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.
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.
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.
Though the most important aspect is that we need to know the motivation and thought process, and all AI can do is fabricate a 'plausible' one.
"And the Lord spake, saying, ''First shalt thou take out the Holy Pin. Then shalt thou count to three, no more, no less. Three shall be the number thou shalt count, and the number of the counting shall be three. Four shalt thou not count, neither count thou two, excepting that thou then proceed to three. Five is right out. Once the number three, being the third number, be reached, then lobbest thou thy Holy Hand Grenade of Antioch towards thy foe, who, being naughty in My sight, shall snuff it.'
... then flooded maintainers would be doing it.
The policy allows the reviewer to reject it on the "AI" grounds.
… but still unfortunately leaves reviewers having to spend time checking submissions and rejecting them.
* new contributor?
* more than 10 files affected (higher count are more valid)?
* wall of text on description without screenshots, etc?
just close the PR as AI, and then the contributor can challenge it if they feel it should not.
The problem is that a lot of AI contributions are lazily produced without review. Those that have been properly reviewed for correctness (tested to ensure actually working with no obvious undesirable side effects, tweaked where needed to be readable and understandable, fitting the other guidelines of the project, etc) will be indiscernible from human-only contributions, but there are a lot of people who make no such effort so the majority are not nearly this good.
That sounds like a contributor problem. Not an AI problem.
I still don't understand a "no AI" policy whose only purpose is to weed out bad PRs. You should be weeding out bad PR's regardless of their source. I don't see why treating a purely human-authored, but bad, piece of code should be treated any differently than an AI-authored one.
All they've accomplished is creaking an environment where good code can't be submitted unless the submitter lies.
You're not the first person I've seen argue that authorship doesn't matter, so I don't want to blame you for it, but I really don't understand where that idea is coming from. To me it seems obviously wrong.
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.
1. 400 chars/10 lines per commit
1b. Not more than 3 commits in the initial pull request
2. 20 lines of explanation for pull request
3. not more than 3 pull request open at any one time
Are we really in a situation where good code that solves a problem won't be merged because the person the person checked the "I used AI" box on the PR?
Ban PR's that are too big, don't have a clear purpose, touch too many areas, etc.
Say AI is used to identify and rewrite a single function that improves performance or fixes a bug, then the developer carefully reviews and tests it and submits a nice tight PR with all human communication.
So they don’t want that? They would just reject it?
If I’m understanding correctly, under the policy the higher performance function / bug free submission would be rejected and they could ask for a rewrite.
Should it then be rewritten from scratch, and clean room engineered so it doesn’t resemble the AI too much?
It's pragmatic. Linus once said, the reason C++ is not allowed in the kernel is to keep the C++ people out.
If commits written by AI wouldn't be substantially different, there would be no need to reject them.
So I agree with you that it won't discourage AI-based coding. But that's not even the intent.
I have some misgivings about AI, but I'm not a fundamentalist - you can't be or the machine will squish you, frankly - but please, don't spam me with text or code that could be much shorter. Relevant quotes:
"I didn't have time to write a short letter, so I wrote a long one instead"
"Brevity is the soul of wit"
This helps with PR reviews as it prevents a giant wall of text but it’s still verbose. However doing it this way cuts down on the wall of text at the expense of increased PR frequency.
Perhaps reconsider "If your feedback on PRs is just being absorbed by a machine and not going towards mentoring a potential future maintainer..."
So why the hate? :)
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.
Before sending it I have tried the patch locally. It worked.
So I sent the proposal. And it was accepted by the author.
... and includes the reviewer efficiency disrespected by your verbose bot.
Personally I'm also experiencing a bit of AI hangover after using it a lot in my own open-source projects. I find it's a bit like taking drugs (not that I have much experience with that) in the sense that in the moment I'm using these tools I feel great and powerful, writing features in a span of hours that would've taken me weeks to write by hand. But inevitably some time later I will look at the code and notice all the subtle cracks and inconsistencies the tool introduced, and despair a bit at the mess.
I now plan to use these tools less for extensive feature development and more for planning, debugging and narrow refactoring where I can put very strict guardrails on them. I'd still say it accelerates my work but not by a factor of 10, more like 1.5-3 (which is still a lot) given the care you need to ensure what is being built is actually good. For what I really like these tools is that I need less mental focus to do coding, but on the other hand I have this new kind of fatigue of being in a constant chat loop with a machine and trying to get it to do stuff based on natural language, never knowing how it will interpret what I write and wrote before. In that sense, these tools don't feel satisfying, it's like operating a machine where you try to push some buttons to get it to do something but the internal wiring changes all the time so you never know exactly what a given button combination will do and you have to figure it out by watching the machine and constantly adapting.
What AI unlocks is contributions from folks who are not at all involved in the project, and creating a PR is no longer enough to clear the gate of “this person is at least somewhat interested in the success of the project”.
AI is a force multiplier when wielded properly, but as an OSS maintainer, it’s easy to drown in prolific, low value “contributions” from folks who don’t care about the project.
Important to note that fast never meant much to open source and for good reason.
It was never a moat.
Moving fast and getting to the right destination is a huge moat. AI changes nothing here.
If you missed your destination, the solution isn't to think deeply about where you're supposed to go, it's to drive faster towards the next goal, so that if you make a mistake, it's not that big of a deal.
The slow moving projects didn't have some magic knowledge about where to go, they made the same mistakes but at a slower pace.
But all of this relied on the fact that code went through the brains of a human and said humans intelligence gets updated from the feedback, so that the developer builds a theory/model of what the software is really meant to look like in the end.
With AI, there is no such model. A context window is more like a tape or a film. The human is still responsible for building that mental model.
Our current generation of AI tools still seems to be very much not there when you really try and use it's output
There's a problematic dopamine dynamic as well where it's far too easy to reach for an AI when doing some work or starting a new project
I'm currently trying to dopamine hack my brain back to preferring to handwriting the majority of my code as opposed to reaching for claude
Time will tell if this is just a phase and it will get better or we'll need some sort of LLMs-anonymous
the assumption that all code (and everything else producing digital artefacts) will be written using AI in the near future,
No, we don't have to. We can just write code ourselves.
(My condolences to people who have jobs where AI is mandated.)
Very relatable. I wasted 2 weeks of full time effort earlier this year building a helper library with Sonnet. It was the first (and the last) time I vibe coded something. Once I was satisfied with it, I began using the library and within 2 days I was certain it was all for nothing. I will never get those 2 weeks back, but a lesson has been learnt.
I gave it an innocuous 2 sentence prompt, telling it to help me implement it, by building X first.
It produced code, and it was a big wall of code, which I expected. What I didn't expect is that the zed developers completely threw out the accept/reject workflow since Codex is no longer directly integrated into zed anymore.
Instead of the agent patiently waiting for my acceptance, it just kept going, it automatically ran cargo test, kept iterating like a dozen times, running cargo test and editing the code. Since I was in the middle of a big refactor, I kept a dozen compile errors as a reminder. It tried to "fix" these compile errors.
Then it proceeded to keep going even further and use the code to finish a file that was supposed to use the new code in the future.
The end result is as expected: It produced completely unusable garbage code that no sane person would sign off on and not just that, it used this garbage code and kept going with it, building more garbage on top of a garbage foundation. It also silenced the errors by producing more garbage code.
I'm the type of person that thinks the "accept always" button for specific commands is the dumbest idea ever [0], but they went one step further and basically made the agentic coding experience so bad it became unusable overnight. At this point I'd rather abandon agentic coding and go back to copy paste development with a chat interface.
[0] it's either accept or reject, everything else is stupid
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.
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
And some projects like WINE or ReactOS probably have to worry about that even more given they need to guarantee clean-room reverse engineering...
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.)
https://codeberg.org/brib/slopfree-software-index#why-care-a...
Not exactly an argument against using AI, is it? It's a bit like saying that GPS makes people worse at navigating by memory, which is true, but also not a strong argument for going back to paper maps. I feel the discourse is more about "stop using AI" and less about "how can we ensure our backup skills doesn't disappear".
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
You could get a perfectly adequate instance of a PR that is easily readable and verifiable while generated by an LLM, but generally they're not.
A policy pushes the aggregate to at least what looks and communicates as a human made PR that is functionally easier to approve. Whether they are created by an LLM or not is then secondary, but it likely pushes all PRs to be better.
But I'd argue that some projects [1] could benefit from the speed (and sometimes, quality) of AI code generation without filtering by something that's difficult to identify (i.e., is it truly human-generated).
One way could be to constrain the size of each commit and PR, and invest more heavily into the review process (e.g., tests, static/dynamic analysis, sandbox deployments), so even if you get 100s of contributions, you can knock each out quickly.
Obviously, easier said than done. And at that point, you may as well use the AI to make the commits yourself, instead of relying on community contributions.
[1] Of course, this is only the case if the project's only purpose is to be a tool, and not also an educational reason for humans to learn how to code - in which case, it makes sense to invest more into identifying the "cheaters".
I'm sure some are convinced LLMs can (eventually) manage everything, and others (I'm leaning more here) are convinced that you will always need a minimum amount of people both educated in the fundamentals and the domain to steer the project, and these people wont exist down the path of non-human PRs.
Imagine morals.
That makes much more sense now. The inability is completely on you, and you admit it at least.
There are functional reasons for a no-AI policy. It helps the Godot Foundation function to establish a no-AI policy. Do you argue it doesn't help them function?
Do you understand the difference between functional and non-functional?
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.
There are also plenty of valid personal reasons for refusing to generate code with AI - learning-by-doing and ownership of the result being the main ones, IMO.
> everybody wants to let AI do their work for them, but nobody wants to be downstream of AI work.
This is also true in my experience. But in my work, I found that I don't care how the code or comment was generated, as long as it doesn't try to overload my brain with irrelevant and obfuscated things, and as long as the person is not pretending that it's true, verified or their own creation (when it isn't).
Agreed, but my main point is most people continue to do exactly this and simply won’t stop. They think “AI took care of it and it’s good enough” then essentially shove their work on to the recipient 30% completed. So long as that’s the way most people use LLM’s we will continue to see restrictions put in place by the recipients.
Alternatively, if you have some vague idea [1] about what you expect to see/have, and the running code satisfies that idea, then it also runs.
Obviously, there are plenty of non-functional specs (e.g., security, cleanness, readability) that a code should probably fulfill before one finds it acceptable, but these are also not somehow impossible for state-of-the-art models to satisfy.
[1] Vibe, if you prefer, tho I dislike the term. Another related term is eyeball estimation.
If you use rsync clone by an LLM to copy a million files, will you bother to verify every single one was copied correctly?
And I'm not disagreeing - it is hard to anticipate what needs verifying, regardless if it's functional or non-functional.
But if it's not a spam submission, you could probably design tests or static/dynamic analysis tools that can verify those million copies much faster than manual reviews.
So you have integration tests that verify the general specs of the software and rely on your skills to verify the finer details. But if you’re using an LLM (and not reviewing every line), you can no longer be confident about those details.
And reviewing every line kills the speed advantage of using LLM.
> I can't think of a functional reason for a no-AI policy
These lists don't have you as an audience.
That is to the point!
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.
(It’s famously not well capable of sounding human)
As someone with 2 years of Godot experience (which seems like a lot given their lifespan), the underlying infra isn't strong enough to ward off the many competitors that will embrace AI at the heart of the engine. Ironically, the best engine right now for AI-assisted coding is Godot! It has plain text scene files, and Opus does a half decent design - screenshot - iterative flow to get things off the ground before artists clean it up.
Being an open source maintainer is HARD work I wouldn't wish on my worst enemy. However, the Godot team has very strong opinions that don't really drive especially better software. There is a small history of being confrontational in their github PRs, and a strong opinionated approach. They mostly inherited their current spot in the market from mistakes and commercial pressures of the top two engines (cough Unity per-install fees).
The removal of AI-generated contributions is pitched as helping them maintain a better core product, but in reality, (my prediction) it will end up massively hampering velocity over the next 3-5 year horizon.
At the same time, it used to be impractical to make your own game engine to make a game. Now, with AI-assisted coding, strong game devs have a viable option, despite the added complexity. Rust libraries like bevy provide the training wheels to a half decent dev + AI assistant that can build more bespoke smaller engines for indies. To gain Godot's level of indie marketshare, a single breakout engine project that embraces vibecoding could be enough. I expect that will gobble up eager /r/aigamedev Redditors and the new swarm of unemployed juniors fresh out of college.
Who are the competitors? Something lower level like bevvy? The way I see it even with vibe coding you need to do a lot of infrastructure work to make editing easy, and anybody except Unity is far off from them.
GUI Editor is not one I'd list.
Internal tooling stood up a GUI Editor clone within a few weeks that was targeted towards our specific use case. Their editor isn't uniquely ergonomic. In fact, for about 3 releases, one of the highest requested objects was multiple tabs at the same time. A rather standard feature in an editor and especially a modern code editor.
My argument isn't totally about individual devs making engines (though it is actually feasible on a Max plan), I'm imagining a very small team competitor that embraces AI-assisted PRs, internally and externally, along with vibecoding directly baked into the app itself (MCP or more direct claude code scripting language integration). That would be able to match or exceed the functionality in Godot, probably with more common and performant scripting languages (Rust + Luau for example).
PRs with just the results and final code doesn't seem better even if we assume ai coding will be much faster.
The team is taking a pretty strong stance against external AI-assisted PRs, which makes you think they'd take a weak stance against internal AI-assisted PRs? It's hard to draw the exact line, but maybe?
For our team, the outcome is the PR, and you have to set up _a lot of testing infrastructure_ to prevent regressions. It's a skillset like any other.
It would be consistent with their actions that my belief is they are slow to adopt workflows that will accelerate them. Thus velocity will decrease.
What are you basing this off of? There are already plenty of game engine projects like what you describe here. Doesn't seem to have affected Godot thus far, unless I'm missing something.
There isn't, until there is. These things take time. The tech has to be adopted, the people have to integrate into game jams, indies percolate. Godot is young, my predictions are 3-5 years.
Regarding competition though, the question is about the unique selling points of Godot that would be hard to replicate. Before AI coding, there is a _lot of momentum_ for leaders in the game engine world. Everyone specializes and it takes many years of game cycles to make the switch to a new engine. Not anymore!
So we have yet to see a dog-eat-dog game engine world, and in that world, ejecting AI-coding could in fact be a net negative. That's what I am arguing at least.
Regarding the unique selling points of the engine: 1. Open-source 2. Node/Scene encapsulation design: Big! - Easily my favorite part of GDScript. Easy to replicate. 3. Scripting languages: GDScript, buggy C# - AI-coding doesn't care what language as long as it's popular
My suspicion: A competitor could use a known compiled language (Rust) and a scripting language (luau) and get the same mileage as Godot and replace every one of their selling points with more performant code. Because they waited so long to deploy a marketplace, they have very little sticky bits to their market share.
I mean, even with the advent of “AI” agents, is software today any better than it was 3 years ago?
I think teams embracing too much LLM coding are going to see a continued decrease in quality and a massive drop in team productivity. Godot, on the other hand, is avoiding this. While it might not be as trendy, I think it’ll be a competitive advantage in the long term.
When accounting for "coding taste," I think there is equal or higher quality output over small teams, and if there is a decrease in software quality, it's nowhere near the implied amount (5-10% at most) with a massive gain in speed (approx 3x? 4x? hard to measure). Those numbers net out positive in the end, especially as the team starts to understand and ship with AI in the loop.
Like who? Unity/Unreal? Those are completely different engines for a different audience. IMO, Godot has a unique market space and no real peers. I think this was a wise decision that only adds to their brand as something for creators rather than corporations.
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)
These people are farming contributions to major FOSS projects as a form of CV-padding. The same is happening with vulnerability reports. The sloppers may genuinely think they're helping out, or they may know their 'contributions' are a net negative for the projects, in the end it doesn't matter much. When you're motivated by direct economical incentives and your situation is precarious enough (in today's labor market, it is), externalities are not high on your list of concerns.
Developers who have a nice job and career, and are making good money, might think of doing open source to “contribute to society” or something like that.
But new developers who are seeing those golden opportunities shut in front of their faces, they feel like they have to desperately fight for the last places on the lifeboat, so I don’t blame them for wanting to farm cv points and game the system of incompetent recruiters who make much more then they will do, instead of spending time and effort doing something nice for society hoping someone will notice (lol they will not, especially if you’re a nobody)
They can even list on their CV that they are the maintainers of those projects.
I do think I helped out.
And I have discovered this edge case when fiddling with my homelab which is my hobby.
Both PR were tiny, not different from human PR. I still believe these were valuable additions, and obviously some maintainers think the same.
- Disable public pull requests.
- Require people to open an issue or discussion. Issues and discussions should have stated length/quality parameters. If an issue is a wall of Claude-text, users should be prepared for this text to be automatically summarized into plain language. If you don't want your Claude-text to be machine-turned into something human-consumable, the onus is on you to post human text up front.
- PRs are only drafted once approved in issue or discussion
I'm wondering if this is a tractable approach that yields results. I've seen references to a few projects trying something like this. Would be nice to hear folks experience.
I am with the maintainers on this one, I am not quite sure how they plan to filter out AI slop, but atleast all slop PRs should stop now, I am sad to not have the free time to contribute to the project or maybe just not enough energy.
In generally, I am just sad that this is where the public contributions and open source has come down to, couldn't we all have been more fun working together, what makes someone think they can vibe code their way to a meaningful PR and not even mention that it's a vibe PR.
Why does this PR appear to add any value, and if it does provide some insights into solving a problem, why do you expect it to be merged and reviewed?
The best defense of these drive by vibe PRs can be I found a bug, tried to fix it, seems to work, here's my code, someone who has more time could take a look and see if it has any insights.
Also only works on PRs that are specifically bug fixes or address some issue specifically. Not your omega 10K+ line feature commits...
Why do some people feel compelled to make these PRs? I am genuinely curious, I don't hate these people but do these folks think that this is adding some value?
However, as a senior engineer with fairly deep technical knowledge in these areas, I'm now using AI in my own projects. Frankly, before even touching Github, I'm already drowning in code reviews generated by my own use of an LLM!
There are meaningful, generally good PRs waiting for my attention against GodotJS, and other projects I (somewhat) maintain e.g. MoonSharp, C# Lua runtime. It was already extremely difficult to stay on top of PR code reviews for reasonably technical projects. When you're already somewhat burnt out from reviewing LLM code all day, it's so much more exhausting than it used to be.
I can fully understand the reasoning for it and I also think it's by and large a good idea because one of the cool things about open source projects is that they are traditionally good places for younger developers to get started or hop in and learn. There's a lot more to be learned from writing everything yourself and thinking through it.
there's a few elsewhere in the comments here but I'm not sure how comprehensive any are
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.
* Software security - I.e. Mozilla blog post on using Mythos for software security [1]
* Algorithms - AlphaEvolve makes real progress on matrix multiplication [2]
* Open source - Backlog crushing in openvpn [3]
* Corporate - CloudFlare Oauth workers [4]
People are clearly using AI to ship real work that people end up using directly or indirectly. Projects like Godot are also in a weird spot though.
[1]. https://blog.mozilla.org/en/privacy-security/ai-security-zer...
[2] https://arxiv.org/abs/2506.13131
[3] https://stanislas.blog/2025/12/claude-code-opus-open-source-...
FOSS has become the release valve for too much labour supply.
But the blog post is written in future tense. I don't think they have a new contribution policy file yet
...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....
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's basically the same issue as spam in emails. It was bad before, and automation made it a zillion times worse.
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.
(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; [...]
How about if AI generates code in a file, then I copy/paste bits... like stack overflow ?
I assume most IDEs allow you to use their snippets under many different licenses. LLMs have mostly been trained on public git repos under lots of different licenses (most importantly, Copyleft licenses)
Allowing AI use by 'trusted contributors' has been suggested and discussed, but there were enough reasons against it and not enough established benefit.
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.
People are never entitled to their contributions getting accepted to someone else's code base.
The rule is general on purpose to allow the maintainer to freely remove whatever is very evident is just ai slop
Do you think sociopaths willing to lie about how they came up with a contribution are really that common?
Because AI is frowned upon where I work, I kept that under the radar. And I got nothing but praises for the good work, everybody loving it. Later I had the opportunity to port a piece of software from one language to another. LLMs are great for porting stuff when steered well. Again, nothing but praises for the amazing work done in a very short time. And this is where I tried to open a debate about AI by disclosing my tools and methods. And boom, suddenly I was evil. Praises gone. But still, none had the guts to throw the port to trash, because it's still very good. Hypocrisy.
So yes, call me sociopath if you like, but I will lie, produce better software and get the praises if I have to work in an environment that values tools and methods over results.
On an unrelated note, I lost all respect and eagerness to try it out after the drama.
Also, what drama?
Google Godot drama 2024, for some top-notch community mismanagement classes.
Though I guess if your stance is “these people should have less rights” then it is politics, but in that case I don’t see the drama for banning people.
This doesn't mean I agree with them, but pretending this isn't a complex and very large issue with multiple facets is just wrong.
Basically some incredibly stupid highschool level drama fed by the worst YouTubers you can think of. People vaguepost about it because it's so dumb.
You just can't expect someone who isn't willing enough to write one good PR to be willing to become a good maintainer.
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.
I predict any project that allows AI will slowly degrade in quality
I've seen policies like this in various places and they do not generally seem to be based quantitative measures of code functionality, security, and efficiency.
There are other approaches to take to deal with large numbers of incoming PRs: improved CI, AI-readable standards for AI code, better static testing, AI first-pass review, etc.
It's fine to enshrine hobbyism into your code review policy to keep things fun and human-scale. On the other hand, where projects actually matter, it is necessary to think about code review as part of an industrial process with inputs and outputs, one where this sort of thing has no place.
This gets a lot harder when there is a giant wall of text that the pull requester doesn't understand and can't really discuss outside of asking AI (and probably getting "The reviewer is right to push back - I was too aggressive in my blah blah blah" as an answer).
A lot of (but maybe not all) pull requests are fundamentally a human to human task, even if there is a lot of technical details involved.
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.
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.
There, I solved FOSS sponsorship.
Yet all that is being produced is piggy-backing unchecked vibe-slop.
At some point you just call it failed.
Puh-lease. Unity's "hara-kiri" was in 2023 by which time Godot was NINE years old. Hara-kiri or no hara-kiri Godot has shown longevity and relevance. Anything gained from Unity's own-goals is just cherry on top.
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.
The problem with "they can just have the AI fix what's wrong" is explained a bit more in the contribution policy itself - https://godotengine.org/article/contribution-policy-2026/ - nice-to-have features often require design decisions which aren't obvious to outside contributors, but which can create a lot of work for maintainers, especially in game engines where backwards compatibility is a must.
A good example is their ongoing effort to restore C# support to web builds - https://github.com/godotengine/godot/pull/106125 - in Godot 3.x .NET integration was done through Mono, so web games could just bundle the Mono interpreter, but for 4.x which uses mainline .NET, the original plan of instead building WASM bundles (https://godotengine.org/article/platform-state-in-csharp-for...) was blocked by .NET WASM bundles not supporting dynamic linking, not by Godot itself.
The modal person asking "When is C# going to be supported for web games?" or prompting a fix likely won't know to ask "Does my fix need SharedArrayBuffer support?" and "Does my fix rely on patching the .NET runtime?", or why those questions matter, and will get frustrated when the fix that works on their machine then can't be merged into the main project.
AI isn't some all powerful programming oracle that can do anything. Sometimes it doesn't do things right and if you're just blindly copying and pasting its mistakes to some poor reviewer that's going to piss them off.
Also what's the point? If you're just relaying messages to an AI what do you add?
I'm guessing you've never been on the receiving end of this behaviour.