rs last week about dreading our LLM-written incident report future, and it hit a massive nerve. We've reached a point where the moment production stops burning, our next instinct's to automate the thinking.
I'm tired of reading beautifully formatted incident reviews that read like they're written by a consultant who's never seen a terminal. They've all the right sections, the timelines are perfectly clean, and they explain absolutely nothing about why we actually broke.
This connects to something I was chewing on last week when I wrote about the cultural bankruptcy of tracking developer activity through screen recordings. If you treat engineering like a factory where every input must be logged and optimized, you end up destroying professional trust. Writing incident reports with AI's the same disease, just looking from a different angle. It treats the post-mortem as a chore to be automated, rather than the literal mechanism of how we learn as an organization.
Let me tell you how this plays out in reality.
Last month, we'd a really nasty incident in the Incident Response channel on Microsoft Teams. It started around 4 PM on a Thursday. Our product detail pages started throwing server errors. This was a nightmare because we were right in the middle of a high-profile marketing campaign.
