I’ve done the same but it’s a moving target as models advance and I find half of my points are ignored until I’m prompting “No wtf why are you still trying to symlink the global Python executable just use the virtual environment that’s already activated”.
Anyway, companies are pouring billions into improving AI tooling user experience so most of what I do manually I just anticipate to be a waste of time. There’s no way my hobby fiddling will outpace whatever gets released in the next couple months.
In the meantime, real linting does work pretty well, if you can write a detector for whatever antipattern you find LLMs fall into (like multiline comments).
Although, given opus 4.8->5.0 experience within claude code, I don't know if I'd agree they necessarily improve things with time. But that's just my experience. I should probably read their release notes, maybe just a tweak to my claude.md would help
I get patches into the biggest AI projects all the time to make inference faster on my 3090 and all you have to do is read the contribution docs and open a small PR.
It’s not a cabal of super geniuses. We are literally in the Wright Brothers era of AI.
You can trivially outpace what big companies are doing it’s insane, why do you think so many innovations are coming out of scrappy Chinese labs? They are willing to engage instead of being defeatist about it.
Not my core competence and I’m not interested in making it a core competence while the field is still rapidly changing. I find harness engineering interesting, but not lucrative enough to push one of the many very important other things on my plate to the backburner.
I don’t think Python language developers are super geniuses either, and I’ve never submitted code for consideration.