this post was submitted on 05 Dec 2023
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Honestly, the best use for AI in coding thus far is to point you in the right direction as to what to look up, not how to actually do it.
Yeah, that's about it. I've trown buggy code at it, tell it to check it, says it'll work just fine... scripts as well. You really can't trust anything that that thing outputs and it's more than 1 or 2 lines long (hello world examples excluded, they work just fine in most cases).
Have you looked at the project that spins up multiple LLM "identities" where they are "told" the issue to solve, one is asked to generate code for it, the others "critique" it, it generates new code based on the feedback, then it can automatically run it, if it fails it gets the error message so it can fix the issues, and only once it has generated code that works and is "accepted" by the other identities, it is given back to you
It sounds a bit silly, but it turns out to work quite well apparently, critiquing code is apparently easier than generating it, and iterating on code based on critiques and runtime feedback is much easier than producing correct code in one go
The software that implements multi agents called ChatDev, it's significant more capable than one agent working alone. The ability to critique and fix bugs in the code in an iterative process gives a massive step up to the ability of the AI to program.
Granted it might still get in a loop between the programing and testing departments, but it's a solid step in the right direction.
I was thinking of AutoGPT, but nice to see there are multiple projects taking a crack at this approach