> My problem with AI is that it now excels at the part of the job that was my favorite (writing code)

My problem is it doesn't even do that. LLMs still aren't good at writing code (despite the hype) and you have to review everything they produce, which takes just as long as writing it myself would. But the industry is falling all over itself to use them to write code, doing a worse job than humans would. It's extremely frustrating.

I agree it’s very mixed, it strongly depends on what you are developing, how big and established your codebase is, how opinionated you are about simple vs overdone, how many subtle and nonlocal interactions your codebase has, etc. Plus the more experienced you are the more you are likely to reject the AI solution as not well considered, whereas to someone new may think it looks plausible and confident.

Yes, they're very good at writing code now. The problem is that we (or at least I am) drowning in code that runs and does that resembles the problem you asked it to solve, but that something is frequently semantically incorrect.

Something has to give; the constant onslaught of slop and workflows changing every few months just isn't sustainable. Either we slow the fuck down and figure out what we're even doing here, or the AI improves so much that we're all out of a job.

They're great and you don't have to review everything.

From what you're always commenting, I could believe that you were exclusively using Haiku 4.5, which would explain how the tool produces only garbage while the rest of the world pretends AI was great.

Just out of curiosity, do you use like Opus 5.5 in Claude Code, and you still find the results inadequate?