this post was submitted on 07 Jun 2026
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AI is making me paranoid about contributions (ruuda.nl)
submitted 1 day ago by lemmydividebyzero@reddthat.com to c/technology@lemmy.world
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[–] WhyJiffie@sh.itjust.works 1 points 1 day ago (1 children)

The value of any given contribution is the same, regardless of whether the code was written by a seasoned developer, a neophyte as a first project, an LLM, a team of high school students learning the language, or space aliens - the code is the code, it helps or hurts exactly the same when merged with zero connection to who or what wrote it.

Caring about who or what wrote the code is applying prejudice. Prejudice works well in a lot of cases, but it's no guarantee.

the blog post is not about who actually wrote the code, but whether it's worth the effort to do a thorough review. if an actual person made it, then yes because they can learn from it and the world becomes a slightly better place. if it was a vibecoder just using an LLM, then explaining what needs to be done and why does not add much to.the world, but it possibly helps to make the LLM company richer

[–] MangoCats@feddit.it 1 points 9 hours ago

whether it’s worth the effort to do a thorough review.

If the vibe coder learns how to vibe better....

I've been using LLMs for a lot of things since last October, the models have improved pretty dramatically since then, but so have my skills in using them - so it's hard to tell (and probably unimportant) which factor is more important in the increased quality and efficiency of my code production and reviews over the last year.

Using LLMs to review code (regardless of who/what wrote it) is a more efficient way to improving code quality, security, maintainability, etc. than just reading it all yourself. Certainly don't go blindly trusting the LLM reviews, but if you haven't tried them for pull request review, you should...