I recently asked ChatGPT to generate some boilerplate code in C to use libsndfile to write out a WAV file with samples from a function I would fill in. The code it generated casted the double samples from the placeholder function it wrote to floats to use sf_writef_float to write to the file. Having coded with libsndfile over a decade ago, I knew that sf_writef_double existed and would write my calculated sample values with no loss of precision. It probably wouldn't have made any audible difference to my finished result but it was still obviously stupidly inferior code for no reason.

This is the kind of stupid shit LLMs do all the time. I know I've also realized months later that some LLM-generated code I used was doing something in a stupid way, but I can't remember the details now.

LLMs can get you started and generate boilerplate, but if you're asking it to write code in a domain you're not familiar with, you have to understand that — if the code even works — it's highly likely that it's doing something in a boneheaded way.

It's not only coding.

Idiocracy incoming in 3, 2, 1

One major problem I have with Copilot is it can’t seem to RTFM when building against an API, SDK, etc. Instead, it just makes shit up. If I have to go through line by line and fix everything, I might as well do it myself in the first place.

I use ai for my docker compose services. I basically just point it at a repo and ask it to Start the service for me. It creates docker compose files tries to run it, rwads logs and troubleshoots without intervention

When I need to update an image i just ask it to do so.

Ai also controls my git workflow. I tell it to create a branch and push or revert or do whatever. Super nice

Ai isn't perfect but it's hella nice for us who used to work closely with tech a decade ago but have since moved to move architect / resale roles with kids and just don't have the time and resources.

I know I'll get hate for this on lemmy though

But yeah, I think it's pretty great. As long as you have basic understanding of whatever it's going you can get pretty far and do a lot of fun stuff

Yeah, the places to use it are (1) boilerplate code that is so predictable a machine can do it, and (2) with a big pinch of salt for advice when a web search didn't give you what you need. In the second case, expect at best a half-right answer that's enough to get you thinking. You can't use it for anything sophisticated or critical. But you now have a bit more time to think that stuff through because the LLM cranked out some of the more tedious code.

I've tried vibe coding two scripts before, and it's honestly brain-fog-inducing.

Llm coding won't be a thing after 2027.

We’re replacing that journey and all the learning, with a dialogue with an inconsistent idiot.

I like this about it, because it gets me to write down and organize my thoughts on what I'm trying to do and how, where otherwise I would just be writing code and trying to maintain the higher level outline of it in my head, which will usually have big gaps I don't notice until spending way too long spinning my wheels, or otherwise fail to hold together. Sometimes a LLM will do things better than you would have, in which case you can just use that code. When it gives you code that is wrong, you don't have to use it, you can write it yourself at that point, after having thought about what's wrong with the AI approach and how what you requested should be done instead.

The first article in the comments is a good response https://unixdigest.com/articles/if-youre-a-programmer-and-you-feel-depressed-by-ai-dont-be.html

i don't think so