Is it slop if it is carefully calculated? I tire of hearing people use slop to mean anything AI, even when it is carefully reviewed.
For someone’s website or one business maybe the risk is worth it, for a widely used software project that many others build on it is horrifying to see that much plausible code generated by an LLM.
Engineers will focus on professionalism of the end product, even if they used AI to generate most of the product.
And I'm not going by "title", but by mindset. Most of my fellow engineers are not - they are just programmers - as in, they don't care about the non-coding part of the job at all.
Are you genuinely confident in a framework project that lands 19kloc generated PRs in one go? I’d worry about hidden security footguns if nothing else and a lot of people use this for their apps. Thankfully I don't use it, but if I did I'd find this really troubling.
It also has security implications - if this is normalised in node.js it would be very easy to slip in deniable exploits into large prs. It is IMO almost impossible to properly review a PR that big for security and correctness.
What kind of logic is this?
and it's not like super carefully written code is magically perfect. we know that djb can release things that are close to that, but almost nobody is like him at all!
if there's anyone i would trust in exploring these avenues, it's him and the maintainers doing god's work in the nodejs repo in these past few years.
I do not think it is wise to brag that your solution to a problem is extremely painful but that you were impervious to all the pain. Others will still feel it. This code takes bandwidth to host and space on devices and for maintainers it permanently doubles the work associated with evolving the filesystem APIs. If someone else comes along with the same kind of thinking they might just double those doubled costs, and someone else might 8x them, all because nobody could feel the pain they were passing on to others
> Bundle a full application into a Single Executable.
Embed a zip file into the executable, or something. Node sort of supports this since v25, see --build-sea. Bun and Deno support this for a longer time.
> Run tests without touching the disk.
This must be left to the host system to decide. Maybe I want them to touch the disk and leave traces useful for debugging. I'd go with tmpfile / tmpdir; whoever cares, knows to mount them as tmpfs, which sits in RAM. (Or a ramdisk under Windows.)
> Sandbox a tenant’s file access. In a multi-tenant platform, you need to confine each tenant to a directory without them escaping
This looks like a wrong tool, again. Run your Node app in a container (like you are already doing), mount every tenant's directory as a separate mount point into your container. (Similar with BSD jails.) This seems like the only problem that is not trivial to solve without a "VFS", but I'm not very certain that such a VFS would be as well-audited as Docker, or nsenter and unshare. The amount of work necessary for implementing that is too much for the niche benefit it would provide.
> Load code generated at runtime. See tmpfs for a trivial answer. For a less trivial answer, I don't see how Node's code loader is bound to a filesystem. If it can import via https, Just use ESM loader hooks and register() your loader, assuming you're running Node ≥ 20.6.
While the large code changes were maintained, they were often split up into a set of semantically meaningful commits for purposes of review and maintenance.
With AI blowing up the line counts on PRs, it's a skill set that more developers need to mature. It's good for their own review to take the mass changes, ask themselves how would they want to systematically review it in parts, then split the PR up into meaningful commits: e.g. interfaces, docs, subsets of changed implementations, etc.
Well, the process you’re describing is mature and intentionally slows things down. The LLM push has almost the opposite philosophy. Everyone talks about going faster and no one believes it is about higher quality.
If there is some bug that slips by review, having the PR broken down semantically allows quicker analysis and recovery later for one case. Even if you have AI reviewing new Node.js releases for if you want to take in the new version - the commit log will be more analyzable by the AI with semantic commits.
Treating the code as throwaway is valid in a few small contexts, but that is not the case for PRs going into maintained projects like Node.js.
> Everyone talks about going faster and no one believes it is about higher quality.
The fact is, it's useful as a tool, but you still should review what's going on/in. That isn't always easy though, and I get that. I've been working on a TS/JS driver for MS-SQL so I can use some features not in other libraries, mostly bridging a Rust driver (first Tiberious, then mssql-client), the clean abstraction made the switch pretty quick... a fairly thorough test suite for Deno/Node/Bun kapt the sanity in check. Rust C-style library with FFI access in TS/JS server environment.
My hardest part, is actually having to setup a Windows Server to test the passswordless auth path (basically a connection string with integrated windows auth). I've got about 80 hours of real time into this project so far. And I'll probably be doing 2 followups.. one with be a generic ODBC adapter with a similar set of interfaces. And a final third adapter that will privide the same methods, but using the native SQLite underneath but smothing over the differences.
I'm leveraging using/dispose (async) instead of explicit close/rollback patterns, similar to .Net as well as Dapper-like methods for "Typed" results, though no actual type validation... I'd considered trying to adapt Zod to check at least the first record or all records, and may still add the option.
All said though, I wouldn't have been able to do so much with so relatively little time without the use of AI. You don't have to sacrifice quality to gain efficiency with AI, but you do need to take the time to do it.
Like, why on earth would I spent hours reviewing your PR that you/Claude took 5 minutes to write? I couldn't care less if it improves (best case scenario) my open source codebase, I simply don't enjoy the imbalance.
Not everyone has the same motivations. I’ve done open source for fun, I’ve done it to unblock something at work, I’ve done it to fix something that annoys me.
If your project is gaining useful functionality, that seems like a win.
Of course any chess bot is going to play better, but that's not the point
Because they're implicitly asking me to put in effort as a reviewer. Pretending that they put more effort in than they have is extremely rude, and intentionally or not, generating a large volume of code amounts to misleading your potential reviewers.
> If there was a huge amount of tedium that they used Claude Code for, then reviewed and cleaned up so that it’s indistinguishable from whatever you’d expect from a human; what’s it to you?
They never do though. These kind of imaginary good AI-based workflows are a "real communism has never been tried" thing.
> If your project is gaining useful functionality, that seems like a win.
Lines of code impose a maintenance cost, and that goes triple when the code quality is low (as is always the case for actually existing AI-generated code). The cost is probably higher than the benefit.
My personal approach to open source is more or less that when I need a piece of software to exist that does not and there is no good reason to keep it private, it becomes open source. I don’t do it for fun, I do it because I need it and might as well share it. If someone sends me a patch that enhances my use case, I will work with them to incorporate it. If they send me a patch that only benefits them it becomes a calculus of how much effort would it take for me to review it. If the effort is high, my advice is to fork the project or make it easier for me to review. Granted I don’t maintain huge or vital projects, but that’s precisely why: I don’t need yet another programming language or runtime to exist and I wouldn’t want to work on one for fun.
I would probably never be able to review this kind of code in open source projects without any financial compensation, because of that reason. Not because I don't like LLMs, not use LLMs, or think their code is of bad quality. But, while without LLMs I know there was a person who sat down and wrote all this in painstaking work, now I know that he or she barely steered a robot that wrote it. It may still be good work, and the steering and prompting is still work and requires skill, but for me I would not feel any emotional value in this code, and it would make it A LOT harder to gather motivation to review it. Interestingly, when I think about it, I realize that I would inherently have motivation to find out how the developer prompted the agent.
Like, you know, when I see a wooden statue of which I know it was designed and carved by someone in months of work, I could appreciate every single edge of the wood much more than if there's a statue that was designed by someone but carved by some kind of wooden CNC machine. It may be same statue and the same or even better quality, and it was still skillful work, but I lose my connection to it.
Can't quite pinpoint it, but for me, it seems, the human aspect is really important here, at least when it's about passion and motivation.
Maybe that made some sense, idk. I just wrote out of my ass.
If the PR does what it says it does, why does it actually matter if it took 2 weeks or 2 minutes to put together, given that it's the equivalent level of quality on review?
You're right that the issue isn't how many minutes it took. The issue is that it's slop. Reviewing thousands of lines of crappy code is unpleasant whether they were autogenerated or painstakingly handcrafted. (Of course, few humans have the patience and resistance to learning to generate the amount of terrible code that AIs do routinely).
For some people, the point was precisely to improve the software available to the global commons through a thriving and active open source effort. "Too many people are giving me too many high-quality PRs to review" is hardly something to complain about, even if you have to just pick them randomly to fit them in the time you have without AI (or other committers) to help review.
If your idea of open source is just to share the code you wanted to work on and ignore contributions, you can do that too. SQLite does that, after all.
Note aside, OpenJS executive director mentioned it's ok to use AI assistance on Node.js contributions:
I checked with legal and the foundation is fine with the DCO on AI-assisted contributions. We’ll work on getting this documented.
It is great to have a legal perspective on compliance of LLM generated code with DCO terms, and I feel safer knowing that at least it doesn't expose Node.js to legal risk. However it doesn't address the well known unresolved ethical concerns over the sourcing of the code produced by LLM tooling.
It's not an AI issue. Node.js itself is lots of legacy code and many projects depend on that code. When Deno and Bun were in early development, AI wasn't involved.
Yes, you can speed up the development a bit but it will never reach the quality of newer runtimes.
It's like comparing C to C++. Those languages are from different eras (relatively to each other).
Speed code all your SaaS apps, but slow iteration speeds are better for a runtime because once you add something, you can basically never remove it. You can't iterate. You get literally one shot, and if you add a awkward or trappy API, everyone is now stuck with it forever. And what if this "must have" feature turns out to be kind of a dud, because everyone converged on a much more elegant solution a few years later? Congratulations, we now have to maintain this legacy feature forever and everyone has to migrate their codebase to some new solution.
Much better to let dependencies and competing platforms like bun or deno do all the innovating. Once everyone has tried and refined all the different ways of solving this particular problem, and all the kinks have been worked out, and all the different ways to structure the API have been tried, you can take just the best of the best ideas and add it into the runtime. It was late, but because of that it will be stable and not a train wreck.
But I know what you're thinking. "You can't do that. Just look at what happens to platforms that iterate slowly, like C or C++ or Java. They're toast." Oh wait, never mind, they're among the most popular platforms out there.
Time is highly correlated with expertise. When you don’t have expertise, you may go fast at expense of stability because you lack the experience to make good decisions to really save speed. This doesn’t hold true for any projects where you rely on experts, good processes and tight timelines (aka: Apollo mission)
but you can only have two of them at the same time.
and we’re talking about FOSS here, so cheap kinda has to be one of them.
So, it's fast if you get lucky and are able to one-shot it, affordable-ish if you get lucky and are able to one-shot it and correct if you get lucky.
And that tends to happen if you're working on a specific set of codebases which are close to the most commonly occurring codebases in the training data set -- i.e. CRUD webapps / heavy boilerplate usage. Most FOSS projects probably don't fit in that camp (i have no data to support this, it's just my gut experience).
And again, I'm not making a claim that the slow and steady tradeoff is best for all situations. Just that it is a great tradeoff for foundational platforms like a runtime. On a platform like postgresql or the JVM, the time from initial proposal to being released as a stable feature is generally years, and this pace I think has served those platforms well.
But I'm open to updating my priors. Do you think there are foundational platforms out there that iterate quickly and do a good job of it?
You’ve read people saying the same thing hundreds of times and have somehow taken that as meaning that it’s credible.
Neither you nor I nor anyone else here knows what the “effects” are, because this is brand new tech, and it’s constantly changing. Yet you’re speaking with absolute confidence.
“Big tech” has downtime all the time, and LLMs did not change that fact. The only difference is that the peanut gallery that is already worked up about AI for philosophical / cultural reasons is suddenly ready to blame AI for every issue under the sun.
You think that you’re making a technical argument but you’re just repeating the same taking points I see teenagers regurgitating on TikTok. There’s nothing intelligent or credible about it.
Don't slap someone else down because you don't know something.
That sort of statement might also be sarcasm in another context: I personally use AI a lot, but also recognize that there are a lot of projects out there that are suffering from low quality slop pull requests, devs that kinda sign out and don't care much about the actual code as long as it appears to be running, alongside most LLMs struggling a lot with longer term maintenance if not carefully managed. So I guess it depends a lot on how AI is used and how much ideological opposition to that there is. In a really testable codebase it could actually work out pretty well, though.
If and when there is evidence that AI is actually increasing the speed of improvement (and not just churn), it would make sense to permit it. Unless and until such evidence emerges, the risks greatly outweigh the benefits, at least for a foundational codebase like this.
I can't help but wonder if this matter could result in an io.js-like fork, splitting Node into two safe-but-slow-moving and AI-all-the-things worlds. It would be historically interesting as the GP poster was, I seem to recall, the initial creator of the io.js fork.
If submitter picks (a) they assert that they wrote the code themselves and have right to submit it under project's license. If (b) the code was taken from another place with clear license terms compatible with the project's license. If (c) contribution was written by someone else who asserted (a) or (b) and is submitted without changes.
Since LLM generated output is based on public code, but lacks attribution and the license of the original it is not possible to pick (b). (a) and (c) cannot be picked based on the submitter disclaimer in the PR body.
Whether AI output can fall under copyright at all is still up for debate - with some early rulings indicating that the fact that you prompted the AI does not automatically grant you authorship.
Even if it does, it hasn't been settled yet what the impact of your AI having been trained on copyrighted material is on its output. You can make a not-completely-unreasonable argument that AI inference output is a derivative work of AI training input.
Fact is, the matter isn't settled yet, which means any open-source project should assume the worst possible outcome - which in practice means a massive AI-generated PR like this should be treated like a nuke which could go off at any moment.
1. Copyright cannot be assigned to an AI agent.
2. Copyrighted works require human creativity to be applied in order to be copyrighted.
For point 2 this would apply to times were AI one shots a generic prompt. But for these large PRs where multiple prompts are used and a human has decided what the design should be and how the API should look you get the human creativity required for copyright.
In regards to being a derivative work I think it would be hard to argue that an LLM is copying or modifying an existing original work. Even if it came up with an exact duplicate of a piece of code it would be hard to prove that it was a copy and not an independent recreation from scratch.
>the worst possible outcome
The worst possible outcome is they get sued and Anthropic defends them from the copyright infringement claim due to Anthopic's indemnity clause when using Claude Code.
Also the commercial version is limited to “…Customer and its personnel, successors, and assigns…”. I am very much not a lawyer and couldn’t find definitions of these in the agreement but I am not sure how transferable this indemnity would be to an open source project.
Well, it's a good thing you're not on the hook for defending against it, then.
Like I said in another comment, you don't have a license just because they're cool and look neat. You have them specifically to guard against people like patent trolls, who are trying to wreck your shit and take your lunch money. It's not an abstract risk.
If you are on the hook for defending against it, and your risk assessment is based on emotional, irrational fear and not an objective understanding of the risks, then you're doing people a disservice and should step down.
You don't have a license because it's what all the cool kids are doing, you have one in case shit goes sideways and someone decides to try and ruin your day. You do, in fact, have to assume the worst.
The "nuke" here is some litigious company -- let's call them Patent Troll Rebranded (PTR) -- discovers that the LLM reproduced large amounts of their copyrighted code. Or it claims to have discovered it. They have large amounts of money and lawyers to fight it out in court and you are a relatively shoestring language foundation.
Either you have to unwind years of development to remove the offending code or you're spending six figures or more to defend yourself in court, all because you didn't bother to anticipate things that are anticipatable.
(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; or
"in part" is a trivial bar to clear.
If there isn't, then (b) works fine, the code is taken from the LLM with no preexisting license. And it would be very strange if a mix of (a) and (b) is a problem; almost any (b) code will need some (a) code to adapt it.
That's not good enough to comply with (b). The code must be specifically covered by an open-source license, it's not enough for it to just not have a license.
As far as I'm concerned, public domain counts as "an appropriate open source license".
For material whose author is known and has explicitly placed it in the public domain, sure. For code that fell off the back of a truck, not so much.
(There's always a risk of an LLM copying something verbatim by accident, but if the designers are doing their job that chance gets low enough to be acceptable. Human code has that risk too after all. (And for situations that aren't an accident, with the human intentionally using snippets to draw out training text, then if they submit that code in a patch it's just a human violating copyright with extra steps.))
Where? I hadn't heard of any such ruling.
This page has a pretty good overview.
> Both the federal and circuit courts in the District of Columbia have upheld the Copyright Office's refusal to register copyrights for works generated solely by machines, establishing that machine ownership would conflict with heritable property rights as establish by the Copyright Act of 1975.[16] As of March 2026, the Supreme Court of the United States has denied hearing challenges to the Copyright Office's decision.[17]
On a more serious note, I think that this will be thoroughly reviewed before it gets merged and Node has an entire security team that overviews these.
Oh I'd use an llm to generate large amounts of feedback and request changes!
Your paid to do a job, you're either professional or you aren't.
It does mean that nurses might end up getting paid more than software engineers, but why is that a bad thing?
> Many contributions contain routine, non-copyrightable material, and developers still sign off on them.
> Compilers change code in ways developers do not always track. Template generators create output from their own logic. Stack Overflow answers are often copied into codebases without much thought about licensing.
Who reviewed and approved the PR?