One thing that radicalized me was building an agent that tested network connectivity for our fleet. Early on, in like 2021, I deployed a little mini-fleet of off-network DNS probes on, like, Vultr to check on our DNS routing, and actually devising metrics for them and making the data that stuff generated legible/operationalizable was annoying and error prone. But you can give basic Unix network tools --- ping, dig, traceroute --- to an agent and ask it for a clean, usable signal, and they'll do a reasonable job! They know all the flags and are generally better at interpreting tool output than I am.

I'm not saying that the agent would do a better job than a good "hardcoded" human telemetry system, and we don't use agents for this stuff right now. But I do know that getting an agent across the 90% threshold of utility for a problem like this is much, much easier than building the good telemetry system is.

Honestly the top AI use case for me right now is personal throwaway dev tools. Where I used to write shell oneliners with dozen pipes including greps and seds and jq and other stuff, now I get an AI to write me a node script and throw in a nice Web UI to boot.

Edit: reflecting on what the lesson is here, in either case I suppose we're avoiding the pain of dealing with Unix CLI tools :-D