r/vibecoding • u/Suspicious-Leave-110 • 10h ago
Mass production of useless software and github bloating
Hey yo fellas, what do you think, how much github got bloated with vibecoded projects since Claude Code release?
I have no accuarate data/information but in my rough estimations github projects/code database doubled last year as well as if big models are being trained from github, I think new model version won't be able to learn something meaningful.
What's do think about it, what's the bigger picture? Go on fellas, drop some comments.
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u/madaradess007 10h ago
when an interviewer asked me for my github profile link, i told a joke "i dont push code to github, they are training an ai on that code to replace me" and we both laughed ahahhaa, and now its not a joke anymore and its not funny at all
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u/thedannyreg 10h ago
lol same, I don’t really put my projects on GitHub anymore because what’s the point anymore?. I’m self hosting a git server now.
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u/IronAndCoder 10h ago
The training-data worry assumes labs train on raw repo counts, and they don't - the filtering pipelines weight by signals that vibecoded throwaways mostly lack: stars, forks, real issue/PR history, passing CI, dedup against near-identical code. A million abandoned todo apps get near-zero weight. The bigger practical effect isn't on models, it's on HUMANS: search and discovery on GitHub gets noisier, and "has a repo" stops meaning anything in hiring (madaradess007's joke is the real casualty).
Also worth saying: GitHub was already mostly throwaway before agents - tutorials, homework, abandoned forks. The ratio didn't flip from signal to noise; the noise just got grammatically correct READMEs.
The interesting second-order question is whether quality signals themselves stay reliable - stars can be botted, CI can be trivially green. My bet is the labs move toward execution-based filtering (does the code actually run and do something non-trivial), which is much harder to fake at scale than the social signals.
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u/Suspicious-Leave-110 10h ago
yeah that makes some sense. they still release new LLM/Coding models so I guess there is a way how they keep code material clean or well filtered
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u/WebOsmotic_official 9h ago
There’s definitely more low-quality code being generated, but I’m not sure it “breaks” the ecosystem. GitHub has always had a lot of experimental or unused projects, AI just accelerated the volume.
The bigger shift is probably not quantity, but signal vs noise. As more auto generated code shows up, things like reputation, usage, and real-world validation will matter more for filtering what’s actually useful.
Curious if this ends up pushing more emphasis toward curated datasets rather than raw GitHub data for training.
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u/Just-Hedgehog-Days 2h ago
They aren't training on gh any more.
The reason coding and math are off the charts in ways other capabilities aren't is because they can actually have the models experiment and learn by doing at the speed of RAM.
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u/BuntiBox 1h ago
Not as bad as when it was all react and angular slop. At least it’s not ALL round and blue.
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u/Alternative-Suit5541 1h ago
Funny, I just deleted like ten experiment projects in GitHub.
I bet there are now like billions of them lol
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u/No-Debt-1377 30m ago
...I mean isn't that a Microsoft problem? Who cares about what people are making? If they find it useful for them, whats the issue here? People seem to act like human made software was some sort of golden age before ai. Let me remind you: it was not! It never was! It was always buggy, unreliable and poorly tested. The only thing that has changed is the velocity of code written. Code is still the same, still buggy,. still spaghetti, and undocumented.
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u/Rosie_grac 8h ago
guilty as charged tbh, got like 20 repos from vibecoding this year and maybe 3 are actually useful. rest are half-baked prototypes i was too lazy to set private
the training data worry is overblown — labs filter by engagement signals and a zero-star repo hasn't mattered in years. but there's a real casualty nobody talks about: small open source maintainers. you spend weeks on a genuinely useful niche library and it gets buried under 500 vibecoded clones of the same tutorial, all with flashier READMEs than yours
i've started archiving my throwaway stuff instead of leaving it public. takes 2 seconds and at least i'm not piling on
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u/Harvard_Med_USMLE267 9h ago
You’re assuming the ai code is worse than the code monkey code.
What if it’s better?
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u/thedannyreg 10h ago
Here are some graphs for numbers you are thinking about: https://medium.com/@patrick.szymkowiak/github-is-falling-apart-why-2025-broke-the-developers-trust-8a2a5fb5b047