I was in the “AI is grossly overhyped” camp because I work on large distributed deep learning training jobs and AI is indeed worthless for those, and will likely always be worthless since the APIs change constantly and the iteration loop is too cumbersome to constantly resubmit broken jobs to a training cluster.

Then I started working on some basic grpc/fullstack crap that I absolutely do not care about, at all, but needs to be done and uses internal frameworks that are not well documented, and now Claude is my best friend at work.

The best part is everyone else’s AI code still sucks, because they ask it to do stupid crap and don’t apply any critical thinking skills to it, so I just tell AI to re-do it but don’t fuck up the error handling and use constants instead of hardcoding strings like a middle schooler, and now I’m a 100x developer fearlessly leading the charge to usher in the AI era as I play the new No Man’s Sky update on my other PC and wait for whatever agent to finish crap.

Ah I see what my goal for this year is then. I have a large Steam backlog to work through. Unfortunately we currently code in short bursts and mostly are trying to figure out how these integrations are supposed to happen and why the different teams tell us different things

this weirdly skirts my own experience yet somehow still read like sarcasm hehe. I think if we just return to calling it intelligent autocomplete expectations for productivity gain would be better established.

trying to hacksmash Claude into outputting something it simply can't just produces endless mess. or getting into a fight pointing out issues with what it's doing and it just piles on extra layer upon layer of gunk. but meanwhile if you ask it to boilerplate an entire SaaS around the hard part, it's done in about 15 seconds.

of course this says nothing about the costs of long term maintainability, and I think everyone by now recognises what that's going to look like