You alluded to it, but also:

3) Not everyone codes the same things

4) It's easy to get too excited about the tech and ignore its failure modes when describing your experiences later

I use AI a lot. With your own control plane (as opposed to a generic Claude Code or whatever) you can fully automate a lot more things. It's still fundamentally incapable of doing tons of tasks though at any acceptable quality level, and I strongly suspect all of (2,3,4) are guiding the disconnect you're seeing.

Take the two things I've been working on this morning as an example.

One was a one-off query. I told it the databases it should consider, a few relevant files, roughly how that part of the business works, and asked it to come back when it finished. When it was done I had it patch up the output format. It two-shot (with a lot of helpful context) something that would have taken me an hour or more.

Another is more R&D-heavy. It pointed me to a new subroutine I needed (it couldn't implement it correctly though) and is otherwise largely useless. It's actively harmful to have it try to do any of the work.

It's possible that (1) matters more than you suspect too. AI has certain coding patterns it likes to use a lot which won't work in my codebase. Moreover, it can't one-shot the things I want. It can, however, follow a generic step-by-step guide for generating those better ideas, translating worse ideas into things that will be close enough to what I need, identifying where it messed up, and refactoring into something suitable, especially if you take care to keep context usage low and whatnot. A lot of people seem to be able to get away with CLAUDE.md or whatever, but I like having more granular control of what the thing is going to be doing.