Assuming AI agents are not the cause of the incident.

AI is good at incident diagnosis, but AI slop code may have actually caused this: designing to avoid cascading failures is something AI doesn't do so well

The place where I consistently see AI/LLMS/Agents/language-widgets-with-tools fail at making decent code (and more often configuration) is infrastructure.

The number of times it has spit out a python program where a much simpler bash script would do, is too many to count.

I have a pet theory that if you don't know what you really want, and aren't skilled enough to understand what you got, infra code is THE WORST.

Anecdote: I wanted a simple change to an ansible playbook today. GPT-6-Astra/codex came up with the most convoluted, brittle solution possible the first time, even though it was extending and already clear, idiomatic playbook. It took some amount of offensive and critical prompting to get it to use ansible's built in modules and tooling to do the same job - and do so with nearly 80% less configuration and like 1000% more human readability.

Some part of me harbours a sneaking suspicion that the "throw everything at it" ethos is by design, not as a defensive measure against crappy code, but as a way to ensure there's so much code and it's so convoluted orgs and operators (or developers) are stuck/addicted.

It's still a force multiplier - but it's by no means driverless, especially for existing/already-running infra.