Wasn’t there recently an article on Lemmy about all the bullshit AI pull requests that FOSS maintainers have to put up with?
All over tbh, most devs are using it to some degree now.
However it’s not an “AI” FOSS contribution, it’ll be Doug contributing, or Pardep, or whatever.
They just quietly used AI like a normal person for some basic parts of the code to get it done faster, then tweaked it to look better.
I’d expect most FOSS projects with contributions in the past 6months have bits and pieces, a line here or there, written in AI
That’s the thing, when the AI performs well, you wouldn’t even be able to tell AI was used
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Then you are deeply out of touch with communities. I rarely encounter anyone who hasn’t used LLMs in their coding workflows in some way at all.
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The vast majority of the time it’s help is in the form of quickly pulling the specific line of info I need from thousands of pages of (insert tool here)'s documentation
It’s mostly saving me time on quickly locating the specific documentation I need, so I can jump straight to it and then read the surrounding info, or double check if it’s had changes lately, etc.
Vector database fuzzy searching goes brrrrrrr
quietly used AI like a normal person
Is ai use normal though? Maybe for you and many others but the existence of these communities, articles, and folks who just don’t get much out of it despite industry cramming it down everyone’s throat would suggest it’s anything but normal.
I work at a very big company with humdreds of debelopers.
We gotamdatory training awhile ago, and it’s now very much normalized as a concept.
It’s no longer a question of does a dev use it, it’s a question of how much
Some use it rarely, others a lot.
I don’t doubt it’s normalized in big companies. I imagine the bigger the company, the more ai they use. Big companies have the most to gain from the reduced-workforce ai sales pitch, and the biggest (meta, google, microsoft, etc) need a return on their ai investment (I’ve yet to hear of any demonstrable roi).
It makes sense that anyone in those companies would see it as normal, but it strikes me as an observer bias or frequency illusion. There’s so much ai hype. That is, after all, where the ad money and investments are flowing, but I also see a ton of skepticism, fatigue, and general disenchantment with it, which aligns with my experiences: that it doesn’t compare to a good system of books, notes, and bookmarks-- and that’s not even considering the costs (monetary, environmental, social, and political) which seem completely oversized. So that’s why I remain skeptical of the claim that normal people use ai.
I also participate in nearly a dozen different coding oriented discord channels over numerous frameworks/languages
Across countless individuals ranging from total newbs to professionals, basically everyone at least to some degree uses LLMs in some manner for coding, and it’s an openly discussed and common topic.
You are deeply out of touch with what programmers are actually doing if you seriously think folks who still havent worked an LLM into their process somehow arent the minority.
Confirmation bias and anecdotal information, but hey, feel free to speak in absolute terms. If you read the article you’d realize you’re making a claim that not even Mark Zuckerberg, one month ago, is making.
Yeah, I mean most Foss projects have code copied from stack exchange since decades.
AI mostly just copies from stack exchange too, so its really just copying from stack exchange with extra steps.
That’s exactly it and why I can’t take this article very seriously.
Just because AI is writing some code doesn’t mean it gets credit as the developer. A human still puts their name beside it. They get all the credit and all the responsibility.
A piece of code I struggled with for days and some vibe-coded slop look identical in a PR.
And for that reason we can be certain that tons and tons of FOSS projects are using it. And the maintainers might not even know it.
The credit should go to the author on stack exchange.
Well there’s a huge difference between “slop” and actually fine code.
As long as the domain space isn’t super esoteric, and the framework is fairly mature, most LLMs will generate not half bad results, enough to get you 90% of the way there.
But then that last 10% of refining amd cleaning up the code, fixing formatting issues, tweaking names, etc is what seperates the slop for them “you can’t even tell an AI helped with this” code
I have projects that prolly a good 5% to 10% of the code is AI generated, but you’d never know cuz I still did a second pass over it to sanity check and make sure its good
100%
I took some code and scripts I wrote and passed them through AI. A lot of it was tightened up, and even better, it added comments and turned some things into functions so they were reusable.
I parsed everything it did to sanity check it. Really, use it like a junior developer. “Hey helper, write me a piece of code that does X.” You always double check the junior.
Quiet you, I can’t hear the echoes in this chamber anymore
I contributed a few open code to GitHub that I made via LLM ai. I had to test it and figure out the architecture
