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Using AI generated code will make you a bad programmer. (slopwatch.com)

submitted 4 days ago* (last edited 4 days ago) by [email protected] to c/[email protected]

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[–] [email protected] 20 points 2 days ago (2 children)

I've been writing code professionally for nearly two decades, and I love having copilot available in my IDE. When there is some boilerplate or a SQL query I just don't want to write, it'll oftentimes get me started with something reasonable that is wrong in a couple of subtle ways. I then fix it, laugh at how wrong it was, or use part of the proposed answer in my project.

If you're a non-corder, sure it is pure danger, but if you know what you're doing it can give you a little boost. Only time will tell if it makes me rusty on some basics, but it is another tool in the toolbox now.

[–] [email protected] 2 points 1 day ago* (last edited 1 day ago)

Same here (15 years). I work in all sorts of frameworks and languages. I normally would have just googled a given question to see the code i need, paste it in with everything that's wrong, and fix it to my liking. I know what I'm doing I was just missing the specific words i havent used in a couple years, i still understand them. Copilot just avoid me opening google, clicking through some bad SEO, passing the bad answers, and doing that a couple more times to bring in everything I need. It's a google formatter.

It's also exactly like searching google. If you ask "is this cancer" you'll find cases where it's cancer, if you ask "is this not cancer" youll find cases where it's cancer. You can't trust it in that way, but you can still quickly parse the internet. I make juniors explain their code so even if they paste it in, they're kind force to research it more to make sure they get it; it's on the reviewers now to train llm kiddos.

[–] [email protected] 3 points 2 days ago

For me personally, there is only two applications of LLMs in programming:

doing tasks I kinda know how to do, but don't want to properly learn (recent example: generate pgf plots from csv data in matplotlib. 90% boilerplate, I last had to do it 3 years ago and vaguely remember some pitfalls so can steer the LLM in that direction. Will probably never again have to do this, so not worth the extra couple hours to properly learn
things I would ordinarily write a script for, but aren't worth automating because they won't come up in the future again (example: convert this Lua table to a Nix set)

Essentially, one-off things that you know how to check for correctness.