[hn_throwaway_99]

This is my experience as well. There are a couple things I love using AI for, like learning new programming languages or technologies (I consider myself an expert in Java and NodeJS, and proficient in Python, but I recently took a job where I had to program in an unfamiliar language), and it's been great for programming up short little "apps" for me for things I want - I've built a slew of browser apps for myself that just save stuff to local storage so that I can easily put it up on GitHub pages (and then I create import and export functions if I switch browsers - export just opens a mailto link where the body just contains a link with the state as a param, so then I just save that email, open it up on a different device and click on the link).

But I've found that there are a lot of places where it kind of falls over. I recently had Cursor do a large "refactoring" for me, and I was impressed with the process it went through, but at the end of the day I still had to review it all, it missed a couple places, and worse, it undid a bug fix that I put in (the bug was previously created when I had AI write a short function for me).

The other thing the makes me really worried is that AI makes it easy to be lazy and add tons of boilerplate code, where in the old world if I had to do it all manually I would definitely have DRY-ed stuff up. So it makes my life immediately easier, but the next guy now is going to have a shit ton more code to look at when they try to understand the project in the first place. AI definitely can help with that understanding/summarization, but a lot of times I feel like code maintenance is a lot of finding that "needle in a haystack", and AI makes it easy to add a shit ton of hay without a second thought.