It's a fair policy. Getting those verbose, AI-authored walls of text is very annoying, especially when you're expected to thoroughly review it. It's like a denial-of-service attack on the human mind. I can only imagine how frustrating this can get in open projects that get a lot of contributions.
However, I don't think this will discourage AI-based coding at all. In fact, I see two potential outcomes of these policies:
- Negative: Submitters just add stylistic markers to make their accounts and output seem human-generated. This is like syntactic sugar: the core content and the size of contributions stay the same, but the style gets quirkier.
- Positive: Submitters actually provide to-the-point, no-bullshit commits and comments - "here's the code, here's why I made that change, here are the effects of that change". Even if AI-generated, these small contributions may become much easier to verify & validate. We may even see some standardization in terms of what qualifies as an appropriately sized contribution, what requires more thorough review (e.g., adding unverified dependencies), etc.
I personally wouldn't care if it was AI-generated or not, as long as the content fit the latter category.
> - Negative: Submitters just add stylistic markers to make their accounts and output seem human-generated. This is like syntactic sugar: the core content and the size of contributions stay the same, but the style gets quirkier.
From my experience reviewing, most contributors never read the policies, especially those making a "quick AI PR". I don't expect the new policy to change this much.
> Positive: Submitters actually provide to-the-point, no-bullshit commits and comments
> From my experience reviewing, most contributors never read the policies, especially those making a "quick AI PR". I don't expect the new policy to change this much.
True. At least with a policy about it, the project maintainers can unilaterally close such PRs without further internal or external discussion on any case-by-case basis.
> From my experience reviewing, most contributors never read the policies, especially those making a "quick AI PR". I don't expect the new policy to change this much.
The policy allows the reviewer to reject it on the "AI" grounds.
> It's like a denial-of-service attack on the human mind.
I think this may be an example of deliberate hostile design, attempting to force users to adopt LLM based solutions to then summarise the vast output. Pushing back against AI contributions as such in this context makes sense, especially in software with an existing proven track record of great value delivery like Godot.
Not quite accomplished, if it's creating text on the pull requests that looks sufficiently human-like, but you're still worried about the quality of the code and that the submitter doesn't understand it.
Contributors can have good intention but verbosity and number of automatically submitted issues kills it.
Few days ago, I have found a small json-based bug in one of popular software. So I submitted an issue that was written by Claude. But it was so verbose that explanation was longer than the bug itself :)
So I had to shorten the text manually.
Efficiency is the key. I haven’t written any issue before so LLM was much quicker than manual experiment. I have personally checked the result before submission.
You "personally checked" the result (generated by an LLM, a huge black box with extensive knowledge of all fields) to the best of your knowledge. There is a mismatch between what the machine knows (and has done as the result of it) and what you think you know.
Implementing a fix implies knowledge of the inner workings that brought you to it. A fix made by a LLM does not give you that.
The whole point of not-accepting AI authored code is because this line is not respected=>"Submitters actually provide to-the-point, no-bullshit commits and comments". You're putting way too much faith into the human minds ability to resist clout-chasing. AI isn't able to humanize code without human supervision.
Do those AI contributors really think they are helping out? Don't they get, that they are destroying such projects with their "work"? Why do they spend money for stuff nobody wants and gets rejected. I don't get it... Don't these people have any hobbies? Or are these free-roaming OpenClaw instances that have been forgotten by their creator and are now doing their own thing?
"If your feedback on PRs is just being absorbed by a machine and not going towards mentoring a potential future maintainer, it becomes much harder to justify spending your free time on PR review," the Foundation said.
Interesting initiative. What are the guiding reasons behind these lists?
I can't think of a functional reason for a no-AI policy: if it runs, it runs, regardless of who or what made it.
Also, even if you avoid AI-generated slop, you can't really avoid the human-generated or human+AI-generated slop that passes your filters.
Still, I can definitely think of good non-functional reasons: provenance, accountability, proof-of-work, encouraging people to write code themselves, empirically tracking how humans develop codebases, etc.
or, maybe, as a form of protest? many people are actively against AI for ethical/moral/personal reasons, so they want to avoid using software made with it
you can see it sort of like making a list of vegan restaurants. you might not see anything wrong with other restaurants (they might even have vegan dishes) but to some people it makes all the difference because they get to choose who they support
I think the main functional reason is that because a human hasn't written the code, its potentially more likely to have subtle hidden bugs that a human cant explain because they didn't write it, as well as large pull requests that have to be validated by a human when smaller human written ones would be better. But I think it's generally the non-functional reasons that projects are rejecting LLM-generated code. Some developers just find LLM generated code icky, and would prefer not to be associated with it
This makes sense, but I'm not sure it's directed at the actual issue.
There are probably some subtle bugs I can't explain in the code I wrote all by myself. I sure had a few "what was I possibly thinking when I wrote this" moments working on some old code - and that's only the bits I know about. And I sure had countless times people pointing out "hey, you got this stinky here" in a code review (which is the whole point of it). Attention lapses and brain farts sure happen. Slop can be more frequent with LLMs but it's certainly not a LLM-specific issue. They're very productive, there's a literal outbreak, and by the sheer volume shadow any The Daily WTF stories.
However, I can agree that LLM-generated code most likely has higher probability of slop. But then, a policy "a human contributor MUST fully know and understand all the contents of the submitted work, in fine detail, all the way down to every single line of contributed code and documentation" would probably address that in a more functional manner. And then the code can be from an LLM or monkeys with typewriters author had seen in his sleep. That stops to matter because author takes ownership and responsibility: "here's a recognized rational agent who swears by their work". Makes non-self-authored code require a lot more effort (unless it's a trivial change for obvious reason), but arguably even more robust than self-authored code.
That is, unless the PR authors tend lie about their knowledge - but that'll be a whole different story, where LLMs will be just a background detail.
(I'm not saying Godot should be done something different - their project, their rules, let's use that as an opportunity to watch how it goes. Just musing on the matter in general, if there's any rationally explainable merit in such policy.)
And on top of that - no matter if you develop open-source or proprietary software, who is to guarantee the AI didn't get trained with GPL (or even worse, leaked proprietary) source code? Who is going to pay my lawyer when someone files a copyright lawsuit and all I have as an excuse is that I "AI-laundered" my code?
And some projects like WINE or ReactOS probably have to worry about that even more given they need to guarantee clean-room reverse engineering...
Given the amount of web scraping LLM providers have been doing, I'd say it's likely that any code that is publicly accessible on the internet has been incorporated into it's training data, whatever its license
> Still, I can definitely think of good non-functional reasons
For many people that’s enough of a reason.
As for functional, you can see it all up and down this comment thread. People don’t check their work and leave these massive walls of text and codebases that someone else has to audit/cleanup. It’s exhausting. Too many people offload their work to AI and put zero effort into vetting the results, which punctually means they are just offloading the work downstream. So many maintainers are simply going “no I will not do your work for you,” which is a very functional decision.
To butcher a comment I read on HN that put it very succinctly months ago: everybody wants to let AI do their work for them, but nobody wants to be downstream of AI work. It’s a seriously problematic dynamic on many levels. And that dynamic will not change until the vast majority of people start reliably vetting the results, which I don’t think is going to happen because babysitting a black box and trying to force it to output something a specific way (or constantly copy editing middling work) is not something that most of us enjoy.
AI accidentally found one of the most expensive resources in the industry: the free time of people who maintain open source in the evenings after their day job
I'm getting the feeling that many people here are mostly reacting to the title instead of reading the actual policy: they state that an important part of the reason is that they use PR review to train new contributors and find possible future maintainers.
Irrespective of the quality of ai-contributions, that seems hard to argue with.
(unless you believe ai will make the whole concept of OS contributions / maintenance redundant. If that's your belief I don't think it makes much sense to submit PR's to Godot though, instead of just forking the engine and having your agents work on it)
The foundation points out something that has always been true, but AI has really brought to the forefront, that any contributor, including AI, could potentially not be relied on to maintain this patch in the future.
This is the core of the issue, not that someone uses AI, but that it’s just one of many smells a patch can have that indicates someone doesn’t understand what they’re submitting. You could be breaking variable naming conventions, changing APIs you shouldn’t, making amateur language mistakes, all indicate that yes, maybe the patch does work, but that there are other good reasons to reject it.
A way around this might be to mark a PR as rejected because of AI and then ask the author to point out some part of it they’re particularly proud of and explain in their own words, not a wall of AI text, what this does and why they like it. Just something where the author has to show that they have something an AI can’t, namely taste and an opinion.
Right. Reviewers still have the advantage of being able to spot AI text because it's often overtly different.
I just meant to say that, if you prompt ai "what would a human be proud of having written this code" you'll get an answer. They're not categorically incapable of fabricating an "opinion", they're just trained not to express one by default.
...the influx of contributions authored or submitted by AI is sapping the projects' maintainers of their willingness to confront the "already tedious" work of reviewing pull requests....
To me this seems a core issue: PR reviews for most people feel tedious and this has been the case way before AI already.
Don't get me wrong, slop is slop, no matter if AI or entirely human-fabricated. But just like AI-assisted coding can actually be helpful, why can't AI-assisted PR reviews make it less tedious?
It can, but using a technology just to work around problems caused (or at least exacerbated) by the very same technology is obviously not something we should be doing or encouraging.
I'm not sure I agree with the policy, but I'm glad we are seeing different project experimenting with different policies. So after a while we can probably see how things shake out in the end.
Definitely sympathetic to their policy, but AI tooling and quality are changing quite fast. In a year I'd expect a modification of this as AI agents get better in virtually every possible way.
If someone thinks they're building better open source with their AI, let them fork; their AI can maintain downstream. If it's really better, people will join the fork. Good luck.
In all likelihood anyone attempting this will realize the value that a maintainer provides. On the odd chance they discover a new working model and produce better software, all the better, everyone wins.
How they enforce it in every other project with the same policy, if the reviewer/maintainer suspects the pr is ai slope he closes it. That's it, it works fantastically well, I do the same even in my job
How do they enforce that contributions aren’t copied and pasted from AGPLv3 or proprietary codebases? The honor system and intuition and occasionally flat out asking people.
Do you think sociopaths willing to lie about how they came up with a contribution are really that common?
I predict this won't last long in any extreme version in any significant open source repo.
Banning AI-slop is one thing, but AI as a properly used co-programmer is becoming more and more capable and shutting out well-guided AI will enable competitors who don't to edge and then power ahead.
There are obviously problems to solve here, but blanket bans (while understandable in under-resourced maintenance environments) aren't anything more than a short-term buffer.
Because it's not about the tool or the quality of the past contributions, but the quality of the current contribution. It's not new either, it's "show me the code" - it doesn't matter who you are, what you say, what you claim to have achieved in the past, the only thing that matters right now is this particular merge request and code.
I don't think the problem is the (AI generated) code per se, but as the article mentions, it's the human interaction. A reviewer can spend hours on reviewing the code and leaving feedback to the author, but if the author just feeds it into an AI (or worse, it's automatically fed into it) and processes it within seconds, only to start with a blank slate for a next change, what's the point of putting in all that effort?
Humans can learn and adapt, AIs can... ingest more stuff into their context, I suppose, but it's been proven that things break down if they have too much stuff in said context, and said context is limited.
I think they arent even trying to build an AI detector. This is more of a social signal like "dont send us an automatically generated flood of changes"
There is legally. Make sure they sign the DCO (Developer Certificate of Origin). They will fail at the first paragraph
(a) The contribution was created in whole or in part by me and I
have the right to submit it under the open source license
indicated in the file; [...]
The Godot maintainers do review based on the quality of contributor's past contributions. Those becoming especially proficient can even become maintainers.
Allowing AI use by 'trusted contributors' has been suggested and discussed, but there were enough reasons against it and not enough established benefit.
Because of lot of AI PRs come from first time contributors who just discovered the tools. Maybe their PR is amazing, maybe it is trash. You never know until you review it.
It's far more time-consuming to judge the quality of someone's past contributions than to have the LLM redo the contribution with quality you can control far more.
In many ways this makes sense. I noticed other projects
struggle with this as well. AI slop spam kills time
available.
On the other hand ... it is a bit strange though, because
what if code contributions objectively improve something?
I dislike AI slop spam, but from a purely objective point
of view, I am not sure it should be forbidden based on
it intrinsically making a change, which COULD be an
improve. Now I am also aware of the AI slop spam worsening
things; ton of documentation is useless, look at what matz
produces with claude, this seems to be written purely by
an alien, aka AI. I don't understand anything that this
AI generates. But I think from an objective point of view,
I'd actually lean more towards not completely disallowing
AI slop contribution. The issue seems largely with:
a) the quality
b) the amount of text generated
Both these problems, in my opinion, could be solved. The
time required by a real human to look at it, though, will
always be a bottleneck, so perhaps the more honest answer
would be that humans don't have enough time for
contributions from skynet.
> what if code contributions objectively improve something?
If the contribution is complex enough, it is no longer an 'objective improvement' but rather a judgement call, and in the process becomes copyrightable. This is where the trouble lies, and why this kind of AI involvement is banned.
If it is not, for example by being a one-line fix that literally cannot be performed differently, it's a different story. Then it can be merged, viewed either as a menial change (exempt by the ban) or by transfer of ownership (the reviewer becomes the effective author) because it is not copyrightable.
While I agree with the general message, and wish it will eventually radiate to cooperations as well, it is obviously a decision driven by feelings, not logic.
The idea that you can't trust code that was generated by heavy users of AI, because _they_ don't understand it enough to fix it, is false, because they can use AI to fix it.
In general, I have hard time understanding how one might even block other contributors from using ai.
Community management (which is an important part of PR/issue management for open source projects) should definitely take in account the human aspect, i.e. feelings.
And it just keeps looping like that until the context window bursts. In practice the model is great at writing new code, but when you feed it its own six month old spaghetti code with a floating bug in the state machine it just starts hallucinating and silently breaking neighboring features
It's a fair policy. Getting those verbose, AI-authored walls of text is very annoying, especially when you're expected to thoroughly review it. It's like a denial-of-service attack on the human mind. I can only imagine how frustrating this can get in open projects that get a lot of contributions.
However, I don't think this will discourage AI-based coding at all. In fact, I see two potential outcomes of these policies:
- Negative: Submitters just add stylistic markers to make their accounts and output seem human-generated. This is like syntactic sugar: the core content and the size of contributions stay the same, but the style gets quirkier.
- Positive: Submitters actually provide to-the-point, no-bullshit commits and comments - "here's the code, here's why I made that change, here are the effects of that change". Even if AI-generated, these small contributions may become much easier to verify & validate. We may even see some standardization in terms of what qualifies as an appropriately sized contribution, what requires more thorough review (e.g., adding unverified dependencies), etc.
I personally wouldn't care if it was AI-generated or not, as long as the content fit the latter category.
> - Negative: Submitters just add stylistic markers to make their accounts and output seem human-generated. This is like syntactic sugar: the core content and the size of contributions stay the same, but the style gets quirkier.
From my experience reviewing, most contributors never read the policies, especially those making a "quick AI PR". I don't expect the new policy to change this much.
> Positive: Submitters actually provide to-the-point, no-bullshit commits and comments
That would be a dream.
> From my experience reviewing, most contributors never read the policies, especially those making a "quick AI PR". I don't expect the new policy to change this much.
True. At least with a policy about it, the project maintainers can unilaterally close such PRs without further internal or external discussion on any case-by-case basis.
> From my experience reviewing, most contributors never read the policies, especially those making a "quick AI PR". I don't expect the new policy to change this much.
The policy allows the reviewer to reject it on the "AI" grounds.
> It's like a denial-of-service attack on the human mind.
I think this may be an example of deliberate hostile design, attempting to force users to adopt LLM based solutions to then summarise the vast output. Pushing back against AI contributions as such in this context makes sense, especially in software with an existing proven track record of great value delivery like Godot.
> Submitters just add stylistic markers to make their accounts and output seem human-generated
https://xkcd.com/810/
Not quite accomplished, if it's creating text on the pull requests that looks sufficiently human-like, but you're still worried about the quality of the code and that the submitter doesn't understand it.
I completely agree.
Contributors can have good intention but verbosity and number of automatically submitted issues kills it.
Few days ago, I have found a small json-based bug in one of popular software. So I submitted an issue that was written by Claude. But it was so verbose that explanation was longer than the bug itself :) So I had to shorten the text manually.
Isn’t there a /skill for this?
If you understood the change, writing a short description of the problem and the fix yourself would be trivial.
Efficiency is the key. I haven’t written any issue before so LLM was much quicker than manual experiment. I have personally checked the result before submission.
So why the hate? :)
You "personally checked" the result (generated by an LLM, a huge black box with extensive knowledge of all fields) to the best of your knowledge. There is a mismatch between what the machine knows (and has done as the result of it) and what you think you know.
Implementing a fix implies knowledge of the inner workings that brought you to it. A fix made by a LLM does not give you that.
Efficiency rarely is the key.
The whole point of not-accepting AI authored code is because this line is not respected=>"Submitters actually provide to-the-point, no-bullshit commits and comments". You're putting way too much faith into the human minds ability to resist clout-chasing. AI isn't able to humanize code without human supervision.
Do those AI contributors really think they are helping out? Don't they get, that they are destroying such projects with their "work"? Why do they spend money for stuff nobody wants and gets rejected. I don't get it... Don't these people have any hobbies? Or are these free-roaming OpenClaw instances that have been forgotten by their creator and are now doing their own thing?
"If your feedback on PRs is just being absorbed by a machine and not going towards mentoring a potential future maintainer, it becomes much harder to justify spending your free time on PR review," the Foundation said.
That is to the point!
There are some curated lists of no-AI software. Would be nice to have an index / plot of how that changes in time.
https://codeberg.org/brib/slopfree-software-index
https://noai.starlightnet.work/list.html
Interesting initiative. What are the guiding reasons behind these lists?
I can't think of a functional reason for a no-AI policy: if it runs, it runs, regardless of who or what made it.
Also, even if you avoid AI-generated slop, you can't really avoid the human-generated or human+AI-generated slop that passes your filters.
Still, I can definitely think of good non-functional reasons: provenance, accountability, proof-of-work, encouraging people to write code themselves, empirically tracking how humans develop codebases, etc.
Because the goal is two-part
1. Accept quality contributions from someone who understands what they're doing
2. Cultivate a relationship with the contributor who might potentially become a core-team member. Maybe even the next maintainer
There is a "why" a the end of the list
https://codeberg.org/brib/slopfree-software-index#why-care-a...
> I can't think of a functional reason for a no-AI policy
Imagine morals.
That would be part of the non-functional reasons mentioned in the next paragraph.
or, maybe, as a form of protest? many people are actively against AI for ethical/moral/personal reasons, so they want to avoid using software made with it
you can see it sort of like making a list of vegan restaurants. you might not see anything wrong with other restaurants (they might even have vegan dishes) but to some people it makes all the difference because they get to choose who they support
I think the main functional reason is that because a human hasn't written the code, its potentially more likely to have subtle hidden bugs that a human cant explain because they didn't write it, as well as large pull requests that have to be validated by a human when smaller human written ones would be better. But I think it's generally the non-functional reasons that projects are rejecting LLM-generated code. Some developers just find LLM generated code icky, and would prefer not to be associated with it
This makes sense, but I'm not sure it's directed at the actual issue.
There are probably some subtle bugs I can't explain in the code I wrote all by myself. I sure had a few "what was I possibly thinking when I wrote this" moments working on some old code - and that's only the bits I know about. And I sure had countless times people pointing out "hey, you got this stinky here" in a code review (which is the whole point of it). Attention lapses and brain farts sure happen. Slop can be more frequent with LLMs but it's certainly not a LLM-specific issue. They're very productive, there's a literal outbreak, and by the sheer volume shadow any The Daily WTF stories.
However, I can agree that LLM-generated code most likely has higher probability of slop. But then, a policy "a human contributor MUST fully know and understand all the contents of the submitted work, in fine detail, all the way down to every single line of contributed code and documentation" would probably address that in a more functional manner. And then the code can be from an LLM or monkeys with typewriters author had seen in his sleep. That stops to matter because author takes ownership and responsibility: "here's a recognized rational agent who swears by their work". Makes non-self-authored code require a lot more effort (unless it's a trivial change for obvious reason), but arguably even more robust than self-authored code.
That is, unless the PR authors tend lie about their knowledge - but that'll be a whole different story, where LLMs will be just a background detail.
(I'm not saying Godot should be done something different - their project, their rules, let's use that as an opportunity to watch how it goes. Just musing on the matter in general, if there's any rationally explainable merit in such policy.)
And on top of that - no matter if you develop open-source or proprietary software, who is to guarantee the AI didn't get trained with GPL (or even worse, leaked proprietary) source code? Who is going to pay my lawyer when someone files a copyright lawsuit and all I have as an excuse is that I "AI-laundered" my code?
And some projects like WINE or ReactOS probably have to worry about that even more given they need to guarantee clean-room reverse engineering...
Given the amount of web scraping LLM providers have been doing, I'd say it's likely that any code that is publicly accessible on the internet has been incorporated into it's training data, whatever its license
Please define "if it runs, it runs"?
> Still, I can definitely think of good non-functional reasons
For many people that’s enough of a reason.
As for functional, you can see it all up and down this comment thread. People don’t check their work and leave these massive walls of text and codebases that someone else has to audit/cleanup. It’s exhausting. Too many people offload their work to AI and put zero effort into vetting the results, which punctually means they are just offloading the work downstream. So many maintainers are simply going “no I will not do your work for you,” which is a very functional decision.
To butcher a comment I read on HN that put it very succinctly months ago: everybody wants to let AI do their work for them, but nobody wants to be downstream of AI work. It’s a seriously problematic dynamic on many levels. And that dynamic will not change until the vast majority of people start reliably vetting the results, which I don’t think is going to happen because babysitting a black box and trying to force it to output something a specific way (or constantly copy editing middling work) is not something that most of us enjoy.
AI accidentally found one of the most expensive resources in the industry: the free time of people who maintain open source in the evenings after their day job
I'm getting the feeling that many people here are mostly reacting to the title instead of reading the actual policy: they state that an important part of the reason is that they use PR review to train new contributors and find possible future maintainers.
Irrespective of the quality of ai-contributions, that seems hard to argue with.
(unless you believe ai will make the whole concept of OS contributions / maintenance redundant. If that's your belief I don't think it makes much sense to submit PR's to Godot though, instead of just forking the engine and having your agents work on it)
The foundation points out something that has always been true, but AI has really brought to the forefront, that any contributor, including AI, could potentially not be relied on to maintain this patch in the future.
This is the core of the issue, not that someone uses AI, but that it’s just one of many smells a patch can have that indicates someone doesn’t understand what they’re submitting. You could be breaking variable naming conventions, changing APIs you shouldn’t, making amateur language mistakes, all indicate that yes, maybe the patch does work, but that there are other good reasons to reject it.
A way around this might be to mark a PR as rejected because of AI and then ask the author to point out some part of it they’re particularly proud of and explain in their own words, not a wall of AI text, what this does and why they like it. Just something where the author has to show that they have something an AI can’t, namely taste and an opinion.
AI is well-capable of fabricating text that looks like an opinion in 2026. This would not help differentiate AI from human authors.
You’re absolutely right - AI is not just capable, it’s on the leading edge. It’s not about vibes, it’s about results.
(It’s famously not well capable of sounding human)
Right. Reviewers still have the advantage of being able to spot AI text because it's often overtly different. I just meant to say that, if you prompt ai "what would a human be proud of having written this code" you'll get an answer. They're not categorically incapable of fabricating an "opinion", they're just trained not to express one by default.
Godot's new contribution policy: https://godotengine.org/article/contribution-policy-2026/
Don't get me wrong, slop is slop, no matter if AI or entirely human-fabricated. But just like AI-assisted coding can actually be helpful, why can't AI-assisted PR reviews make it less tedious?
It can, but using a technology just to work around problems caused (or at least exacerbated) by the very same technology is obviously not something we should be doing or encouraging.
I'm not sure I agree with the policy, but I'm glad we are seeing different project experimenting with different policies. So after a while we can probably see how things shake out in the end.
Definitely sympathetic to their policy, but AI tooling and quality are changing quite fast. In a year I'd expect a modification of this as AI agents get better in virtually every possible way.
Totally valid.
If someone thinks they're building better open source with their AI, let them fork; their AI can maintain downstream. If it's really better, people will join the fork. Good luck.
In all likelihood anyone attempting this will realize the value that a maintainer provides. On the odd chance they discover a new working model and produce better software, all the better, everyone wins.
And how will this be enforced ?
How they enforce it in every other project with the same policy, if the reviewer/maintainer suspects the pr is ai slope he closes it. That's it, it works fantastically well, I do the same even in my job
"suspects".... that sounds error prone. And I read it like "we don't want AI generated stuff unless we can't tell the difference".
How do they enforce that contributions aren’t copied and pasted from AGPLv3 or proprietary codebases? The honor system and intuition and occasionally flat out asking people.
Do you think sociopaths willing to lie about how they came up with a contribution are really that common?
Underlying announcement might be a better link:
https://godotengine.org/article/contribution-policy-2026/
I predict this won't last long in any extreme version in any significant open source repo.
Banning AI-slop is one thing, but AI as a properly used co-programmer is becoming more and more capable and shutting out well-guided AI will enable competitors who don't to edge and then power ahead.
There are obviously problems to solve here, but blanket bans (while understandable in under-resourced maintenance environments) aren't anything more than a short-term buffer.
Why base the decision on what tools are used by the author and not on the quality of their past contributions?
Because it's not about the tool or the quality of the past contributions, but the quality of the current contribution. It's not new either, it's "show me the code" - it doesn't matter who you are, what you say, what you claim to have achieved in the past, the only thing that matters right now is this particular merge request and code.
I don't think the problem is the (AI generated) code per se, but as the article mentions, it's the human interaction. A reviewer can spend hours on reviewing the code and leaving feedback to the author, but if the author just feeds it into an AI (or worse, it's automatically fed into it) and processes it within seconds, only to start with a blank slate for a next change, what's the point of putting in all that effort?
Humans can learn and adapt, AIs can... ingest more stuff into their context, I suppose, but it's been proven that things break down if they have too much stuff in said context, and said context is limited.
If your contributions are genuinely indistinguishable from AI code, then this shouldn’t affect you. There would be no way to enforce it
I think they arent even trying to build an AI detector. This is more of a social signal like "dont send us an automatically generated flood of changes"
There is legally. Make sure they sign the DCO (Developer Certificate of Origin). They will fail at the first paragraph
(a) The contribution was created in whole or in part by me and I have the right to submit it under the open source license indicated in the file; [...]
https://developercertificate.org/
I guess that means no IDEs doing refactoring or automating common code. Not linters altering code, etc... right ? Because that's the same thing.
How about if AI generates code in a file, then I copy/paste bits... like stack overflow ?
Because:
1. In the case of AI generated code, the tool is the author.
2. Its far easier to enforce.
3. The alternative gate keeps against new contributors.
The Godot maintainers do review based on the quality of contributor's past contributions. Those becoming especially proficient can even become maintainers.
Allowing AI use by 'trusted contributors' has been suggested and discussed, but there were enough reasons against it and not enough established benefit.
Because of lot of AI PRs come from first time contributors who just discovered the tools. Maybe their PR is amazing, maybe it is trash. You never know until you review it.
You are not the author with ai.
It's far more time-consuming to judge the quality of someone's past contributions than to have the LLM redo the contribution with quality you can control far more.
If AI is so good, there should be hundreds of new engines far exceeding Godot.
Yet all that is being produced is piggy-backing unchecked vibe-slop.
In many ways this makes sense. I noticed other projects struggle with this as well. AI slop spam kills time available.
On the other hand ... it is a bit strange though, because what if code contributions objectively improve something? I dislike AI slop spam, but from a purely objective point of view, I am not sure it should be forbidden based on it intrinsically making a change, which COULD be an improve. Now I am also aware of the AI slop spam worsening things; ton of documentation is useless, look at what matz produces with claude, this seems to be written purely by an alien, aka AI. I don't understand anything that this AI generates. But I think from an objective point of view, I'd actually lean more towards not completely disallowing AI slop contribution. The issue seems largely with:
a) the quality
b) the amount of text generated
Both these problems, in my opinion, could be solved. The time required by a real human to look at it, though, will always be a bottleneck, so perhaps the more honest answer would be that humans don't have enough time for contributions from skynet.
> what if code contributions objectively improve something?
If the contribution is complex enough, it is no longer an 'objective improvement' but rather a judgement call, and in the process becomes copyrightable. This is where the trouble lies, and why this kind of AI involvement is banned.
If it is not, for example by being a one-line fix that literally cannot be performed differently, it's a different story. Then it can be merged, viewed either as a menial change (exempt by the ban) or by transfer of ownership (the reviewer becomes the effective author) because it is not copyrightable.
Just put it behind a paywall for PR prioritization or consideration, more payment to jump the queue.
There, I solved FOSS sponsorship.
oh shoot, anyway
Godot is one of the worst run open source projects with a crawling pace since 2014.
[delayed]
It’s been wildly successful. Poorly run projects tend to fail.
Care to give arguments?
While I agree with the general message, and wish it will eventually radiate to cooperations as well, it is obviously a decision driven by feelings, not logic.
The idea that you can't trust code that was generated by heavy users of AI, because _they_ don't understand it enough to fix it, is false, because they can use AI to fix it.
In general, I have hard time understanding how one might even block other contributors from using ai.
Community management (which is an important part of PR/issue management for open source projects) should definitely take in account the human aspect, i.e. feelings.
And it just keeps looping like that until the context window bursts. In practice the model is great at writing new code, but when you feed it its own six month old spaghetti code with a floating bug in the state machine it just starts hallucinating and silently breaking neighboring features