I think this is a reasonable decision (although maybe increasingly insufficient).
It doesn't really matter what your stance on AI is, the problem is the increased review burden on OSS maintainers.
In the past, the code itself was a sort of proof of effort - you would need to invest some time and effort on your PRs, otherwise they would be easily dismissed at a glance. That is no longer the case, as LLMs can quickly generate PRs that might look superficially correct. Effort can still have been out into those PRs, but there is no way to tell without spending time reviewing in more detail.
Policies like this help decrease that review burden, by outright rejecting what can be identified as LLM-generated code at a glance. That is probably a fair bit today, but it might get harder over time, though, so I suspect eventually we will see a shift towards more trust-based models, where you cannot submit PRs if you haven't been approved in advance somehow.
Even if we assume LLMs would consistently generate good enough quality code, code submitted by someone untrusted would still need detailed review for many reasons - so even in that case it would like be faster for the maintainers to just use the tools themselves, rather than reviewing someone else's use of the same tools.
For well-intended open source contributions using GenAI, my current rules of thumb are:
* Prefer an issue over a PR (after iterating on the issue, either you or the maintainer can use it as a prompt)
* Only open a PR if the review effort is less than the implementation effort.
Whether the latter is feasible depends on the project, but in one of the projects I'm involved in it's fairly obvious: it's a package manager where the work is typically verifying dependencies and constraints; links to upstream commits etc are a great shortcut for reviewers.
Unfortunately, LLMs generate useless word salad and nonsense even when working on issues text, you absolutely have to reword the writing from scratch otherwise it's just an annoyance and a complete waste of time. Even a good prompt doesn't help this all that much since it's just how the tool works under the hood: it doesn't have a goal of saying anything specific in the clearest possible way and inwardly rewording it until it does, it just writes stuff out that will hopefully end up seeming at least half-coherent. And their code is orders of magnitude worse than even their terrible English prose.
I don't think it really is - drive-by changes have been a net burden on maintainers long before LLMs started writing code. Someone who wants to put in the work to become a repeat contributor to a project is a different story.
How to differentiate between a drive-by contribution and a first contribution from a potentially long-time contrubutor.
And I would say especially for operating systems if it gets any adoption irregular contributions are pretty legit. E.g. when someone wants just one specific piece of hardware supported that no one else has or needs without being employed by the vendor.
This sounds complicated in theory, but it's easier in practice.
Potential long time contributor is somebody who was already asking annoying questions in the irc channel for a few months and helped with other stuff before shooting off th e PR. If the PR is the first time you hear from a person -- that's pretty drive-by ish.
Sounds like a better way to make sure you have to be part of a clique to get your changed reviewed. I’ve been a long-time bug fixer in a few projects over the years without participating in IRC. I like the software and want it you work, but have no interest in conversing about it at that level, especially when I was conversing about software constantly at work.
I always provided well-documented PRs with a narrow scope and an obvious purpose.
Why would I ask annoying questions when I can identify, reproduce, pinpoint the bug, locate it in code, and fix it? Doing it alone should make it clear I don't need to ask to understand it. And why would I be interested in small talk? Doubt many people are when they patch up their work tools. It's a dispassionate kind of kindness.
Not to mention LLMs can be annoying, too. Demand this, and you'll only be inviting bots to pester devs on IRC.
Project maintainers will always have the right to decide how to maintain their projects, and "owe" nothing to no one.
That being said, to outright ban a technology in 2026 on pure "vibes" is not something I'd say is reasonable. Others have already commented that it's likely unenforceable, but I'd also say it's unreasonable for the sake of utility. It leaves stuff on the table in a time where they really shouldn't. Things like documentation tracking, regression tracking, security, feature parity, etc. can all be enhanced with carefully orchestrated assistance. To simply ban this is ... a choice, I guess. But it's not reasonable, in my book. It's like saying we won't use ci/cd, because it's automated stuff, we're purely manual here.
I think a lot of projects will find ways to adapt. Create good guidelines, help the community to use the best tools for the best tasks, and use automation wherever it makes sense.
At the end of the day slop is slop. You can always refuse to even look at something if you don't like the presentation. Or if the code is a mess. Or if it doesn't follow conventions. Or if a PR is +203323 lines, and so on. But attaching "LLMs aka AI" to the reasoning only invites drama, if anything it makes the effort of distinguishing good content from good looking content even harder, and so on. In the long run it won't be viable. If there's a good way to optimise a piece of code, it won't matter where that optimisation came from, as long as it can be proved it's good.
tl;dr; focus on better verification instead of better identification; prove that a change is good instead of focusing where it came from; test, learn and adapt. Dogma was never good.
At the moment verification at scale is an unsolved problem, though. As mentioned, I think this will act as a rough filter for now, but probably not work forever - and denying contributions from non-vetted contributors will likely end up being the new default.
Once outside contributions are rejected by default, the maintainers can of course choose whether or not to use LLMs or not.
I do think that it is a misconception that OSS software needs to "viable". OSS maintainers can have many motivations to build something, and just shipping a product might not be at the top of that list at all, and they certainly don't have that obligation. Personally, I use OSS as a way to build and design software with a level of gold plating that is not possible in most work settings, for the feeling that _I_ built something, and the pure joy of coding - using LLMs to write code would work directly against those goals. Whether LLMs are essential in more competitive environments is also something that there are mixed opinions on, but in those cases being dogmatic is certainly more risky.
Your analogy with CI/CD is flawed because while not all were convinced of the merits of CI/CD, it's also not technology built on vast energy use and copyright violation at a scale unseen in all of history, which has upended the hardware market, shaken the idea of job security for developers to its very foundation and done it while offering no really obvious benefits to groups wishing to produce really solid software. Maybe that comes eventually, but not at this level of maturity.
But you're right it's probably unenforceable. They will probably end up accepting PRs which were written with LLM assistance, but if they do it will be because it's well-written code that the contributor can explain in a way that doesn't sound to the maintainers like an LLM is answering their questions. And maybe at that point the community as a whole would have less to worry about - if we're still assuming that we're not setting ourselves up for horrible licence violation problems in the future when it turns out an LLM spat out something verbatim from a GPLed project.
> Or if the code is a mess. Or if it doesn't follow conventions.
In my experience these things are very easily fixable by ai, I just ask it to follow the patterns found and conventions used in the code and it does that pretty well.
I've recently worked extensively with "prompt coding", and the model we're using is very good at following such instructions early on. However after deep reasoning around problems, it tends to focus more on solving the problem at hand than following established guidelines.
Still haven't found a good way to keep it on course other than "Hey, remember that thing that you're required to do? Still do that please."
> That being said, to outright ban a technology in 2026 on pure "vibes" is not something I'd say is reasonable.
To outright accept LLM contributions would be as much "pure vibes" as banning it.
The thing is, those that maintain open source projects have to make a decision where they want to spend their time. It's open source, they are not being paid for it, they should and will decide what it acceptable and what is not.
If you dislike it, you are free to fork it and make a "LLM's welcome" fork. If, as you imply, the LLM contributions are invaluable, your fork should eventually become the better choice.
Or you can complain to the void that open source maintainers don't want to deal with low effort vibe coded bullshit PRs.
> Even if we assume LLMs would consistently generate good enough quality code, code submitted by someone untrusted would still need detailed review for many reasons - so even in that case it would like be faster for the maintainers to just use the tools themselves, rather than reviewing someone else's use of the same tools.
Wouldn't an agent run by a maintainer require the same scrutiny? An agent is imo "someone else" and not a trusted maintainer.
Yes, I agree. It was just me playing with a hypothetical (but in my view not imminent) future where vibe-coding without review would somehow be good enough.
I feel like the pattern here is donate compute, not code. If agents are writing most of the software anyway, why deal with the overhead of reviewing other people's PRs? You're basically reviewing someone else's agent output when you could just run your own.
Maintainers could just accept feature requests, point their own agents at them using donated compute, and skip the whole review dance. You get code that actually matches the project's style and conventions, and nobody has to spend time cleaning up after a stranger's slightly-off take on how things should work.
Well, it's not quite that easy because someone still has to test the agent's output and make sure it works as expected, which it often doesn't. In many cases, they still need to read the code and make sure that it does what it's supposed to do. Or they may need to spend time coming up with an effective prompt, which can be harder than it sounds for complicated projects where models will fail if you ask them to implement a feature without giving them detailed guidance on how to do so.
Definitely, but that's kind of my point: the maintainers are still going to be way better at all of that than some random contributor who just wants a feature, vibe codes it, and barely tests it. The maintainers already know the codebase, they understand the implications of changes, and they can write much better plans for the agent to follow, which they can verify against. Having a great plan written down that you can verify against drastically lowers the risk of LLM-generated code
Or even more efficient: the model we already have. Donate money and let the maintainer decide whether to convert it into tokens or mash the keys themself.
The point isn't that agent output is magically better; it's that reviewing your own agent's output is way cheaper (intellectually) than reviewing a stranger's, because you've written the plan by yourself. And 'slop' is mostly what you get when you don't have a clear plan to verify against. Maintainers writing detailed specs for their own agents is a very different thing from someone vibe coding a feature request
You’re assuming that maintainers have a desire to use agentic coding in the first place.
Secondly, it would seem that such contributions would contribute little value, if the maintainers have to write up the detailed plans by themselves, basically have to do all the work to implement the change by themselves.
I think we will be getting into an interesting situation soon, where project maintainers use LLMs because they truly are useful in many cases, but will ban contributors for doing so, because they can't review how well did the user guide the LLM.
* modelling a solution that is consistent with the existing modelling/architecture of the software and moves modelling and architecture in the right direction
* verifying that the the implementation of the solution is not introducing accidental complexity
These are the things LLMs can't do well yet. That's where contributions will be most appreciated. Producing code won't be it, maintainers have their own LLM subscriptions.
Some sort of LLM audit trail is needed (containing prompts used, model identifier and marking all code written by LLM). It could be even signed by llm providers (but that wouldn't work with local models). Append only standard format that is required to be included in PR. It wouldn't be perfect (e.g. deleting the log completely), but it might help with code reviews. It would probably useful in general to help see what was written by llms.
The GPL talks about "the preferred form for modification of the software", and I'm starting to think that anything which involves any kind of LLM agent should be including all the text that the user gave to it as well. Prompts, etc.
Of course, even then it's not reproducible and requires proprietary software!
If an author of a PR just generated code with an LLM, the GitHub PR becomes an incredibly inefficient interface between a repository owner and the LLM. A much better use of the owner time would be to interact with LLM directly instead of responding to LLM generated PR, waiting for updates, responding again, etc.
Maybe a future direction will be the submission of detailed research, specifications and change plans for feature requests. Something that can be assessed by a human and turned into working code by both slides.
I wonder if that is an opportunity to build an Open-Source platform focused on this, replacing GitHub as the collaboration platform of a time where code was valuable.
The "interesting situation" is that maintainers are unable to cheaply distinguish slop from good contributions so they will simply stop accepting outside contributions.
This will cut off one of the genuine entry points to the industry where all you really needed was raw talent.
Yep, that’s why my forks of all their libraries with bugs fixed such as https://github.com/pmarreck/zigimg/commit/52c4b9a557d38fe1e1... will never ever go back to upstream, just because an LLM did it. Lame, but oh well- their loss. Also, this is dumb because anyone who wants fixes like this will have to find a fork like mine with them, which is an increased maintenance burden.
Hugely unpopular opinion on HN, but I'd rather use code that is flawed while written by a human, versus code that has been generated by a LLM, even if it fixes bugs.
I'd gladly take a bug report, sure, but then I'd fix the issues myself. I'd never allow LLM code to be merged.
If you rely on llms, you're simply not going to make it. The person who showed their work on the math test is 9/10 times is doing better in life than the person that only knew how to use a calculator. Now how do we think things are going to turn out for the person that doesn't even think they need to learn how to use a calculator.
Just like when people started losing their ability to navigate without a GPS/Maps app, you will lose your ability to write solid code, solve problems, hell maybe even read well.
I want my brain to be strong in old age, and I actually love to write code unlike 99% in software apparently (like why did you people even start doing this career.. makes no sense to me).
I'm going to keep writing the code myself! Stop paying Billionaires for their thinking machines, its not going to work out well for you.
> any content submitted that is clearly labelled as LLM-generated (including issues, merge requests, and merge request descriptions) will be immediately closed
Note the word "clearly". Weirdly, as a native English speaker this term makes the policy less strict. What about submarine LLM submissions?
I have no beef with Redox OS. I wish them well. This feels like the newest form of OSS virtue signaling.
That would constitute an attempt to circumvent their policy, with the consequence of being banned from the project. In other words, it makes not clearly labeling any LLM use a bannable offense.
Don't ask don't tell looks like a reasonable policy. If no one can tell that your code was written by an LLM and you claim authorship, then whether you have actually written it is a matter of your conscience.
As a native English speaker I read this as two parts. If it's obvious, the response is immediate and not up for debate. If it's not obvious then it falls in the second part - "any attempt to bypass this policy will result in a ban from the project".
A submarine submission, if discovered, will result in a ban.
Using the phrase "virtual signaling" long ago became a meaningless term other than to indicate one's views in a culture war. 10 years ago David Shariatmadari wrote "The very act of accusing someone of virtue signalling is an act of virtue signalling in itself", https://www.theguardian.com/commentisfree/2016/jan/20/virtue... .
Somewhat off topic, but I can’t believe someone got paid to write that article, what a load of crap. It’s like saying that fallacies don’t exist because sometimes people incorrectly claim the other side is arguing fallaciously.
If you go by the literal definition in the article, it’s very clear what OP meant when he said the AI policy is virtue-signaling, and it has absolutely nothing to do with the culture war.
The LLM ban is unenforceable, they must know this. Is it to scare off the most obvious stuff and have a way to kick people off easily in case of incomplete evidence?
It is enforceable, I think you mean to say that it cannot be prevented since people can attempt to hide their usage? Most rules and laws are like that, you proscribe some behavior but that doesn't prevent people from doing it. Therefore you typically need to also define punishments:
> This policy is not open to discussion, any content submitted that is clearly labelled as LLM-generated (including issues, merge requests, and merge request descriptions) will be immediately closed, and any attempt to bypass this policy will result in a ban from the project.
What happens when the PR is clear, reasonable, short, checked by a human, and clearly fixes, implements, or otherwise improves the code base and has no alternative implementation that is reasonably different from the initially presented version?
How would you tell that it's LLM-generated in that case?
If the submitter is prepared to explain the code and vouch for its quality then that might reasonably fall under "don't ask, don't tell".
However, if LLM output is either (a) uncopyrightable or (b) considered a derivative work of the source that was used to train the model, then you have a legal problem. And the legal system does care about invisible "bit colour".
The problem is that even if the code is clear and easy to understand AND it fixes a problem, it still might not be suitable as a pull request. Perhaps it changes the code in a way that would complicate other work in progress or planned and wouldn't just be a simple merge. Perhaps it creates a vulnerability somewhere else or additional cognitive load to understand the change. Perhaps it adds a feature the project maintainer specifically doesn't want to add. Perhaps it just simply takes up too much of their time to look at.
There are plenty of good reasons why somebody might not want your PR, independent of how good or useful to you your change is.
If you're going to set a firm "no AI" policy, then my inclination would be to treat that kind of PR in the same way the US legal system does evidence obtained illegally: you say "sorry, no, we told you the rules and so you've wasted effort -- we will not take this even if it is good and perhaps the only sensible implementation". Perhaps somebody else will eventually re-implement it later without looking at the AI PR.
How funny would it be if the path to actually implement that thing is then cut off because of a PR that was submitted with the exact same patch. I'm honestly sitting here grinning at the absurdity demonstrated here. Some things can only be done a certain way. Especially when you're working with 3rd party libraries and APIs. The name of the function is the name of the function. There's no walking around it.
It follows the same reasoning as when someone purposefully copies code from a codebase into another where the license doesn't allow.
Yes it might be the only viable solution, and most likely no one will ever know you copied it, but if you get found out most maintainers will not merge your PR.
That's why I said "somebody else, without looking at it". Clean-room reimplementation, if you like. The functionality is not forever unimplementable, it is only not implementable by merging this AI-generated PR.
It's similar to how I can't implement a feature by copying-and-pasting the obvious code from some commercially licensed project. But somebody else could write basically the same thing independently without knowing about the proprietary-license code, and that would be fine.
You not realizing how ridiculous this is, is exactly why half of all devs are about to get left behind.
Like, this should be enshrined as the quintessential “they simply, obstinately, perilously, refused to get it” moment.
Shortly, no one is going to care about anyone’s bespoke manual keyboard entry of code if it takes 10 times as long to produce the same functionality with imperceptibly less error.
I think the bigger point about enforcement is not whether you're able to detect "content submitted that is clearly labelled as LLM-generated", but that banning presumes you can identify the origin. Ie.: any individual contributor must be known to have (at most) one identity.
Once identity is guaranteed, privileges basically come down to reputation — which in this case is a binary "you're okay until we detect content that is clearly labelled as LLM-generated".
[Added]
Note that identity (especially avoiding duplicate identity) is not easily solved.
I suspect this is for now just a rough filter to remove the lowest effort PRs. It likely will not be enough for long, though, so I suspect we will see default deny policies soon enough, and various different approaches to screening potential contributors.
Any sufficiently advanced LLM-slop will be indistinguishable from regular human-slop. But that’s what they are after.
This heuristic lets the project flag problematic slop with minimal investment avoiding the cost issues with reviewing low-quality low-effort high-volume contributions, which should be near ideal.
Much like banning pornography on an artistic photo site, the perfect application on the borderline of the rule is far less important than filtering power “I know it when I see it” provides to the standard case. Plus, smut peddlers aren’t likely to set an OpenClaw bot-agent swarm loose arguing the point with you for days then posting blogs and medium articles attacking you personally for “discrimination”.
A sign to point at when you get someone is posting "I asked AI to fix this and got this". You can stop reading and any arguments right there. Saving lot of time and effort.
Just require that the CLA/Certificate of Origin statement be printed out, signed, and mailed with an envelope and stamp, where besides attesting that they appropriately license their contributions ((A)GPL, BSD, MIT, or whatever) and have the authority to do so, that they also attest that they haven't used any LLMs for their contributions. This will strongly deter direct LLM usage. Indirect usage, where people whip up LLM-generated PoCs that they then rewrite, will still probably go on, and go on without detection, but that's less objectionable morally (and legally) than trying to directly commit LLM code.
As an aside, I've noticed a huge drop off in license literacy amongst developers, as well as respect for the license choices of other developers/projects. I can't tell if LLMs caused this, but there's a noticeable difference from the way things were 10 years ago.
> As an aside, I've noticed a huge drop off in license literacy amongst developers
What do you mean by this? I always assumed this was the case anyway; MIT is, if I'm not mistaken, one of the mostly used licenses. I typically had a "fuck it" attitude when it came to the license, and I assume quite a lot of other people shared that sentiment. The code is the fun bit.
> I always assumed this was the case anyway; MIT is, if I'm not mistaken, one of the mostly used licenses
No, it wasn't that way in the 2000s, e.g., on platforms like SourceForge, where OSS devs would go out of their way to learn the terms and conditions of the popular licenses and made sure to respect each other's license choices, and usually defaulted to GPL (or LGPL), unless there was a compelling reason not to: https://web.archive.org/web/20160326002305/https://redmonk.c...
Not necessarily a bad idea, but I think the bigger issue here and now is the increasing assymmetry in effort between code submitter and reviewer, and the unsustainable review burden on the maintainers if nothing is done.
Honestly, given that that GPL model would be far below SOTA in capabilities, what exactly would be its use-case? Why would anyone try to use an inferior LLM if they can get away with using a superior one?
While I am more on the AI-hater side, I don't consider this to be a good idea:
"any content submitted that is clearly labelled as LLM-generated (including issues, merge requests, and merge request descriptions) will be immediately closed"
For example:
- What if a non-native English speaker uses the help of an AI model in the formulation of some issue/task?
- What about having a plugin in your IDE that rather gives syntax and small code fragment suggestions ("autocomplete on steroids")? Does this policy mean that the programmers are also restricted on the IDE and plugins that they are allowed to have installed if they want to contribute?
> What if a non-native English speaker uses the help of an AI model in the formulation of some issue/task?
Unfortunately, when I have seen this in the context of the Rust project, the result has still been the typical verbose word salad that is typical of chat style LLMs. It is better to use a dedicated translation tool, and post the original along with the translation.
> What about having a plugin in your IDE that rather gives syntax and small code fragment suggestions ("autocomplete on steroids")?
Very good question, I myself consider this sort of AI usage benign (unlike agent style usage), and is the only style of AI I use myself (since I have RSI it helps having to type less). You could turn the feature off for just this project though.
> Does this policy mean that the programmers are also restricted on the IDE and plugins that they are allowed to have installed if they want to contribute?
I don't think that follows, but what features you have active in the current project would definitely be affected. From what I have seen all IDEs allow turning AI features on and off as needed.
> What if a non-native English speaker uses the help of an AI model in the formulation of some issue
I've seen this excuse before but in practice the output they copy/paste is extremely verbose and long winded (with the bullet point and heading soup etc.)
Surely non-native speakers can see that structure and tell the LLM to match their natural style instead? No one wants to read a massive wall of text.
I am wondering why people spam OSS with AI slop pull requests in the first place?
Are they really that delusional to think that their AI slop has any value to the project?
Do they think acting like a complete prick and increasing the burden for the maintainers will get them a job offer?
I guess interacting with a sycophantic LLM for hours truly rots the brain.
To spell it out: No, your AI generated code has zero value. Actually less than that because generating it helped destroy the environment.
If the problem could be solved by using an LLM and the maintainers wanted to, they could prompt it themselves and get much better results than you do because they actually know the code. And no AI will not help you "get into open source". You don't learn shit from spamming open source projects.
That is one reason I believe. Being told that you need open source presence to be employed.
I think some people also like the feeling of being helpful. And they do not understand reality of LLM outputs. See comments posting AI generated summaries or answers to question. With no verification or critical checking themselves.
> This policy is not open to discussion, any content submitted that is clearly labelled as LLM-generated (including issues, merge requests, and merge request descriptions) will be immediately closed, and any attempt to bypass this policy will result in a ban from the project.
It sounds serious and strict, but it applies to content that's 'clearly labelled as LLM-generated'. So what about content that isn't as clear? I don't know what to make of it.
My guess is that the serious tone is to avoid any possible legal issues that may arise from the inadvertent inclusion of AI-generated code. But the general motivation might be to avoid wasting the maintainers' time on reviewing confusing and sloppy submissions that are made using the lazy use of AI (as opposed finely guided and well reviewed AI code).
if (foo == true) { // checking foo is true (rocketship emoji)
20 lines of code;
} else {
the same 20 lines of code with one boolean changed in the middle;
}
Description:
(markdown header) Summary (nerd emoji):
This PR fixes a non-existent issue by adding an *if statement** that checks if a variable is true. This has the following benefits:
This PR does not just improve performance, it fundamentally reshapes how we approach performance considerations. This is not just design --- it's architecture. Simple, succinct, yet powerful.
I see a lot of oss forks in the future where people just fork to fix their issues with LLMs without going through maintainers. Or even doing full LLM rewrites of smaller stuff.
AI has the potential to level the playing field somewhat between open source and commercial software and SaaS that can afford armies of expensive paid developers.
Time consuming work can be done quickly at a fraction of the cost or even almost free with open weights LLMs.
They're certainly welcome to do whatever they're like, and for a microkernel based OS it might make sense--I think there's probably pretty "Meh" output from a lot of LLMs.
I think part of the battle is actually just getting people to identify which LLM made it to understand if someones contribution is good or not. A javascript project with contributions from Opus 4.6 will probably be pretty good, but if someone is using Mistral small via the chat app, it's probably just a waste of time.
Let someone from the Redox team go read [1], [2], and [3]. If they still insist on keeping their position then ... well. The industry is being redefined as we speak and everyone doing the push-back are pushing against themselves really.
“Our approach is harness-first engineering: instead of reading every line of agent-generated code, invest in automated checks that can tell us with high confidence, in seconds, whether the code is correct. “
that’s literally what The whole industry has been doing for decades, and spoiler: you still need to review code! it just gives you confidence that you didn’t miss anything.
Also, without understanding the code, it’s difficult to see its failure modes, and how it should be tested accordingly.
So you read the three-part series of blogs that are packed in details in 3 minutes after I shared the link and put yourself into a position of entitled opinion and calling my position a silly take? Sure thing.
> The industry is being redefined as we speak and everyone doing the push-back are pushing against themselves really.
No, they’re pushing back against a world full of even more mass surveillance, corporate oligarchy, mass unemployment, wanton spam, and global warming. It is absolutely in your personal best interest to hate AI.
While I appreciate the morality and ethics of this choice, the current trend means projects going in this direction are making themselves irrelevant (don't bother quipping at how relevant redox is today, thanks). E.g. top security researches are now using LLMs to find new RCEs and local privilege escalations; no reason why the models couldn't fix these, too - and it's only the security surface.
IOW I think this stance is ethically good, but technically irresponsible.
Even if we assume that LLMs become good enough for this to be true (some might feel that is the case already - I disagree, but that is beside the point), there is no reason why OSS maintainers should accept such outside contributions that they would need to carefully review, as it comes from an untrusted source, when they could just use the tools themselves directly. Low effort drive-by PRs is a burden with no upside.
Not sure how they can expect to make a viable full OS without massive use of LLMs, so this makes no sense.
What makes sense if that of course any LLM-generated code must be reviewed by a good programmer and must be correct and well written, and the AI usage must be precisely disclosed.
What they should ban is people posting AI-generated code without mentioning it or replying "I don't know, the AI did it like that" to questions.
The problem is the increasing review burden - with LLMs it is possible to create superficially valid looking (but potentially incorrect) code without much effort, which will still take a lot of effort to review. So outright rejecting code that can identified as LLM-generated at a glance, is a rough filter to remove the lowest effort PRs.
Over time this might not be enough, though, so I suspect we will see default deny policies popping up soon enough.
Because it takes a massive amount of developer work (perhaps more than anything else), and it's very unlikely they either have the ability to attract enough human developers to be able to do it without LLM assistance.
Not to mention that even finding good developers willing to develop without AI (a significant handicap, even more so for coding things like an OS that are well represented in LLM training) seems difficult nowadays, especially if they aren't paying them.
>Not sure how they can expect to make a viable full OS without massive use of LLMs, so this makes no sense.
Humans have been doing this for the better parts of 5 decades now. Don't assume others rely on LLMs as much as you do.
>Not to mention that even finding good developers willing to develop without AI (a significant handicap, even more so for coding things like an OS that are well represented in LLM training) seems difficult nowadays, especially if they aren't paying them.
I highly doubt that. In fact, I'd take a significant pay cut to move to a company that doesn't use LLMs, if I were forced to use them in my current job.
> Because it takes a massive amount of developer work
You know what else takes "a massive amount of developer work"?
"any LLM-generated code must be reviewed by a good programmer"
And this is the crux of the matter with using LLMs to generate code for everything but really simple greenfield projects: They don't really speed things up, because everything they produce HAS TO be verified by someone, and that someone HAS TO have the necessary skill to write such code themselves.
LLMs save time on the typing part of programming. Incidentially that part is the least time consuming.
The submitter is supposed to be the good programmer; if not, then maintainers may or may not review it themselves depending on the importance of the feature.
There are only 4 successful general purpose production OSes (GNU/Linux, Android/Linux, Windows, OS X/iOS) and only one of those made by the open source community (GNU/Linux).
And a new OS needs to be significantly better than those to overcome the switching costs.
> There are only 4 successful general purpose production OSes
Feel like you are using a very narrow definition of "success" here. Is BSD not successful? It is deployed on 10s of millions of routers/firewalls/etc in addition to being the ancestor of both modern MacOS and PlaystationOS...
Just because they have been made before LLMs doesn't mean it can be done again, since there was just one success (GNU/Linux) and that success makes it much harder for new OSes since they need to better then it
I think this is a reasonable decision (although maybe increasingly insufficient).
It doesn't really matter what your stance on AI is, the problem is the increased review burden on OSS maintainers.
In the past, the code itself was a sort of proof of effort - you would need to invest some time and effort on your PRs, otherwise they would be easily dismissed at a glance. That is no longer the case, as LLMs can quickly generate PRs that might look superficially correct. Effort can still have been out into those PRs, but there is no way to tell without spending time reviewing in more detail.
Policies like this help decrease that review burden, by outright rejecting what can be identified as LLM-generated code at a glance. That is probably a fair bit today, but it might get harder over time, though, so I suspect eventually we will see a shift towards more trust-based models, where you cannot submit PRs if you haven't been approved in advance somehow.
Even if we assume LLMs would consistently generate good enough quality code, code submitted by someone untrusted would still need detailed review for many reasons - so even in that case it would like be faster for the maintainers to just use the tools themselves, rather than reviewing someone else's use of the same tools.
For well-intended open source contributions using GenAI, my current rules of thumb are:
* Prefer an issue over a PR (after iterating on the issue, either you or the maintainer can use it as a prompt)
* Only open a PR if the review effort is less than the implementation effort.
Whether the latter is feasible depends on the project, but in one of the projects I'm involved in it's fairly obvious: it's a package manager where the work is typically verifying dependencies and constraints; links to upstream commits etc are a great shortcut for reviewers.
Unfortunately, LLMs generate useless word salad and nonsense even when working on issues text, you absolutely have to reword the writing from scratch otherwise it's just an annoyance and a complete waste of time. Even a good prompt doesn't help this all that much since it's just how the tool works under the hood: it doesn't have a goal of saying anything specific in the clearest possible way and inwardly rewording it until it does, it just writes stuff out that will hopefully end up seeming at least half-coherent. And their code is orders of magnitude worse than even their terrible English prose.
That's a pretty good framework!
Prompts from issue text makes a lot of sense.
Isn't the obvious solution to not accept drive by changes?
That's eliminating of an important part of open source culture.
I don't think it really is - drive-by changes have been a net burden on maintainers long before LLMs started writing code. Someone who wants to put in the work to become a repeat contributor to a project is a different story.
How to differentiate between a drive-by contribution and a first contribution from a potentially long-time contrubutor.
And I would say especially for operating systems if it gets any adoption irregular contributions are pretty legit. E.g. when someone wants just one specific piece of hardware supported that no one else has or needs without being employed by the vendor.
This sounds complicated in theory, but it's easier in practice.
Potential long time contributor is somebody who was already asking annoying questions in the irc channel for a few months and helped with other stuff before shooting off th e PR. If the PR is the first time you hear from a person -- that's pretty drive-by ish.
Sounds like a better way to make sure you have to be part of a clique to get your changed reviewed. I’ve been a long-time bug fixer in a few projects over the years without participating in IRC. I like the software and want it you work, but have no interest in conversing about it at that level, especially when I was conversing about software constantly at work.
I always provided well-documented PRs with a narrow scope and an obvious purpose.
Why would I ask annoying questions when I can identify, reproduce, pinpoint the bug, locate it in code, and fix it? Doing it alone should make it clear I don't need to ask to understand it. And why would I be interested in small talk? Doubt many people are when they patch up their work tools. It's a dispassionate kind of kindness.
Not to mention LLMs can be annoying, too. Demand this, and you'll only be inviting bots to pester devs on IRC.
I can understand drive-by features can be a net burden, but what is wrong with a drive-by bugfix?
how in the heck do you disambiguate a first time long term contributor and a first time drive by contributor?
Sure - and I suspect we will see that soon enough. But it has downsides too, and finding the right way to vet potential contributors is tricky.
Project maintainers will always have the right to decide how to maintain their projects, and "owe" nothing to no one.
That being said, to outright ban a technology in 2026 on pure "vibes" is not something I'd say is reasonable. Others have already commented that it's likely unenforceable, but I'd also say it's unreasonable for the sake of utility. It leaves stuff on the table in a time where they really shouldn't. Things like documentation tracking, regression tracking, security, feature parity, etc. can all be enhanced with carefully orchestrated assistance. To simply ban this is ... a choice, I guess. But it's not reasonable, in my book. It's like saying we won't use ci/cd, because it's automated stuff, we're purely manual here.
I think a lot of projects will find ways to adapt. Create good guidelines, help the community to use the best tools for the best tasks, and use automation wherever it makes sense.
At the end of the day slop is slop. You can always refuse to even look at something if you don't like the presentation. Or if the code is a mess. Or if it doesn't follow conventions. Or if a PR is +203323 lines, and so on. But attaching "LLMs aka AI" to the reasoning only invites drama, if anything it makes the effort of distinguishing good content from good looking content even harder, and so on. In the long run it won't be viable. If there's a good way to optimise a piece of code, it won't matter where that optimisation came from, as long as it can be proved it's good.
tl;dr; focus on better verification instead of better identification; prove that a change is good instead of focusing where it came from; test, learn and adapt. Dogma was never good.
At the moment verification at scale is an unsolved problem, though. As mentioned, I think this will act as a rough filter for now, but probably not work forever - and denying contributions from non-vetted contributors will likely end up being the new default.
Once outside contributions are rejected by default, the maintainers can of course choose whether or not to use LLMs or not.
I do think that it is a misconception that OSS software needs to "viable". OSS maintainers can have many motivations to build something, and just shipping a product might not be at the top of that list at all, and they certainly don't have that obligation. Personally, I use OSS as a way to build and design software with a level of gold plating that is not possible in most work settings, for the feeling that _I_ built something, and the pure joy of coding - using LLMs to write code would work directly against those goals. Whether LLMs are essential in more competitive environments is also something that there are mixed opinions on, but in those cases being dogmatic is certainly more risky.
Your analogy with CI/CD is flawed because while not all were convinced of the merits of CI/CD, it's also not technology built on vast energy use and copyright violation at a scale unseen in all of history, which has upended the hardware market, shaken the idea of job security for developers to its very foundation and done it while offering no really obvious benefits to groups wishing to produce really solid software. Maybe that comes eventually, but not at this level of maturity.
But you're right it's probably unenforceable. They will probably end up accepting PRs which were written with LLM assistance, but if they do it will be because it's well-written code that the contributor can explain in a way that doesn't sound to the maintainers like an LLM is answering their questions. And maybe at that point the community as a whole would have less to worry about - if we're still assuming that we're not setting ourselves up for horrible licence violation problems in the future when it turns out an LLM spat out something verbatim from a GPLed project.
> Or if the code is a mess. Or if it doesn't follow conventions.
In my experience these things are very easily fixable by ai, I just ask it to follow the patterns found and conventions used in the code and it does that pretty well.
I've recently worked extensively with "prompt coding", and the model we're using is very good at following such instructions early on. However after deep reasoning around problems, it tends to focus more on solving the problem at hand than following established guidelines.
Still haven't found a good way to keep it on course other than "Hey, remember that thing that you're required to do? Still do that please."
> That being said, to outright ban a technology in 2026 on pure "vibes" is not something I'd say is reasonable.
To outright accept LLM contributions would be as much "pure vibes" as banning it.
The thing is, those that maintain open source projects have to make a decision where they want to spend their time. It's open source, they are not being paid for it, they should and will decide what it acceptable and what is not.
If you dislike it, you are free to fork it and make a "LLM's welcome" fork. If, as you imply, the LLM contributions are invaluable, your fork should eventually become the better choice.
Or you can complain to the void that open source maintainers don't want to deal with low effort vibe coded bullshit PRs.
> Even if we assume LLMs would consistently generate good enough quality code, code submitted by someone untrusted would still need detailed review for many reasons - so even in that case it would like be faster for the maintainers to just use the tools themselves, rather than reviewing someone else's use of the same tools.
Wouldn't an agent run by a maintainer require the same scrutiny? An agent is imo "someone else" and not a trusted maintainer.
Yes, I agree. It was just me playing with a hypothetical (but in my view not imminent) future where vibe-coding without review would somehow be good enough.
I feel like the pattern here is donate compute, not code. If agents are writing most of the software anyway, why deal with the overhead of reviewing other people's PRs? You're basically reviewing someone else's agent output when you could just run your own.
Maintainers could just accept feature requests, point their own agents at them using donated compute, and skip the whole review dance. You get code that actually matches the project's style and conventions, and nobody has to spend time cleaning up after a stranger's slightly-off take on how things should work.
Well, it's not quite that easy because someone still has to test the agent's output and make sure it works as expected, which it often doesn't. In many cases, they still need to read the code and make sure that it does what it's supposed to do. Or they may need to spend time coming up with an effective prompt, which can be harder than it sounds for complicated projects where models will fail if you ask them to implement a feature without giving them detailed guidance on how to do so.
Definitely, but that's kind of my point: the maintainers are still going to be way better at all of that than some random contributor who just wants a feature, vibe codes it, and barely tests it. The maintainers already know the codebase, they understand the implications of changes, and they can write much better plans for the agent to follow, which they can verify against. Having a great plan written down that you can verify against drastically lowers the risk of LLM-generated code
Who reviews the correctness of the second agents' review?
Or even more efficient: the model we already have. Donate money and let the maintainer decide whether to convert it into tokens or mash the keys themself.
So your proposed solution to AI slop PRs is to "donate" compute, so the maintainers can waste their time by generating the AI slop themselves?
The point isn't that agent output is magically better; it's that reviewing your own agent's output is way cheaper (intellectually) than reviewing a stranger's, because you've written the plan by yourself. And 'slop' is mostly what you get when you don't have a clear plan to verify against. Maintainers writing detailed specs for their own agents is a very different thing from someone vibe coding a feature request
You’re assuming that maintainers have a desire to use agentic coding in the first place.
Secondly, it would seem that such contributions would contribute little value, if the maintainers have to write up the detailed plans by themselves, basically have to do all the work to implement the change by themselves.
Open-source maintainers have no investors to placate, no competition to outrun, why would they want to use agentic coding in the first place?
I think we will be getting into an interesting situation soon, where project maintainers use LLMs because they truly are useful in many cases, but will ban contributors for doing so, because they can't review how well did the user guide the LLM.
The bottlenecks today are:
* understanding the problem
* modelling a solution that is consistent with the existing modelling/architecture of the software and moves modelling and architecture in the right direction
* verifying that the the implementation of the solution is not introducing accidental complexity
These are the things LLMs can't do well yet. That's where contributions will be most appreciated. Producing code won't be it, maintainers have their own LLM subscriptions.
Some sort of LLM audit trail is needed (containing prompts used, model identifier and marking all code written by LLM). It could be even signed by llm providers (but that wouldn't work with local models). Append only standard format that is required to be included in PR. It wouldn't be perfect (e.g. deleting the log completely), but it might help with code reviews. It would probably useful in general to help see what was written by llms.
The GPL talks about "the preferred form for modification of the software", and I'm starting to think that anything which involves any kind of LLM agent should be including all the text that the user gave to it as well. Prompts, etc.
Of course, even then it's not reproducible and requires proprietary software!
If an author of a PR just generated code with an LLM, the GitHub PR becomes an incredibly inefficient interface between a repository owner and the LLM. A much better use of the owner time would be to interact with LLM directly instead of responding to LLM generated PR, waiting for updates, responding again, etc.
Maybe a future direction will be the submission of detailed research, specifications and change plans for feature requests. Something that can be assessed by a human and turned into working code by both slides.
I wonder if that is an opportunity to build an Open-Source platform focused on this, replacing GitHub as the collaboration platform of a time where code was valuable.
I think guiding the LLM to write code is easy for them to write code by themselves.
The "interesting situation" is that maintainers are unable to cheaply distinguish slop from good contributions so they will simply stop accepting outside contributions.
This will cut off one of the genuine entry points to the industry where all you really needed was raw talent.
Zig has a similar stance on no-LLM policy
https://codeberg.org/ziglang/zig#strict-no-llm-no-ai-policy
Yep, that’s why my forks of all their libraries with bugs fixed such as https://github.com/pmarreck/zigimg/commit/52c4b9a557d38fe1e1... will never ever go back to upstream, just because an LLM did it. Lame, but oh well- their loss. Also, this is dumb because anyone who wants fixes like this will have to find a fork like mine with them, which is an increased maintenance burden.
Hugely unpopular opinion on HN, but I'd rather use code that is flawed while written by a human, versus code that has been generated by a LLM, even if it fixes bugs.
I'd gladly take a bug report, sure, but then I'd fix the issues myself. I'd never allow LLM code to be merged.
If you rely on llms, you're simply not going to make it. The person who showed their work on the math test is 9/10 times is doing better in life than the person that only knew how to use a calculator. Now how do we think things are going to turn out for the person that doesn't even think they need to learn how to use a calculator.
Just like when people started losing their ability to navigate without a GPS/Maps app, you will lose your ability to write solid code, solve problems, hell maybe even read well.
I want my brain to be strong in old age, and I actually love to write code unlike 99% in software apparently (like why did you people even start doing this career.. makes no sense to me).
I'm going to keep writing the code myself! Stop paying Billionaires for their thinking machines, its not going to work out well for you.
I have no beef with Redox OS. I wish them well. This feels like the newest form of OSS virtue signaling.
> What about submarine LLM submissions?
That would constitute an attempt to circumvent their policy, with the consequence of being banned from the project. In other words, it makes not clearly labeling any LLM use a bannable offense.
Don't ask don't tell looks like a reasonable policy. If no one can tell that your code was written by an LLM and you claim authorship, then whether you have actually written it is a matter of your conscience.
I read that as benefit of the doubt, which is a reasonable stance.
As a native English speaker I read this as two parts. If it's obvious, the response is immediate and not up for debate. If it's not obvious then it falls in the second part - "any attempt to bypass this policy will result in a ban from the project".
A submarine submission, if discovered, will result in a ban.
Using the phrase "virtual signaling" long ago became a meaningless term other than to indicate one's views in a culture war. 10 years ago David Shariatmadari wrote "The very act of accusing someone of virtue signalling is an act of virtue signalling in itself", https://www.theguardian.com/commentisfree/2016/jan/20/virtue... .
People who talk about "virtue signalling" are usually engaging in vice signalling.
Somewhat off topic, but I can’t believe someone got paid to write that article, what a load of crap. It’s like saying that fallacies don’t exist because sometimes people incorrectly claim the other side is arguing fallaciously.
If you go by the literal definition in the article, it’s very clear what OP meant when he said the AI policy is virtue-signaling, and it has absolutely nothing to do with the culture war.
The LLM ban is unenforceable, they must know this. Is it to scare off the most obvious stuff and have a way to kick people off easily in case of incomplete evidence?
It is enforceable, I think you mean to say that it cannot be prevented since people can attempt to hide their usage? Most rules and laws are like that, you proscribe some behavior but that doesn't prevent people from doing it. Therefore you typically need to also define punishments:
> This policy is not open to discussion, any content submitted that is clearly labelled as LLM-generated (including issues, merge requests, and merge request descriptions) will be immediately closed, and any attempt to bypass this policy will result in a ban from the project.
What happens when the PR is clear, reasonable, short, checked by a human, and clearly fixes, implements, or otherwise improves the code base and has no alternative implementation that is reasonably different from the initially presented version?
How would you tell that it's LLM-generated in that case?
If the submitter is prepared to explain the code and vouch for its quality then that might reasonably fall under "don't ask, don't tell".
However, if LLM output is either (a) uncopyrightable or (b) considered a derivative work of the source that was used to train the model, then you have a legal problem. And the legal system does care about invisible "bit colour".
The problem is that even if the code is clear and easy to understand AND it fixes a problem, it still might not be suitable as a pull request. Perhaps it changes the code in a way that would complicate other work in progress or planned and wouldn't just be a simple merge. Perhaps it creates a vulnerability somewhere else or additional cognitive load to understand the change. Perhaps it adds a feature the project maintainer specifically doesn't want to add. Perhaps it just simply takes up too much of their time to look at.
There are plenty of good reasons why somebody might not want your PR, independent of how good or useful to you your change is.
If you're going to set a firm "no AI" policy, then my inclination would be to treat that kind of PR in the same way the US legal system does evidence obtained illegally: you say "sorry, no, we told you the rules and so you've wasted effort -- we will not take this even if it is good and perhaps the only sensible implementation". Perhaps somebody else will eventually re-implement it later without looking at the AI PR.
How funny would it be if the path to actually implement that thing is then cut off because of a PR that was submitted with the exact same patch. I'm honestly sitting here grinning at the absurdity demonstrated here. Some things can only be done a certain way. Especially when you're working with 3rd party libraries and APIs. The name of the function is the name of the function. There's no walking around it.
It follows the same reasoning as when someone purposefully copies code from a codebase into another where the license doesn't allow. Yes it might be the only viable solution, and most likely no one will ever know you copied it, but if you get found out most maintainers will not merge your PR.
That's why I said "somebody else, without looking at it". Clean-room reimplementation, if you like. The functionality is not forever unimplementable, it is only not implementable by merging this AI-generated PR.
It's similar to how I can't implement a feature by copying-and-pasting the obvious code from some commercially licensed project. But somebody else could write basically the same thing independently without knowing about the proprietary-license code, and that would be fine.
You not realizing how ridiculous this is, is exactly why half of all devs are about to get left behind.
Like, this should be enshrined as the quintessential “they simply, obstinately, perilously, refused to get it” moment.
Shortly, no one is going to care about anyone’s bespoke manual keyboard entry of code if it takes 10 times as long to produce the same functionality with imperceptibly less error.
This is where most reasonable people would say “OK, fine”
CLEARLY, a lot of developers are not reasonable
I think the bigger point about enforcement is not whether you're able to detect "content submitted that is clearly labelled as LLM-generated", but that banning presumes you can identify the origin. Ie.: any individual contributor must be known to have (at most) one identity.
Once identity is guaranteed, privileges basically come down to reputation — which in this case is a binary "you're okay until we detect content that is clearly labelled as LLM-generated".
[Added]
Note that identity (especially avoiding duplicate identity) is not easily solved.
I suspect this is for now just a rough filter to remove the lowest effort PRs. It likely will not be enough for long, though, so I suspect we will see default deny policies soon enough, and various different approaches to screening potential contributors.
Any sufficiently advanced LLM-slop will be indistinguishable from regular human-slop. But that’s what they are after.
This heuristic lets the project flag problematic slop with minimal investment avoiding the cost issues with reviewing low-quality low-effort high-volume contributions, which should be near ideal.
Much like banning pornography on an artistic photo site, the perfect application on the borderline of the rule is far less important than filtering power “I know it when I see it” provides to the standard case. Plus, smut peddlers aren’t likely to set an OpenClaw bot-agent swarm loose arguing the point with you for days then posting blogs and medium articles attacking you personally for “discrimination”.
Probably just an attempt to stop low effort LLM copy pasta.
A sign to point at when you get someone is posting "I asked AI to fix this and got this". You can stop reading and any arguments right there. Saving lot of time and effort.
> The LLM ban is unenforceable
Just require that the CLA/Certificate of Origin statement be printed out, signed, and mailed with an envelope and stamp, where besides attesting that they appropriately license their contributions ((A)GPL, BSD, MIT, or whatever) and have the authority to do so, that they also attest that they haven't used any LLMs for their contributions. This will strongly deter direct LLM usage. Indirect usage, where people whip up LLM-generated PoCs that they then rewrite, will still probably go on, and go on without detection, but that's less objectionable morally (and legally) than trying to directly commit LLM code.
As an aside, I've noticed a huge drop off in license literacy amongst developers, as well as respect for the license choices of other developers/projects. I can't tell if LLMs caused this, but there's a noticeable difference from the way things were 10 years ago.
> As an aside, I've noticed a huge drop off in license literacy amongst developers
What do you mean by this? I always assumed this was the case anyway; MIT is, if I'm not mistaken, one of the mostly used licenses. I typically had a "fuck it" attitude when it came to the license, and I assume quite a lot of other people shared that sentiment. The code is the fun bit.
> I always assumed this was the case anyway; MIT is, if I'm not mistaken, one of the mostly used licenses
No, it wasn't that way in the 2000s, e.g., on platforms like SourceForge, where OSS devs would go out of their way to learn the terms and conditions of the popular licenses and made sure to respect each other's license choices, and usually defaulted to GPL (or LGPL), unless there was a compelling reason not to: https://web.archive.org/web/20160326002305/https://redmonk.c...
Now the corporate-backed "MIT-EVERYTHING" mindvirus has ruined all of that: https://opensource.org/blog/top-open-source-licenses-in-2025
I am 100% certain that code that Redox OS relies on in upstream already has LLM code in it.
Yes, but that is there choice and burden to maintain.
Glad to see they are applying some rigor. I've started removing AI-heavy projects from my dependency tree.
We need LLMs that have a certificate of origin.
For instance a GPL LLM trained only on GPL code where the source data is all known, and the output is all GPL.
It could be done with a distributed effort.
Not necessarily a bad idea, but I think the bigger issue here and now is the increasing assymmetry in effort between code submitter and reviewer, and the unsustainable review burden on the maintainers if nothing is done.
I don't think the licensing issues are the main problem, but the spam.
Honestly, given that that GPL model would be far below SOTA in capabilities, what exactly would be its use-case? Why would anyone try to use an inferior LLM if they can get away with using a superior one?
Rather, LLMs that do NOT contain GPL code.
While I am more on the AI-hater side, I don't consider this to be a good idea:
"any content submitted that is clearly labelled as LLM-generated (including issues, merge requests, and merge request descriptions) will be immediately closed"
For example:
- What if a non-native English speaker uses the help of an AI model in the formulation of some issue/task?
- What about having a plugin in your IDE that rather gives syntax and small code fragment suggestions ("autocomplete on steroids")? Does this policy mean that the programmers are also restricted on the IDE and plugins that they are allowed to have installed if they want to contribute?
> What if a non-native English speaker uses the help of an AI model in the formulation of some issue/task?
Unfortunately, when I have seen this in the context of the Rust project, the result has still been the typical verbose word salad that is typical of chat style LLMs. It is better to use a dedicated translation tool, and post the original along with the translation.
> What about having a plugin in your IDE that rather gives syntax and small code fragment suggestions ("autocomplete on steroids")?
Very good question, I myself consider this sort of AI usage benign (unlike agent style usage), and is the only style of AI I use myself (since I have RSI it helps having to type less). You could turn the feature off for just this project though.
> Does this policy mean that the programmers are also restricted on the IDE and plugins that they are allowed to have installed if they want to contribute?
I don't think that follows, but what features you have active in the current project would definitely be affected. From what I have seen all IDEs allow turning AI features on and off as needed.
> What if a non-native English speaker uses the help of an AI model in the formulation of some issue
I've seen this excuse before but in practice the output they copy/paste is extremely verbose and long winded (with the bullet point and heading soup etc.)
Surely non-native speakers can see that structure and tell the LLM to match their natural style instead? No one wants to read a massive wall of text.
I am wondering why people spam OSS with AI slop pull requests in the first place?
Are they really that delusional to think that their AI slop has any value to the project?
Do they think acting like a complete prick and increasing the burden for the maintainers will get them a job offer?
I guess interacting with a sycophantic LLM for hours truly rots the brain.
To spell it out: No, your AI generated code has zero value. Actually less than that because generating it helped destroy the environment.
If the problem could be solved by using an LLM and the maintainers wanted to, they could prompt it themselves and get much better results than you do because they actually know the code. And no AI will not help you "get into open source". You don't learn shit from spamming open source projects.
For one, it makes your Github profile look more attractive to employers (superficially, at least).
Sometimes, I'd guess, it's also because your Github profile has some kind of an advertisement.
That is one reason I believe. Being told that you need open source presence to be employed.
I think some people also like the feeling of being helpful. And they do not understand reality of LLM outputs. See comments posting AI generated summaries or answers to question. With no verification or critical checking themselves.
You can then list on your profile that you’re a contributor to 1000 FOSS projects.
Before this it was junk like spacing changes
They will sooner or later change that policy or get very slow in keeping up.
Hm, wondering how to enforce this rule. Rules without any means to enforce them can put the honest people into a disadvantage.
> This policy is not open to discussion, any content submitted that is clearly labelled as LLM-generated (including issues, merge requests, and merge request descriptions) will be immediately closed, and any attempt to bypass this policy will result in a ban from the project.
It sounds serious and strict, but it applies to content that's 'clearly labelled as LLM-generated'. So what about content that isn't as clear? I don't know what to make of it.
My guess is that the serious tone is to avoid any possible legal issues that may arise from the inadvertent inclusion of AI-generated code. But the general motivation might be to avoid wasting the maintainers' time on reviewing confusing and sloppy submissions that are made using the lazy use of AI (as opposed finely guided and well reviewed AI code).
What would constitute "clearly llm generated" though
(markdown header) Summary (nerd emoji):
This PR fixes a non-existent issue by adding an *if statement** that checks if a variable is true. This has the following benefits:
(markdown header) Conclusion:This PR does not just improve performance, it fundamentally reshapes how we approach performance considerations. This is not just design --- it's architecture. Simple, succinct, yet powerful.
Peak comedy
I see a lot of oss forks in the future where people just fork to fix their issues with LLMs without going through maintainers. Or even doing full LLM rewrites of smaller stuff.
AI has the potential to level the playing field somewhat between open source and commercial software and SaaS that can afford armies of expensive paid developers.
Time consuming work can be done quickly at a fraction of the cost or even almost free with open weights LLMs.
Spiritually Amish
They're certainly welcome to do whatever they're like, and for a microkernel based OS it might make sense--I think there's probably pretty "Meh" output from a lot of LLMs.
I think part of the battle is actually just getting people to identify which LLM made it to understand if someones contribution is good or not. A javascript project with contributions from Opus 4.6 will probably be pretty good, but if someone is using Mistral small via the chat app, it's probably just a waste of time.
Let someone from the Redox team go read [1], [2], and [3]. If they still insist on keeping their position then ... well. The industry is being redefined as we speak and everyone doing the push-back are pushing against themselves really.
[1] https://www.datadoghq.com/blog/ai/harness-first-agents/
[2] https://www.datadoghq.com/blog/ai/fully-autonomous-optimizat...
[3] https://www.datadoghq.com/blog/engineering/self-optimizing-s...
P.S. I know this will be downvoted to death but I'll leave it here anyway for folks who want to keep their eyes wide open.
That’s such a silly take.
“Our approach is harness-first engineering: instead of reading every line of agent-generated code, invest in automated checks that can tell us with high confidence, in seconds, whether the code is correct. “
that’s literally what The whole industry has been doing for decades, and spoiler: you still need to review code! it just gives you confidence that you didn’t miss anything.
Also, without understanding the code, it’s difficult to see its failure modes, and how it should be tested accordingly.
So you read the three-part series of blogs that are packed in details in 3 minutes after I shared the link and put yourself into a position of entitled opinion and calling my position a silly take? Sure thing.
They probably used an AI to summarise those blog posts for them and it told them with high confidence, in seconds, whether they were correct.
> The industry is being redefined as we speak and everyone doing the push-back are pushing against themselves really.
No, they’re pushing back against a world full of even more mass surveillance, corporate oligarchy, mass unemployment, wanton spam, and global warming. It is absolutely in your personal best interest to hate AI.
While I appreciate the morality and ethics of this choice, the current trend means projects going in this direction are making themselves irrelevant (don't bother quipping at how relevant redox is today, thanks). E.g. top security researches are now using LLMs to find new RCEs and local privilege escalations; no reason why the models couldn't fix these, too - and it's only the security surface.
IOW I think this stance is ethically good, but technically irresponsible.
Even if we assume that LLMs become good enough for this to be true (some might feel that is the case already - I disagree, but that is beside the point), there is no reason why OSS maintainers should accept such outside contributions that they would need to carefully review, as it comes from an untrusted source, when they could just use the tools themselves directly. Low effort drive-by PRs is a burden with no upside.
People can choose not to use AI. This is because they think it is inevitable that they will eventually use LLMs.
Not sure how they can expect to make a viable full OS without massive use of LLMs, so this makes no sense.
What makes sense if that of course any LLM-generated code must be reviewed by a good programmer and must be correct and well written, and the AI usage must be precisely disclosed.
What they should ban is people posting AI-generated code without mentioning it or replying "I don't know, the AI did it like that" to questions.
The problem is the increasing review burden - with LLMs it is possible to create superficially valid looking (but potentially incorrect) code without much effort, which will still take a lot of effort to review. So outright rejecting code that can identified as LLM-generated at a glance, is a rough filter to remove the lowest effort PRs.
Over time this might not be enough, though, so I suspect we will see default deny policies popping up soon enough.
>Not sure how they can expect to make a viable full OS without massive use of LLMs, so this makes no sense.
Why not?
Because it takes a massive amount of developer work (perhaps more than anything else), and it's very unlikely they either have the ability to attract enough human developers to be able to do it without LLM assistance.
Not to mention that even finding good developers willing to develop without AI (a significant handicap, even more so for coding things like an OS that are well represented in LLM training) seems difficult nowadays, especially if they aren't paying them.
>Not sure how they can expect to make a viable full OS without massive use of LLMs, so this makes no sense.
Humans have been doing this for the better parts of 5 decades now. Don't assume others rely on LLMs as much as you do.
>Not to mention that even finding good developers willing to develop without AI (a significant handicap, even more so for coding things like an OS that are well represented in LLM training) seems difficult nowadays, especially if they aren't paying them.
I highly doubt that. In fact, I'd take a significant pay cut to move to a company that doesn't use LLMs, if I were forced to use them in my current job.
The LLM has brainwashed so many devs that they now think they are nothing without it.
That's an optimistic view. Maybe they really are 10x slower on any task without a LLM.
> Because it takes a massive amount of developer work
You know what else takes "a massive amount of developer work"?
"any LLM-generated code must be reviewed by a good programmer"
And this is the crux of the matter with using LLMs to generate code for everything but really simple greenfield projects: They don't really speed things up, because everything they produce HAS TO be verified by someone, and that someone HAS TO have the necessary skill to write such code themselves.
LLMs save time on the typing part of programming. Incidentially that part is the least time consuming.
Well, assuming you care about verification, of course. If it's got that green checkmark emoji, it ships!
The submitter is supposed to be the good programmer; if not, then maintainers may or may not review it themselves depending on the importance of the feature.
> Not sure how they can expect to make a viable full OS without massive use of LLMs, so this makes no sense.
Every single production OS, including the one you use right now, was made before LLMs even existed.
> What makes sense if that of course any LLM-generated code must be reviewed by a good programmer
The time of good programmers, especially ones working for free in their spare time on OSS projects, is a limited resource.
The ability to generate slop using LLMs, is effectively unlimited.
This discrepancy can only be resolved in one way: https://itsfoss.com/news/curl-ai-slop/
There are only 4 successful general purpose production OSes (GNU/Linux, Android/Linux, Windows, OS X/iOS) and only one of those made by the open source community (GNU/Linux).
And a new OS needs to be significantly better than those to overcome the switching costs.
> There are only 4 successful general purpose production OSes
Feel like you are using a very narrow definition of "success" here. Is BSD not successful? It is deployed on 10s of millions of routers/firewalls/etc in addition to being the ancestor of both modern MacOS and PlaystationOS...
None of this counters the argument I made above :-)
Just because they have been made before LLMs doesn't mean it can be done again, since there was just one success (GNU/Linux) and that success makes it much harder for new OSes since they need to better then it
Well, by this logic there have been 0 successful OSes made with LLMs so far...
what a retarded view. All OSes you use today were developed without AI
they already have...