I've had a lot of bad experiences with current chatgpt (mainly, it tends to just get sidetracked and hyper-fixated on literally anything, so if I give it a rodmap of tasks to do it will fixate on the first one and keep adding caveats as to why something isn't complete) and a lot more success with Claude (not) doing that. But I don't use Codex, but chat chatgpt (I don't have the max plans so Codex gobbles up usage limits in like 20 minutes even on the simplest of tasks) so Idk, maybe that's why?

To counter the bad though: right now Claude and I have been doing some very interesting work on acoustics and advancing steam audio. I've been researching this for several years trying on and off again to make my hopes a reality but could never take all the math and make something coherent out of it by hand, and Claude has helped with that (well, and Steam Audio). The trouble mainly comes from being blind and trying to build geometry from code and not being able to mentally visualize the geometry in question (which is also why I struggle with physics engines). It's been really fun just experimenting with this and seeing how good it gets. Who knows, I might make it a library that I publish someday.

> I hear people around me talking about a bad experience they had with ChatGPT last summer as though it proves all AI coding is “slop”.

They always quit right before it got good.

> Honestly, it makes me sad for them.

The the consternation? They’re going to be obsoleted in no time anyway, so we’re told. Are they missing out on some months’ worth of coasting as meat proxies before exponential takeoff? Is that the sad part?

Current models are still worse than I am, or any competent developer I've ever worked with. You act as though people tried ChatGPT in 2023 and gave up forever, but that isn't what is happening here. The cold hard truth is that, contrary to what AI boosters claim, LLMs still suck at programming and output slop.