everyone's focused on whether their agent works. almost nobody asks if it's actually getting better over time

been thinking about this a lot lately and i think there's a blind spot most of us have. there's tons of conversation around whether agents complete tasks. did it finish the run, did it hit the goal, does the output look right. and yeah, obviously that matters. but it kinda feels like we've collectively decided that's the whole question and just... moved on. what almost nobody seems to be asking is: is the agent actually better at run 500 than it was at run 5? because if nothing is being captured between runs, what broke, what worked, what kept failing in the same exact spot then you're not running a system that learns. you're running the same system on loop. and any improvement is coming from you manually patching things, not from the agent getting smarter about its own failure modes. the completion rate looks fine. the agent is "working." but it's working exactly as well as it did on day one. and it'll keep working exactly that well indefinitely unless someone intervenes by hand every time. i don't think people realize how common this is. most production agent setups i've seen have decent visibility into whether tasks finished. almost none of them have anything that actually feeds failure patterns back into future runs in a structured way. like, monitoring tells you what broke, great. but knowing what broke and actually doing something with that information so the next run benefits from it? completely different problem. and i haven't seen many teams actually solving it.