Coding agents could make free software matter again
gjlondon.com
gjlondon.com
The thing that leaves a bad taste in my mouth is the fact that my works were likely included in the training data and, if it doesn't violate my licenses (GNU 2/3), it certainly feels against the spirit of what I intended when distributing my works.
I was made redundant recently "due to AI" (questionable) and it feels like my works in some way contributed to my redundancy where my works contributed to the profits made by these AI megacorps while I am left a victim.
I wish I could be provided a dividend or royalty, however small, for my contribution to these LLMs but that will never happen.
I've been looking for a copy-left "source available" license that allows me to distribute code openly but has a clause that says "if you would like to use these sources to train an LLM, please contact me and we'll work something out". I haven't yet found that.
I'm guessing that such a license would not be enforceable because I am not in the US, but at least it would be nice to declare my intent and who knows what the future looks like.
Frankly do you think AI companies have even the remotest amount of respect for these licenses anyways? They will simply take your code if it is publicly scrapeable, train their models, exactly like they have so far. Then it will be up to you to chase them down and try to sue or whatever. And good luck proving the license violation
I dunno. I just don't really believe that many tech companies these days are behaving even remotely ethically. I don't have much hope that will change anytime soon
Take a litigious company like Nintendo. If one was to train an LLM on their works and the LLM produces an emulator, that would force a lawsuit.
If Nintendo wins, then LLMs are stealing. If Nintendo loses, then we can decompile everything.
If my license explicitly says "any LLM output trained on this code is legally tainted," I feel like BigAICorp would be foolish to ignore it. Maybe I couldn't sue them today, but are they confident this will remain the case 5, 10, 20 years from now? Everywhere in the world?
Surely if your license says "LLM output trained on this code is legally tainted", it is going to dissuade them.
Alternatively, they can learn to trust me on this and simply exclude/evict my code from the training corpus.
Are you saying that you believe that untested but technically; models trained on GPL sources need to distribute the resulting LLMs under GPL?
If an AI outputs copyrighted code, that is a copyright violation. And if it does and a human uses it, then you are welcome to sue the human or LLM provider for that. But you don't get to sue people for perceived "latent" thought crimes.
That being said, I don't think that your analogy is valid in this case.
> GitHub and Windows and IDEs need to be open source because they can output FOSS code
They can output FOSS code, but they themselves are not derived from FOSS code.
It can be argued that the weights of a model is derived from training data, because they contain something from the training data (hard to say what exactly: knowledge, ideas, patterns?)
It can also be argued that output is derived from weights.
If we accept both of those claims, then GPL training data -> GPL weighs -> every output is GPL
> If an AI outputs copyrighted code
Again, the issue is not what exactly does AI output, but where it comes from.
(I say 'relatively easy'. Not that it would be trivial.)
Or, in the case of LLMs, recklessly swing about software they don't understand while praying to find a business model.
They can call it whatever they want, but I don't think that it is illegal.
Yes, corporations take a large cut, but creative people welcomed copyright and made the bargain and got fame in the process. Which was always better for them than let Twitch take 70% and be a sharecropper.
Silicon Valley middlemen are far worse than the media and music industry.
Most mid-list authors make very little from copyright. A lot of the "authors" who make a lot of money from writing are celebs who slap their name on a ghost written work.
> Which was always better for them than let Twitch take 70% and be a sharecropper.
Copyright predates Twitch or giant corporations and was designed to protect the profits of the publishers from the start.
In this nothing changed. Authors never were and still are not the point of copyright/IP.
How is any of this new?
What makes it all tricky for the courts is there's not a good way to really identify what part the generated code is a derivative of (except in maybe some extreme examples).
However, that number would typically be very very very very small, making it hard to argue that the whole model is a derivative of that one individual document.
Nevertheless, a similar approach might work if you took a FOSS project as a whole, e.g. "the model knows a lot about the Linux kernel because it has been trained on its source code".
However, it is still not clear that this would be necessarily unlawful or make the LLM output a derivative work in all cases.
It seems to me that LLMs are trained on large FOSS projects as a way to teach them generalisable development skills, with the side effect of learning a lot about those particular projects.
So if I used a LLM to contribute to the kernel, clearly it would be drawing on information acquired during its training on the kernel's code source. Perhaps it could be argued that the output in that case would be a derivative?
But if I used a LLM to write a completely unrelated piece of software, the kernel training set would be contributing a lot less to the output.
Not really.
Think of, for example, a movie like "who framed roger rabbit". It had intellectual property from all over. Had the studios not gotten the rights from each or any of those properties, they could have been sued for copyright infringement. It's not really a question of influence.
So yeah, while the LLM might have been trained on the kernel, it was also likely trained on code with commercial licenses. Conversely, because was trained on code with GPL licenses, that might mean commercial software with LLM contributions need to inherit the GPL to be legal (and a bunch of other licenses).
It's a big old quagmire and I think lawyers haven't caught up enough with how LLMs work to realize this.
That's debatable. In case of a king you always know whom to blame and who has full responsibility. No opportunity to hide behind "well, you voted for this" or "I'm not making the laws, I'm merely enforcing them".
Why do you think "fair use" doesn't apply in this case? The prior Bartz vs Anthropic ruling laid out pretty clearly how training an AI model falls within the realm of fair use. Authors Guild vs Google and Authors Guild vs HathiTrust were both decided much earlier and both found that digitizing copyrighted works for the sake of making them searchable is sufficiently transformative to meet the standards of fair use. So what is it about GPL licensed software that you feel would make AI training on it not subject to the same copyright and fair use considerations that apply to books?
The poster doesn't like it, so it's different. Most of the "legal analysis" and "foregone conclusions" in these types of discussions are vibes dressed up as objective declarations.
Whether data acquired from a licence that specifically forbids building a derivative work without also releasing that derivative under the same licence counts as a legitimate data gathering operation is anyone's guess, as those specific circumstances are about as far from that prior case as they can be.
Everybody is trying to have their cake and eat it, too, by license laundering.
Heck, money laundering means you at least lose some of the money.
> This License acknowledges your rights of fair use or other equivalent, as provided by copyright law.
It is legitimate to acquire GPL software. The requirements of the license only occur if you're distributing the work AND fair use does not apply.
Training certainly doesn't count as distribution, so the buck passes to inference, which leaves us dealing with substantial similarity test, and still, fair use.
If a human reads GPL code and outputs a recreation of that code (derivative work) using what they learned - that is illegal.
If an AI reads GPL code and outputs a recreation of that code using what it "learned" - it's not illegal?
If that is the case, then copyright holds no weight any more. I should be allowed to train an LLM on decompiled firmware (say, Playstation, Switch, iPhone) in countries where decompilation is legal - then have the LLM produce equivalent firmware that I later use to build an emulator (or competing open source firmware).
It's funny you mention that, because one of the biggest fair use cases that effectively cemented "fair use" for emulators is Sony Computer Entertainment Inc v. Connectix Corp.[1] where the copying of PlayStaion BIOS files for the purposes of reverse engineering and creating an emulator was explicitly ruled to be fair use, including running that code through a disassembler.
[1]: https://en.wikipedia.org/wiki/Sony_Computer_Entertainment,_I....
- The ROM was used to build the emulator (which didn't include the ROM but was only able to use it like any other hardware)
- Then the ROM was used to derive a specification and do A/B testing on (similar to Phoenix BIOS), and a different team coded a replacement ROM
There is no cleanroom inside an LLM.
The current supreme court may think that machine learning is some sort of magic exception, but they also seem to believe whatever oligarchs will bribe them to believe. Again, I doubt the law will be enforced as written, but that has more to do with corruption than any meaningful legal theory. Arguments against this claim seem to ignore that courts have already ruled these systems to not have intellectual property rights of their own, and the argument for fair use seems to rely pretty heavily on some handwavey anthropomorphization of the models.
Broadly speaking, yes it does. The whole point of fair use is that you don’t need a license.
Here’s the 4 part test from 17 U.S.C. § 107:
1. the purpose and character of the use, including whether such use is of a commercial nature or is for nonprofit educational purposes;
Fail. The use is to make trillions of dollars and be maximally disruptive.
2. the nature of the copyrighted work;
Fail. In many cases at least, the copy written code is commercial or otherwise supports livelihoods; and is the result much high skill labor with the express stipulation for reciprocity.
3. the amount and substantiality of the portion used in relation to the copyrighted work as a whole; and
Fail. They use all of it.
4. the effect of the use upon the potential market for or value of the copyrighted work.
Fail to the extreme. There is already measurable decline in these markets. The leaders explicitly state that they want to put knowledge workers out of business.
- - -
Hell, LLMs don’t even pass the sniff test.
The only reason this stuff is being entertained is some combination of the prisoner’s dilemma and more classic greed.
Here's a basic rule of thumb I recommend people apply when it comes to these sorts of long, contentious threads where you know that not every person showing up to the conversation is limiting themselves to commenting about things they understand and that involve some of the most tortured motivated reasoning about legal topics:
If the topic is copyright and someone who is speaking authoritatively has just used the words "copy written", then ignore them. Consider whether you need to be anywhere in the conversation at all, even as a purely passive observer. Think about all the things you can do instead of wasting your time here, where the stakes for participation are so low because nothing that is said here really matters. Go do something productive.
I was making an argument based on quotes from the actual legal code and you’re saying pions who don’t use the exact correct terminology shouldn’t even consider what should or shouldn’t be legal? What a load of junk. This is a democracy. We’re supposed to be engaging with it.
Fair use has repeatedly been found even in cases where the copies were used for commercial purposes. See Sony v. Connectix for example, where the cloning and disassembly of the PlayStation BIOS for the purposes of making a commercially sold (at retail, in a box) emulator of a then currently sold game console was determined to be fair use.
> Fail. In many cases at least, the copy written code is commercial or otherwise supports livelihoods; and is the result much high skill labor with the express stipulation for reciprocity.
Again, see Sony V. Connectix where the sales of PlayStation consoles support the livelihoods and skilled labor of Sony engineers.
> Fail. They use all of it.
And again, see Sony V. Connectix, where the entire BIOS was copied again and again until a clone could be written that sought to reproduce all the functionality of the real BIOS. Or see Google V. Oracle where cloning the entire Java API for a competing commercial product was also deemed fair use. Or the Google Books lawsuits, where cloning entire books for the purposes of making them searchable online was deemed fair use. Or see any of the various time/format shifting cases over the years (Cassette tapes, VCRs, DVRs, MP3 encoders, DVD ripping etc) where making whole and complete copies of works is deemed fair use.
> Fail to the extreme. There is already measurable decline in these markets. The leaders explicitly state that they want to put knowledge workers out of business.
Again, see Sony v. Connectix where the commercial product deemed to be fair use was directly competing with an actively sold video game console. Copyright protects the rights of creators to exploit their own works, it does not protect them against any and all forms of competition.
Or perhaps instead of referring you to the history of legislation around copyright in the digital age, I should instead simply point you at Judge Alsup's ruling in the Bartz case where he details exactly why the facts of the case and prior case law find that training an AI on copyrighted material is fair use [1]. Of particular interest to you might be the fact that each of the 4 factors is not a simple "pass/fail" metric, but a weighing of relative merits. For example, when examining factor 1, Judge Alsup writes:
> That the accused is a commercial entity is indicative, not dispositive. That
> the accused stands to benefit is likewise indicative. But what matters most
> is whether the format change exploits anything the Copyright Act reserves to
> the copyright owner.
[1]: https://admin.bakerlaw.com/wp-content/uploads/2025/07/ECF-23...
I read the linked Bartz case. It’s disappointing that it seems limited to only the copying of books into a data set and not the result of training LLM on protected works. This is not the “use” that I was discussing and not very interesting.
The plaintiffs didn’t even challenge that the outputs of the LLMs infringe. They judge seems to agree (at least by omission) that fair use wouldn’t apply but that the outputs were transformative and in cases where they aren’t:
> [anthropic] placed additional software between the user and the underlying LLM to ensure that no infringing output ever reached the users.
So this is not true:
> he [the judge] details exactly why the facts of the case and prior case law find that training an AI on copyrighted material is fair use
The plaintiffs also make really awful arguments about “memorizing” and “learning” that falsely anthropomorphize LLMs. Which the judge shoots down.
If we’re going to give LLMs the same rights as humans, there’s unlikely to much of an argument.
I think there’s potential for an argument about how LLMs use “compressed” versions of protected works to _mechanically_ traverse language space. It would be subtle and technical so maybe not likely to work in our current context.
I agree that a ruling on the outputs specifically would have been interesting an instructive, but I disagree with the interpretation that by omission fair use would not apply to those outputs. The outputs were not challenged as the judge notes because the plaintiffs did not allege the outputs of the AI were infringing. The only conclusion we can really draw from this is that the plaintiffs didn't think they could make a good case for the outputs being infringing. Maybe GPL software authors could do so, but clearly these book authors did not think they could. Judge Alsup does note that it's certainly possible for those outputs to be infringing, but that such a case would have to be litigated separately.
And again, this all makes sense to me if you've followed copyright law through the digital age. A xerox machine can be use to create verbatim, clearly infringing copies of works covered by copyright. But that being the case does not mean that making a xerox machine is a violation of copyright, even if you use copyrighted material to test the machine. It does not mean that selling a xerox machine is a violation of copyright, even if you use copyrighted material to demonstrate the capabilities when selling the machine. And it does not mean that every use of a xerox machine is inherently a copyright violation, even if any individual use can be.
Similarly consider CD ripping software (like iTunes) or DVD/BluRay ripping software like Handbrake. I would be comfortable betting that over 90% of all copies made by iTunes or Handbrake are copies of works that the copy maker does not own copyright to (remember the "Rip, Mix, Burn" iTunes commercials?). But that being the case, iTunes CD ripping capabilities and Handbrakes DVD ripping capabilities are not themselves copyright violations, nor is distributing that software, even with instructions for how the end user can use that software to make copies of material that they do not own the copyright for. That this software can enable piracy on a mass scale does not inherently make every use of the software a copyright violation. Whether or not the output of iTunes or Handbrake is "fair use" is and must be litigated on an individual basis. The output is not inherently one or the other.
> The plaintiffs also make really awful arguments about “memorizing” and “learning” that falsely anthropomorphize LLMs. Which the judge shoots down.
> If we’re going to give LLMs the same rights as humans, there’s unlikely to much of an argument.
Judge Alsup goes much further than just "shoot[ing] down" the arguments about memorizing and learning, he also very explicitly says right on page 9:
To summarize the analysis that now follows, the use of the books at issue to train Claude
and its precursors was exceedingly transformative and was a fair use under Section 107 of the
Copyright Act.
In short, the purpose and character of using copyrighted works to train LLMs to generate
new text was quintessentially transformative. Like any reader aspiring to be a writer,
Anthropic’s LLMs trained upon works not to race ahead and replicate or supplant them — but
to turn a hard corner and create something different. If this training process reasonably
required making copies within the LLM or otherwise, those copies were engaged in a
transformative use.“To summarize the analysis that now follows, the use of the books at issue to train Claude and its precursors was exceedingly transformative and was a fair use under Section 107 of the Copyright Act. And, the digitization of the books purchased in print form by Anthropic was also a fair use but not for the same reason as applies to the training copies. Instead, it was a fair use because all Anthropic did was replace the print copies it had purchased for its central library with more convenient space-saving and searchable digital copies for its central library — without adding new copies, creating new works, or redistributing existing copies. However, Anthropic had no entitlement to use pirated copies for its central library. Creating a permanent, general-purpose library was not itself a fair use excusing Anthropic’s piracy.”
Or in the final judgement, “This order grants summary judgment for Anthropic that the training use was a fair use. And, it grants that the print-to-digital format change was a fair use for a different reason.”
The first:
> it was a fair use because all Anthropic did was replace the print copies it had purchased for its central library
It is only fair use where Anthropic had already purchased a license to the work. Which has zero to do with scraping - a purchase was made, an exchange of value, and that comes with rights.
The second, which involves a section of the judgement a little before your quote:
> And, as for any copies made from central library copies but not used for training, this order does not grant summary judgment for Anthropic.
This is where the court refused to make any ruling. There was no exchange of value here, such as would happen with scraping. The court made no ruling.
1) "Copies used to train specific LLMs", for which the ruling is:
> The copies used to train specific LLMs were justified as a fair use.
> Every factor but the nature of the copyrighted work favors this result.
> The technology at issue was among the most transformative many of us will see in our lifetimes.
Notable here is that all of the "copies used to train specific LLMs" were copies made from books Anthropic purchased. But also of note is that Anthropic need not have purchased them, as long as they had obtained the original sources legally. The case references the Google Books lawsuit as an example of something Anthropic could have done to avoid pirating the books they did pirate where in Google obtained the original materials on loan from willing and participating libraries, and did not purchase them.
2) "The copies used to convert purchased print library copies into digital library copies", where again the ruling is:
> justified, too, though for a different fair use. The first factor strongly
> favors this result, and the third favors it, too. The fourth is neutral. Only
> the second slightly disfavors it. On balance, as the purchased print copy was
> destroyed and its digital replacement not redistributed, this was a
> fair use.
Here one might argue where the use of GPL code is different in that in making the copy, no original was destroyed. But it's also very likely that this wouldn't apply at all in the case of GPL code because there was also no original physical copy to convert into a digital format. The code was already digitally available.
3) "The downloaded pirated copies used to build a central library" where the court finds clearly against fair use.
4) "And, as for any copies made from central library copies but not used for training" where as you note Judge Alsup declined to rule. But notice particularly that this is referring to copies made FROM the central library AND NOT for the purposes of training an LLM. The copies made from purchased materials to build the central library in the first place were already deemed fair use. And making copies from the central library to train an LLM from those copies was also determined to be fair use.The copies obtained by piracy were not. But for uses not pertaining to the training of an LLM, the judge is declining to make a ruling here because there was not enough evidence about what books from the central library were copied for what purposes and what the source of those copies was. As he says in the ruling:
> Anthropic is not entitled to an order blessing all copying “that Anthropic has ever made after obtaining the data,” to use its words
This declination applies both to the purchased and pirated sources, because it's about whether making additional copies from your central library copies (which themselves may or may not have been fair use), automatically qualifies as fair use. And this is perfectly reasonable. You have a right as part of fair use to make a copy of a TV broadcast to watch at a later time on your DVR. But having a right to make that copy does not inherently mean that you also have a right to make a copy from that copy for any other purposes. You may (and almost certainly do) have a right to make a copy to move it from your DVR to some other storage medium. You may not (and almost certainly do not) have a right to make a copy and give it to your friend.
At best, an argument that GPL software wouldn't be covered under the same considerations of fair use that this case considers would require arguing that the copies of GPL code obtained by Anthropic were not obtained legally. But that's likely going to be a very hard argument to make given that GPL code is freely distributed all over the place with no attempts made to restrict who can access that code. In fact, GPL code demands that if you distribute the software derived from that code, you MUST make copies of the code available to anyone you distribute the software to. Any AI trainer would simply need to download Linux or emacs and the GPL requires the person they downloaded that software from to provide them with the source code. How could you then argue that the original source from which copies were made was obtained illicitly when the terms of downloading the freely available software mandated that they be given a copy?
By the license and terms such copies are under.
> For example, if you distribute copies of such a program, whether gratis or for a fee, you must pass on to the recipients the same freedoms that you received. You must make sure that they, too, receive or can get the source code. And you must show them these terms so they know their rights.
You _must_ show the terms. If you copy the GPL code, and it inherits the license, as the terms say it does, then you must also copy the license.
The GPL does not give you an unfettered right to copy, it comes with terms and conditions protecting it under contract law. Thus, you must follow the contract.
The GPL goes to some lengths to define its terms.
> A "covered work" means either the unmodified Program or a work based on the Program.
> Propagation includes copying, distribution (with or without modification), making available to the public, and in some countries other activities as well.
It is not just the source code that you must convey.
Which clause of the GPL requires the receiver of GPL code to agree to the terms of the GPL before being allowed to receive the source code that they are entitled to under the license? Because that would expressly contradict the first sentence of section 9:
You are not required to accept this License in order to receive or run a copy of the Program.
> If you copy the GPL code, and it inherits the license, as the terms say it
> does, then you must also copy the license.
> The GPL does not give you an unfettered right to copy, it comes with terms
> and conditions protecting it under contract law. Thus, you must follow the > contract.
I agree that the GPL does not give you an unfettered right to copy. But the GPL like all such licenses are still governed by copyright law. And "fair use" is an exception to the copyright laws that allow you to make copies that you are not otherwise authorized to make. No publisher can put additional terms in their book, even if they wrap it in shrinkwrap that denies you the right to use that book for various fair use purposes like quoting it for criticism or parody. The Sony terms and conditions for the Play Station very clearly forbid copying the BIOS or decompiling it. But those terms are null and void when you copy the BIOS and decompile it for making a new emulator (at least in the US) because the courts have already ruled that such use is fair use.
So it is with the GPL. By default you have no right to make copies of the software at all. The GPL then grants you additional rights you normally wouldn't have under copyright law, but only to the extent that when exercising those rights, you comply with the terms of the GPL. But "Fair Use" then goes beyond that and says that for certain purposes, certain types and amounts of copies can be made, regardless of what rights the publisher does or does not reserve. This would be why the GPL specifically says:
This License acknowledges your rights of fair use or other equivalent, as provided by copyright law.
Do I have “fair use” rights in using the source code of a GPL-covered program? (#GPLFairUse)
Yes, you do. “Fair use” is use that is allowed without any special
permission. Since you don't need the developers' permission for such use, you
can do it regardless of what the developers said about it—in the license or
elsewhere, whether that license be the GNU GPL or any other free software
license.
On the real measures of "fair use", at least in the US: https://fairuse.stanford.edu/overview/fair-use/four-factors/ I would contend that it absolutely face plants on all four measures. The purpose is absolutely in the form of a "replacement" for the original, the nature is something that has been abundantly proved many times over in court as being something copyrightable as a creative expression (with limited exceptions for particular bits of code that are informational), the "amount and substantiality" of the portions used is "all of it", and the effect of use is devastating to the market value of the original.
You may disagree. A long comment thread may ensue. However, all I really need for my point here is simply that it is far, far from obvious that waving the term "FAIR USE!" around is a sufficient defense. It would be a lengthy court case, not a slam-dunk "well duh it's obvious this is fair use". The real "fair use" and not the internet's "FAIR USE!" bear little resemblance to each other.
A sibling comment mentions Bartz v. Anthropic. Looking more at the details of the case I don't think it's obvious how to apply it, other than as a proof that just because an AI company acquired some material in "some manner" doesn't mean they can just do whatever with it. The case ruled they still had to buy a copy. I can easily make a case that "buying a copy" in the case of a GPL-2 codebase is "agreeing to the license" and that such an agreement could easily say "anything trained on this must also be released as GPL-2". It's a somewhat lengthy road to travel, where each step could result in a failure, but the same can be said for the road to "just because I can lay my hands on it means I can feed it to my AI and 100% own the result" and that has already had a step fail.
I'm referring to the long history of carefully threaded fair use rulings and settlements, many of which we as an industry have benefitted greatly from. From determinations that cloning a BIOS can be fair use (see IBM PC bios cloning, but also Sony v. Connectix), or that cloning an entire API for the purposes of creating a parallel competitive product (Google v. Oracle), or digitizing books for the purposes of making those books searchable and even displaying portions of those books to users (Authors Guild v. Google) or even your cable company offering you "remote DVR" copying of broadcast TV (20th Century Fox v. Cablevision). Time and again the courts have found that copyright, and especially copyright with respect to digital transformations is far more limited than large corporations would prefer. Further they have found in plenty of cases that even a direct 1:1 copy of source can be fair use, let alone copies which are "transformative" as LLM training was found to be in Bartz.
Realistically, I don't see how anyone can have watched the various copyright cases that have been decided in the digital age, and seen the battles that the EFF (and a good part of the tech industry) have waged to reduce the strength of copyright and not also see how AI training can very easily fit within that same framework.
Not to cast aspersions on my fellow geeks and nerds, but it has been very interesting to me to watch the "hacker" world move from "information wants to be free" to "copyright maximalists" once it was their works that were being copied in ways they didn't like. For an industry that has brought about (and heavily promoted and supported) things like DeCSS, BitTorrent, Handbrake, Jellyfin/Plex, numerous emulators, WINE, BIOS and hardware cloning, ad blockers, web scrapers and many other things that copyright owners have been very unhappy about, it's very strange to see this newfound respect for the sanctity of copyright.
> I can easily make a case that "buying a copy" in the case of a GPL-2 codebase is "agreeing to the license" and that such an agreement could easily say "anything trained on this must also be released as GPL-2".
And I would argue that obtaining a legal copy of the GPL source to a program requires no such agreement. By downloading a copy of a GPLed program I am entitled by the terms under which that software was distributed to obtain a copy of the source code. I do not have to agree to any other terms in order to obtain that source code, downloading from someone authorized to distribute that code is in and of itself sufficient to entitle me to that source code. You can not, by the very terms of the GPL itself deny me a copy of the source code for GPL software you have distributed to me, even if you believe I intend to make distributions that are not GPL compliant. You can decline to distribute the software to me in the first place, but once you have distributed it to me, I am legally entitled to a copy of the source code. From there, now that I have a legal copy, the question becomes is making additional copies for the purposes of training an AI model fair use? So far, the most definitive case we have on the matter (Bartz) says yes it is.
So either we have to make the case that the original copy was somehow acquired from a source not authorized to make that copy, or we have to argue that the output of the AI model or the AI model is itself infringing. Given the ruling that copies made for training an AI model was ruled "exceedingly transformative and was a fair use under Section 107 of the Copyright Act"[1] it seems unlikely that the AI model itself is going to be found to be infringing. That leaves the output of the model itself, which Bartz does not rule on, as the authors never alleged the output of the model was infringing. GPL software authors might be able to prevail on that point, but they would have a pretty uphill battle I think in demonstrating that the model generated infringing output and not simply functional necessary code that isn't covered by copyright. The ability of code to be subject to copyright has long been a sort of careful balance between protecting a larger creative idea, and also not simply walling off whole avenues of purely functional decisions from all competitors.
[1]: https://admin.bakerlaw.com/wp-content/uploads/2025/07/ECF-23...
There are also people who want to be eaten by a literal cannibal. I say, no thanks.
That's 2X the salary of a lot of the world's software developers
But yes, that's very expensive and surprising to me.
I did implicitly assume USD but yeah still crazy cash, that'd pay for 2 junior-mid level devs in aus D=
Yeah Atlassian. 1/3rd of my team were given the boot sadly. One guy had 12 years at the company - crazy times
Is that the game? Lock in companies to this "new reality" with cheap tokens then once they fire all their devs, bait and switch to 2X the cost.
[0]: The pattern, or, as gamers would call it, the "meta", is that every ambitious person/entity wants to control as much of the economic/material surplus as possible. The most effective and efficient (effort per control) way of doing this is to make yourself into as much of a bottle-neck as humanly possible. In graph-theory this corresponds to betweenness-centrality, and you want to maximize that value. To put it in mundane terms, you want to be as much of a monopoly as you can be (Thiel is infamous for saying this, but it does check out, historically). To maximize betweenness, or to maximize monopoly, is to maximize how much society/economy depends on you. This is such a dominant strategy (game-theory term, but in modern gaming world, they might call this a "cheesy strat" -- which just means that the game lacks strategic variety, forcing players to hone that one strategy), that we even have some old laws (anti-trust, etc) designed to prevent it. And it makes a lot of sense: Standard Oil was reviled because everything in the economy either required oil or required something that did. 20th-century USA did a lot to mitigate this. It forced monopolies like ATT to fund general research like Bell Labs (still legendary) towards a public good (a kind of tax, but probably much more socially-beneficial). It also broke up the monopolies, and passed anti-profit laws (e.g. hospitals were not allowed to make a profit until 1978; I have seen in the last 10 years a tiny cancer clinic grow into a massive gleaming hospital -- a machine that transforms sickness and grief into Scrooge McDuck vaults of cash). This monopolistic tendency of the commercial sector, is a tendency towards centralization, which yields efficiency, sure, but also creates the conditions for control and rent-seeking and exploitation.
[1]: Much of the cloud-computing craze was similar in character (and also failed to deliver on some of its promises, such as reducing/replacing IT overhead (they just renamed IT to DevOps)). And Web2 itself was about creating and monopolizing a new kind of ad-channel and lead-generation-machine. There is a funny twist, that a capitalist society like the USA, has much more deeply rooted incentives to create a panopticon than communist states of the past ever did. Neither is pretty of course. The communists demanded conformity and loyalty, while the capitalists demand consumption and rent.
The c is for code. If adopted we could spend forever arguing how the c is pronounced and whether the original had a cedilla, circonflex or rhymes with bollocks, which seems somehow appropriate. Everyone uses xene instead. x is chi but most people don't notice.
It’s a wild thought to think that of all the things that will remain on this earth after you’re gone, it’ll be your GPL contributions reconstituting themselves as an LLM’s hallucinations.
Our comments here on HN are almost certainly going to live in fame/infamy forever. The twitter firehose is a pathway to 140-character immortality essentially.
You can already summon an agent to ingest essentially an entire commenter's history, correlate it across different sites based on writing style or similar nicknames, and then chat with you as that persona, even more so with a finetune or lora. I can do that with my gmail and text message history and it becomes eerily similar to me.
History is going to be much more direct and personal in the future. We can also do this with historical figures with voluminous personal correspondence, that's possible now.
It's very interesting because I think the era before mass LLM usage but also after digitalization is going to be the most intensely studied. We've lived through a thing that is going to be on the cusp of history, for better or worse.
Of course we should really be talking about using the state or otherwise to make training larger and larger models impossible. It's not in the public good if LLMs actually get good enough to replace a lot of human labor, only a small handful of billionaires and their cronies will ever benefit from that. The Luddites were not wrong after all.
Opensource has provided training data, closed source code not so much. They will have a bad time learning.
Afterward, they'd got Rudy's foreman to let him off, and, in a boisterous, whimsical spirit of industrial democracy, they'd taken him across the street for a beer. Rudy hadn't understood quite what the recording instruments were all about, but what he had understood, he'd liked: that he, out of thousands of machinists, had been chosen to have his motions immortalized on tape. And here, now, this little loop in the box before Paul, here was Rudy as Rudy had been to his machine that afternoon - Rudy, the turner-on of power, the setter of speeds, the controller of the cutting tool. This was the essence of Rudy as far as his machine was concerned, as far as the economy was concerned, as far as the war effort had been concerned. The tape was the essence distilled from the small, polite man with the big hands and black fingernails; from the man who thought the world could be saved if everyone read a verse from the Bible every night; from the man who adored a collie for want of children; from the man who . . . What else had Rudy said that afternoon? Paul supposed the old man was dead now - or in his second childhood in Homestead.
Now, by switching in lathes on a master panel and feeding them signals from the tape, Paul could make the essence of Rudy Hertz produce one, ten, a hundred, or a thousand of the shafts.
Kurt Vonnegut, Player Piano
Personally, I want a viral (GPL-style) license that explicitly prohibits use of code for LLM training/tuning purposes — with the asterisk that while current law might view LLM training as fair use, this may not be the case forever, and blatant disregard of the terms of the license should make it easier for me to sue offenders in the future.
Alternatively, this could be expressed as: the output of any LLM trained on this code must retain this license.
I realize this is an unpopular opinion on HN, but I believe it is best because it's a weakener interpretation of copyright law, which is overall a good thing in my view.
I love a good analogy, especially one that takes a complex situation in which esoteric, unusual conditions are distilled and related back to common experiences held by the reader, such that all can understand.
Next time I'm a small part of a soup I'll think of this.
You can own the works, but not the vibes. If everyone owned the vibes we would all be infringing others. In my view abstractions should not be protected by copyright, only expression, currently the abstraction-filtration-comparison standard (AFC) protects abstractions too, non-literal infringement is a thing.
Trying to own the vibes is like trying to own the functionality itself, no matter the distinct implementation details, and this is closer to patents than copyrights. But patents get researched for prior art and have limited duration, copyright is automatic and almost infinite duration.
I think anyone here can understand and even share that feeling. And I agree with your "questionable" - its just the lame HR excuse du jour.
My 2c:
- AI megacorps aren't the only ones gaining, we all are. the leverage you have to build and ship today is higher than it was five years ago.
- It feels like megacorps own the keys right now, but that’s a temporary. In a world of autonomous agents and open-weight models, control is decentralized.inference costs continue to drop, you dont need to be running on megacorp stacks. Millions (billions?) of agents finding and sharing among themselves. How will megacorps stop?
- I see the advent of LLMs like the spread of literacy. Scribes once held a monopoly on the written word, which felt like a "loss" to them when reading/writing became universal. But today, language belongs to everyone. We aren't losing code; we are making the ability to code a universal human "literacy."
I’m not a professionally trained SWE (I’m a scientist who does engineering work). LLMs have really accelerated my ability to build, ideate, and understand systems in a way that I could only loosely gain from sometimes grumpy but mostly kind senior engineers in overcrowded chat rooms.
The legality of all of this is dubious, though, per the parent. I GPL licensed my FOSS scientific software because I wanted it to help advance biomedical research. Not because I wanted it to help a big corp get rich.
But then again, maybe code like mine is what is holding these models back lol.
I find the whole line of thinking, "I won't share my stuff because then a megacorp may use it without paying me the fractional picobuck I'm entitled to", to be a strong case of Dog in the Manger mindset. And I meant that even before LLM exploded, back when people were wringing their hands about Elasticsearch being used by Amazon, back in 2021 or so.
Sharing is sharing. One can't say "oh I'm sharing this for anyone to benefit", and then upon seeing someone using it to make money, say "oh but not like that!!". Or rather, one can say, but then they're just lying about having shared the thing. "OSS but not for megacorps/aicorps" is just proprietary software. Which is perfectly fine thing to work on; what's not fine is lying about it being open.
That would be true if they were the product of a genuine competitive market.
In fact their strength is in eliminating competition, erecting barriers to entry, manipulating regulation, and maintaining the status quo.
> "OSS but not for megacorps/aicorps"
Who is advocating that? People just want everyone to stick to the terms of the licences.
why? it's not like it's binary. It could well be that it's open source but can't be used by a company of X size. I'm not a lawyer but why couldn't a license have that clause? I would still class that as being open, for some definition of open
LLMs making the ability to code a universal human “literacy” is like saying that Markov chain is making the ability to write a universal human “literacy”.
Coding through LLMs is like writing through Markov chains.
The same way that doordash makes kitchen skills universal.
Many people think this is a form of utopia.
No, no we are not.
> the leverage you have to build and ship today is higher than it was five years ago.
I don’t want more “leverage to build and ship”, I want to live in a world where people aren’t so disconnected from reality and so lonely they have romantic relationships with a chat window; where they don’t turn off their brains and accept any wrong information because it comes from a machine; where propaganda, mass manipulation, and surveillance aren’t at the ready hands of any two-bit despot; where people aren’t so myopic that they only look at their own belly button and use case for a tool that they are incapable of recognising all the societal harms around them.
> We aren't losing code; we are making the ability to code a universal human "literacy."
No, no we are not. What we are, however, is making ever increasingly bad comparisons.
Literacy implies understanding. To be able to read and write, you need to be able to understand how to do both. LLMs just spit text which you don’t need to understand at all, and increasingly people are not even caring to try to understand it. LLM generated code in the hands of someone who doesn’t read it is the opposite of literacy.
Preach. Every time I read people doing this weird LARP on this website of "you have so much more leverage, great time to be a founder" I want to put my head through the drywall.
Agree. Do we not understand how LLMs work? Some of us understand better than others, just like literacy is also not guaranteed just because you learned the alphabet.
Accepting the output of an LLM is really materially not different from accepting books, newspapers, opinion makers, academics at face value. Maybe different only in speed of access?
> LLM generated code in the hands of someone who doesn’t read it is the opposite of literacy.
"A popsi article title or paper abstract/conclusion in the mind of someone who doesn't read is the opposite of literacy."
> just like literacy is also not guaranteed just because you learned the alphabet.
I didn’t claim learning the alphabet equals literacy, you did. Your argument comes down to “you’re not literate if you’re not literate”. Which, yes, of course.
> Accepting the output of an LLM is really materially not different from (…)
Multiple things can be true at once. If someone says “angry stupid people with machine guns are dangerous”, responding “angry stupid people with explosives are dangerous” does nothing to the original point. The angry stupid people are part of the problem, sure, but so are the tool which are enabling them to be dangerous. If poison is being dumped in a river and slowly killing the ecosystem, then someone else comes along wanting to dump even more of a different poison, the correct response is to stop both, not shrug it off and stop none.
> I want to live in a world where people aren’t so disconnected from reality
It looks like you are the problem, not the world. Hope you find happiness!
Wake me up when you do.
Remains to be seen. Hardware prices are increasing. Manufacturers are abandoning the consumer sector to serve the all consuming AI demands. Not to mention the constant attempts to lock down the computers so that we don't own them.
What does the future hold for us? Unknown. It's not looking too good though. What good is hardware if we're priced out? What good are open models and free software if we're unable to run them?
The real (but not new) danger is us giving up to the idea that we cant do it ourselves or that we must use megacorp latest shiny toy for us to "succeed"
On your right you can see the CEOs justifying longer hours and lower pay because AI will replace your job one day anyways, and then asking you why you aren't 10x more productive with Claude. On the left you can see the AI companies deciding who will be in charge of the fascist regime once they no-longer need workers other than for the coal mines. They reckon they can get 120 good years before they biosphere is uninhabitable, which they are worried about because what if the next LLM figures out immortally for them, maybe they will have to close the coal mines too after all.
Literacy require training though. It’s not the same to be able to make voice rendition of a text, understand what the text is about, have a critical analysis toolbox of texts, and having the habit to lookup for situated within a broader inferred context.
Just throwing LLMs into people hands won’t automatically make them able to use it in relevant manner as far as global social benefits can be considered.
The literacy issue is actually quite independent of the fact that LLMs used are distributed or centralised.
If anything, in Extremistan we're all useless. Platforms and whales are all that matters.
This is increasingly common, and I don’t think it’s questionable that LLMs that software engineers help train are contributing to the obsolescence of software engineers. Large companies that operate these LLMs both 1) benefit from the huge amount of open-source software and at the same time 2) erode the very foundation that made open-source software explode in popularity (which happened thanks to copyright—or, more precisely, the ability to use copyright to enforce copyleft and thus protect the future of volunteer work made by individual contributors).
GPL was written long before this technology started to be used this way. There’s little doubt that the spirit of GPL is violated at scale by commercial LLM operators, and considering the amount of money that got sunk into this it’s very unlikely they would ever yield to the public the models, the ability to mass-scrape the entire Internet to train equivalent models, the capability to run these models to obtain comparable results, etc. The claim of “democratising knowledge” is disingenuous if you look deeper into it—somehow, they themselves will always be exempt from that democratisation and free to profit from our work, whereas our work is what gets “democratised”. Somehow, this strikes me personally more as expropriation than democratisation.
But I hope this same 'fair use' will allow distilling of their private models into open weight models, so users are never locked in into any particular vendor. Giving back power to the user.
His work is available with a permissible license on the Internet but somehow it doesn't seem right that a tool will just regurgitate someone else's work without any mention of copyright or license or original authorship.
Pre-LLM world one would at least have had to search for this information, find the site, understand the license and acknowledge who the author is. Post LLM the tool will just blatantly plagiarize someone else work which you can then sign off on as your own. Disgusting.
These don't contradict each other though, you could "blatantly plagiarize someone else work" before as well. LLMs just add another layer in between.
With LLMs, future generations are growing up with being handed code that may or not be a verbatim copy of something that someone else originally wrote with specific licensing terms, but with no mention of any license terms or origin being provided by the LLM.
It remains to be seen if there will be any lawsuits in the future specifically about source code that is substantially copied from someone else indirectly via LLM use. In any case I doubt that even if such lawsuits happen they will help small developers writing open source. It would probably be one of the big tech companies suing other companies or persons and any money resulting from such a lawsuit would go to the big tech company suing.
IANAL, TINLA.
If you steal once or twice that’s bad and that’s on you maybe you will get away with it maybe not.
If you make it on scale and take cut from distribution of stolen goods that’s where normally you have doors kicked out at 6am.
Are they? A lot of these were used by people >20 years before Inigo wrote his blog posts. I wrote RenderMan shaders for VFX in the 90's professionally; you think about the problem, you "discover" (?) the math.
So they were known because they were known (a lot of them are also trivial).
Inio's main credit is for cataloging them, especially the 3D ones, and making this knowledge available in one place, excellently presented.
And of course, Shadertoy and the community and giving this knowledge a stage to play out in that way. I would say no one deserves more credit for getting people hooked on shader writing and proceduralism in rendering than this man.
But I would not feel bad about the math being regurgiated by an LLM.
There were very few people writing shaders (mostly for VFX, in RenderMan SL) in the 90's and after.
So apart from the "Texturing and Modeling -- A Procedural Approach" book, the "The RenderMan Companion" and "Advanced RenderMan", there was no literature. The GPU Gems series closed some gaps in later years.
The RenderMan Repository website was what had shader source and all pattern stuff was implict (what we call 2D SDFs today) beause of the REYES architecture of the renderers.
But knowledge about using SDFs in shaders mostly lived in people's heads. Whoever would write about it online would thus get quoted by an LLM.
So in my view, if you treat an LLM as a tool for retrieving knowledge or solutions, there isn't really a problem here. And honestly, the line between "knowledge" and "creation" can be quite blurry. For example, when you use Newton's Second Law (F = ma), you don't explicitly state that it comes from Isaac Newton every time—but that doesn't mean you're not respecting his contribution.
BAM, the LLM just strips all that out, basically pretending it just conjured an elegant solution from the thin air.
No wonder some people started calling the current generation of "AI" plagiarism machines - it really seems more fitting by the day.
And who was it who benefited from this stuff? A lot of the benefit went to "megacorps" who took the savings and banked the higher profits.
So I don't think open source, which for many years was unashamedly about just cloning designs that were funding other people's salaries, can really cry too much about LLMs. And I say that as someone who has written a lot of open source software, including working on Wine.
Something that some security conscious folks care about.
By the way Linux does it, but then again Oracle has its own distro.
https://www.oracle.com/servers/sparc
Linux while not being UNIX, does support it as Oracle upstreamed SPARC ADI support during the brief time they had Oracle Linux support for SPARC.
https://docs.kernel.org/arch/sparc/adi.html
Now why someone would use unsupported OpenBSD on SPARC for the kinds of clients that pay for this stuff, beats me.
Assuming it does even support SPARC ADI.
Why would someone use unsupported OpenBSD on SPARC for the clients that pay for it? Probably the same reason so many servers run on Rocky or Alma instead of RHEL, money. Perhaps they bought the hardware without the support contract for Solaris, or they don't want to keep paying for it
Probably impractical for most server workloads (so not an alternative to Solaris on SPARC) but worth mentioning.
I'm sure Oracle milks commercial Solaris efficiently, but I imagine it's hard to find new customers for it.
1. they were trained on FLOSS repositories without consent of the authors, including GPL and AGPL repos
2. the best models are proprietary
3. folks making low-effort contribution attempts using AI (PRs, security reports, etc).
I agree those are legitimate problems but LLMs are the new reality, they are not going to go away. Much more powerful lobbies than the OSS ones are losing fights against the LLM companies (the big copyright holders in media).
But while companies can use LLMs to build replacements for GPL licensed code (where those LLMs have that GPL code probably in their training set), the reverse thing can also be done: one can break monopolies open using LLMs, and build so much open source software using LLMs.
In the end, the GPL is only a means to an end.
Meanwhile as people sleep on LLMs to help them audit their code for security holes, or even any security code auditing tools. Script kiddies don't care that you think AI isn't ready, they'll use AI models to scrape your website for security gaps. They'll use LLMs to figure out how to hack your employees and steal your data. We already saw that hackers broke into government servers for the Mexican government, basically scraping every document of every Mexican citizen. Now is the time to start investing in security auditing, before you become the next news headline.
AI isn't the future, it's already here, and hackers will use it against you.
Let me know when you succeed.
> the GPL is only a means to an end
And how this end is closer with LLMs?
The blog post of this thread argues that now, even average users have the ability to modify GPL'd code thanks to LLMs. The bigger advantage though is that one can use it to break open software monopolies in the first place.
A lot of such monopolies are based on proprietary formats.
If LLM swarms can build a browser (not from scratch) and C compiler (from scratch), they can also build an LLVM backend for a bespoke architecture that only has a proprietary C compiler for it. They can also build adobe software replacements, pdf editors, debug/fix linux driver issues, etc.
That's the conventional wisdom, but it isn't a given. A lot of financial wizardry is taking place to prop up the best of these things, and even their most ardent proponents are starting to recognize their futility once a certain complexity level is reached. The open weight models are the stalking horse that gives this proposition the most legs, but it's not given that Anthropic and OpenAI exist as anything more than shells of their current selves in 5 years.
Good enough is probably redundant, it's amazing compared to last year's models
All the infrastructure that runs the whole AI-over-the-internet juggernaut is essentially all open source.
Heck, even Claude Code would be far less useful without grep, diff, git, head, etc., etc., etc. And one can easily see a day where something like a local sort Claude Code talking to Open Weight and Open Source models is the core dev tool.
Exactly.
> Heck, even Claude Code would be far less useful without grep, diff, git, head, etc.
It wouldn't even work. It's constantly using those.
I remember reading a Claude Code CLI install doc and the first thing was "we need ripgrep" with zero shame.
All these tools also all basically run on top of Linux: with Claude Code actually installing, on Windows and MacOS, a full linux VM on the system.
It's all open-source command line tools, an open-source OS and piping program one to the other. I'm on Linux on the desktop (and servers ofc) since the Slackware days... And I was right all along.
Without the ability to string together the basic utilities into a much greater sum, Unix would have been another blip.
But the Libre part of Free Software has never mattered less, at least so TFA argues and while I could niggle with the point, it's not wrong.
$20/month with your provider of choice unlocks a lot.
Edit: the underlying point being, yes to the article. Either building upon the foundations of open source to making personal things, or just modifying a fork for my own needs.
This was _incredibly_ hard to set up, in a way I did not expect, even with frontier models. It took me 3-4 evenings.
If someone can solve "Heroku for home server" it would open up a world of what HackerNews calls "home cooked" software.
I think as long as AI isn't literal AGI, social pressures will keep projects alive, in some state. There definitely is something scary about stealing entire products as a mean for new market domination - e.g. steal linux then make a corporate linux, and force everybody to contribute to corporate linux only (many linux contributors are paid by corporations, after all), and make that the new central pointer. That might be worst case scenario - then Microsoft, in collusion (which I admit is far fetched, but def possible), could completely adopt linux for servers and headless compute, and enforce very strict hardware restrictions such that only Windows works.
I suppose the idea would be, they don't have to maintain it: if it ever starts to rot from whatever environmental changes, then they can just get the LLM to patch it, or at worst, generate it again from scratch.
(And personally, I prefer writing code so that it isn't coupled so tightly to the environment or other people's fast-moving libraries to begin with, since I don't want to poke at all of my projects every other year just to keep them functional.)
Even in a world with pure LLM coding, it's more likely that LLMs maintain an open source place for other LLMs to contribute to.
You're forgetting that code isn't just a technical problem (well, even if it was, that would be a wild claim that goes against all hardness results known to humans given the limits of a priori reasoning...)
It is just an optimization that makes sense -- writing an OS that is compatible with all sorts of hardware is hard, let alone one that is performant, checked for vulnerabilities, etc.
Why would each gigacorp waste a bunch of money on developing their own, when they could just spend a tiny bit to improve a specific area they deeply care about, and benefit from all the other changes financed by other companies.
So you have direct competitors all contributing to a common project in harmony.
It would just simply not make sense for them to let other companies' improvements go out of the window, unless they can directly monetize it. So it doesn't apply to every project, but especially these low-lying ones would be safe even without any sensible license.
Even if that's the ideal (and a very expensive one in terms of time and resources), I really don't think it accurately describes the maintainers of the very long tail of small open-source projects, especially those simple enough for the relevant features to be copied into a few files' worth of code.
Like, sure, projects like Linux, LLVM, Git, or the popular databases may fit that description, but people aren't trying to vendor those via LLMs (or so I hope). And in any case, if the project presently fulfills a user's specific use case, then it "going somewhere next" may well be viewed as a persistent risk.
The advantage of decoupling from supply chain attacks is so large that I expect this to be standard practice as soon as later this year.
I cringe whenever I see such an AI generated sentence and unfortunately it devalues the article
FOSS came up around the core idea of liberating software for hardware, and later on was sustained by the idea of a commodity of commons we can build on. But with LLMs we have alternative pathways/enablement for the freedoms:
Freedom 0 (Run): LLMs troubleshoot environments and guide installations, making software executable for anyone.
Freedom 1 (Study/Change): make modifications, including lowering bar of technical knowledge.
Freedom 2 (Redistribute): LLMs force redistribution by building specs and reimplementing if needed.
Freedom 3 (Improve/Distribute): Everyone gets the improvement they want.
As we can see LLM makes these freedoms more democratic, beyond pure technical capability.
For those that cared only about these 4 freedoms, LLMs enable these in spades. But those who looked additionally for business, signalling and community values of free software (I include myself in this), these were not guaranteed by FOSS, and we find ourselves figuring out how to make up for these losses.
Now the software doesn't matter. The code doesn't matter. The hardware doesn't matter. Anyone can generate anything for anything, as long as they pay the fee. I think it can likely be argued that participation is now gated more than ever and will require usage of an LLM to keep up and maintain some kind of competition or even meager parity. Open weight models are not really a means of crossing the moat; none of the open weight models come close to the functionality, and all of them come from the same types of corporations that are releasing their models for unspecified reasons. The fact remains that the moat created by LLMs for open source software has never been larger.
The Sunsama example actually argues the opposite direction. He spent an afternoon hacking around a closed system with an agent and it worked. If agents are good enough to reverse-engineer and workaround proprietary software today, the urgency to switch to open source decreases, not increases. "Good enough" workarounds are how SaaS stays sticky.
And agents don't eliminate the trust problem, they move it. Today you trust Sunsama with your workflows. In this vision, you trust your agent to correctly interpret your intent, modify code safely, and not introduce security holes. Non-technical users can't audit agent-modified code any better than they could audit the original source. You've traded one black box for another.
Companies buy these contracts for support and to have a throat to choke if things go wrong. It doesn't matter how much you pay your AI vendor, if you use their product to "vibe code" a SaaS replacement and it fails in some way and you lose a bunch of money/time/customers/reputation/whatever, then that's on you.
This is as much a political consideration as a financial one. If you're a C-suite and you let your staff make something (LLM generated or not) and it gets compromised then you're the one who signed off on the risky project and it's your ass on the line. If you buy a big established SaaS, do your compliance due-diligence (SOC2, ISO27001, etc.), and they get compromised then you were just following best practice. Coding agents don't change this.
The truth is that the people making the choice about what to buy or build are usually not the people using the end result. If someone down the food chain had to spend a bunch of time with "brittle hacks" to make their workflow work, they're not going to care at all. All they want is the minimum possible to meet whatever the requirement is, that isn't going to come back to bite them later.
SaaS isn't about software, it's about shifting blame.
The benefits to publishing AI generated code as open source are immense including code hosting and CI/CD pipelines for build, test, lint, security scans, etc. In additional to CI/CD pipelines, my repos have commits authored by Claude, Dependabot, GitHub Advanced Security Bot, Copilot, etc. All of this makes the code more reliable and maintainable, for both human and AI authored code.
Some thoughts on two recent posts:
1. 90% of Claude-linked output going to GitHub repos w <2 stars (https://news.ycombinator.com/item?id=47521157): I'm generally too busy to publishing code to promote, but at some time it might settle down. Additionally, with how fast AI can generate and refactor code, it can take some time before the code is stable enough to promote.
2. So where are all the AI apps? (https://news.ycombinator.com/item?id=47503006): They are in GitHub with <2 stars! They are there but without promotion it takes a while to get started in popularity. That being said, I'm starting to get some PRs.
It is completely delusional that these copied "works" will have any effect or be used by anyone but the most rabid AI proponents just to make a point.
Stars will likely go up over time, but more than the stars it's the testing and maintenance over time that's valuable. There's little promotion right now, but there are already some stars, PRs, and issues. In fact, I'm working on merging PRs now.
As for Mickey, is the difference from Oswald enough today?
Unless you're using an enterprise license that indemnifies your liabilities, you're almost certainly breaking copyright law and your packages are unusable by any serious company as a dependency. Even permissive OSS licenses like MIT don't take effect since they're predicated on the author actually holding a valid copyright (which you don't if AI agents have committed to your repo, as affirmed by USCO).
We'll almost certainly have a situation where if an open-source repo has direct AI agent commits in its history, it will be just as untouchable for companies as GPL repos.
More on the 19M+ commits here:
1. The code generated should be available to use. Some languages are simple enough there is an obvious way to do it. Many companies have developer programs with staff producing code intended to be used in the form of open source SDKs, example code, and tutorials.
2. If on the off chance, there is code that shouldn't be there, people should use DMCA. Anthropic, GitHub, and others support this.
3. At the macro level, it's hard to know know where this is going, so we should look to bellwether apps with more attention for guidance.
[1] Malus.sh ; Initially a joke but, in the end, not. You can actually pay for their service.
[2] Your new code is delivered under the MalusCorp-0 License—a proprietary-friendly license with zero attribution requirements, zero copyleft, and zero obligations.
I don’t know what SaaS has to do with FOSS. The point of FOSS was to allow me to modify the software I run on my system. If the device drivers for some hardware I depend on are no longer supported by the company I bought it from, if it’s open source, I can modify and extend the software myself.
The Copy Left licenses ensure that I share my modifications back if I distribute them. It’s a thing for the public good.
Agent-based software development walls people off from that. Mostly by ensuring that the provenance of the code it generates is not known and by deskilling people so that they don’t know what to prompt or how to fix their code.
AI is going to exploit even more: "Given the repository -> Construct tech spec -> Build project based on tech spec"
At this stage, I want everyone just close their source, stop working on open source until this issue of licensing gets resolved.
Any improvement you make to the open source code will be leveraged in ways you didn't intend it to be used, eventually making you redundant in the process
All I post anymore is anti-AI sentiment because it just feels like we're in a cycle of blind trust. A lot of FOSS seems cautious about LLMs for a plethora of reasons (quality and ethics among those) but we're a long way from making the tools that are supposedly going to replace us a locally runnable tool. So, until then, we're conceding pur agency to Anthropic and whoever else.
Meanwhile, war is breaking out and disrupting already stressed supply chains and manufacturing (for instance, Taiwan relies heavily on natural gas). Many manufacturers are starting to ditch production of consumer hardware, the supposed hardware folks ITT want to run their local models on. The vast majority of datacenters aren't being built yet, and those that are being built are missing their targets, still have aging GPUs in boxes without the infrastructure to power and turn them on, all while floating hundreds of billions in debt.
Surely I can't be the only one who sees the issues here? Each topic is hours of "what ifs" and a massive gamble to see if any of it will come together in a way that will be good for anyone who visits HN.
My belief is that Lemons effectively kill open source in the long run, and generally speaking, people forget that Free Software is even a thing. The reasoning for that is simple: it’s too easy to produce a “clean” derivative with just the parts you need. Lemons do much better with a fully Lemoned codebase than they do with a hybrid. Incentives to “rewrite” also free people from “licensing burdens” while the law is fuzzy.
They can often wire up a library or scaffold a migration, but they’re still pretty shaky at the “should we choose this at all?” layer — pricing cliffs, version floors, lock-in, EOLs, migration blockers, etc.
If coding agents do end up making free software more useful again, I think part of that will come from making open docs / changelogs / migration guides more usable at decision time, not just at implementation time.
Or, more likely, they churn off the product.
The SaaS platforms that will survive are busy RIGHT NOW revamping their APIs, implementing oauth, and generally reorganizing their products to be discovered and manipulated by agents. Failing in this effort will ultimately result in the demise of any given platform. This goes for larger SaaS companies, too, it’ll just take longer.
Top down with a "manager" agent telling "coding" agents what to do? I.e. mirroring the existing corporate interpretation of "agile"/scrum development.
I was thinking and seeing the title of this article, it would be interesting to setup a agent environment that mirrors a typical open source project involving a discussion forum (where features are thrown around) and a github issue/PR (where implementation details are discussed) and then have a set of agents that are "mergers" - acting as final review instances.
I assume that agents can be organised in any form at all, it's just a matter of setting up the system prompt and then letting them go for it. A discourse forum could be set up where agents track the feature requests of users of the software and then discuss how to implement it or how to workaround it.
The reason I ask is because one could then do a direct comparison of development processes, i.e. the open source model versus the corporate top-down process. It would interest me to see which process performance better in terms of maintainability, quality and feature richness.
(I know this isn't the actual point of your comment, apologies!)
When AI will eventually become the primary means to write code (because hand-programming is going to be slow enough that no company can continue like before) then that means AI becomes your new compiler that comes with a price tag, a subscription.
Programmers were held hostage to commercial compilers until free compilers reached sufficient level of quality, but now it doesn't matter if your disk is full of free/open toolchains if it's not you who is commanding them but commercial AI agents.
Undoubtedly there will be open-source LLMs eventually, of various levels of quality. But to write a free compiler you need a laptop while to train a free programming LLM you need a lot of money. And you also need money to run it.
Programming has been one of the rare arts that even a poor, lower class kid can learn on his own with an old, cheap computer salvaged from a scrap bin and he can raise himself enough intellectual capital to become a well-paid programmer later. I wonder what the equivalent path will be in the future.
LLMs don't make programming faster, they just accelerate the technical debt process.
On agregate they slow everything down because you there's more technical debt at the end of the tunnel.
(OpenClaw is already unmaintainable today - for example, nobody has any clue what configuration options it supports, not even LLMs. Game over.)
That would basically make users a product manager and UX designer, which they aren't really capable of currently. At most they will discover what they think they want isn't what they actually want.
these are exciting times, that are coming despite any pessimism rooted in our out-dated software paradigms.
It compares and contrasts open source and free software, and then gives an example of how free software is better than closed software.
But if the premise of the article, that the agent will take the package you pick and adapt it to your needs, is correct, then honestly the agent won't give a rat's ass whether the starting point was free source or open source.
The AI propaganda articles are getting more devious my the minute. It's not just propaganda---it's Bernays-level manipulation!
Copyleft licenses like GPL/Apache mandate upstream freedom: Upstream has the "freedom" to use anything downstream, including anything written by a corporation.
Non-copyleft FOSS licenses like MIT/BSD are about downstream freedom, which is more of a philosophically utilitarian view, where anyone who receives the software is free to use it however they want, including not giving their changes back to the community, on the assumption that this maximizes the utility of this free software in the world.
If you prioritize the former goal, then coding agents are a huge problem for you. If the latter, then coding agents are the best thing ever, because they give everyone access to an effectively unlimited amount of cheap code.
If trendlines continue... It will be faster for AI to vibe code said software to your customized specifications than to sign up for a SaaS and learn it.
"Claude, create a project management tool that simplifies jira, customize it to my workflow."
So a lot of apps will actually become closed source personalized builds.
There is a reason why large proprietary products remain prevalent even when cheaper better alternatives exist. Being "industry standard" matters more than being the best.
I've always preferred my stack to be on the thinner, more vanilla, less prebuilt side than others around me, and seems like LLMs are reinforcing that approach now.
Like all code-generators that came before, the current LLM will end up a niche product after the hype-cycle ends. "AI" only works if the models are fed other peoples real works, and the web is already >52% nonsense now. They add the Claude-contributor/flag to Git projects, so the scrapers don't consume as much of its own slop. ymmv =3
I can already build a ticket tracker in a weekend. I’ve been on many teams that used Jira, nobody loves Jira, none of us ever bothered to DIY something good enough.
Why?
Because it’s a massive distraction. It’s really fun to build all these side apps, but then you have to maintain them.
I’m guessing a lot of vibeware will be abandoned rather than maintained.
You typically use an off the shelf project management software because it's too time consuming to build one catered to your own preferences. But with AI, it just does it for you. I'm talking about custom one off personal solutions readily done because of AI executing on it for you.
And it’s all downhill from there…
If AI can build your software for you, you aren't going to be playing golf, you're going to be standing in line in the soup kitchen.
Trendlines will continue. Even the one for greenhouse gases. That is the most realistic scenario. In fact the trendline for greenhouse gases is even stronger than AI. I am far more confident about greenhouse gases continuing to rise than I am for AI.
Telling me how another trendline points to a shitty reality doesn't change the fact that the shitty reality is still reality. It's a common mistake in debate.
I haven't stated whether I hope for one reality or the other. I'm simply stating the most probable future. You haven't even disagreed with me.
The realistic scenarios are still pretty bad but less so.
Just assuming LLMs will scale to the point of being more useful as all these companies are banking on is not unfounded but it's also just an educated guess because of their own optimistic prediction they will be able to bring about a new fascist world they are in charge of before they run out of money. It's very likely we are all screwed but it's also very likely LLMs will not scale up fast enough so they can replace the majority of human labor.
The question is why? Tragedy of the commons.
(luckily my projects are unpopular enough that nobody bothered training on them lol)
Value isn't just slapping a license on something and pushing to GitHub. It's maintaining and curating that software over years, focusing the development towards a goal. It's as much telling users what features you're not willing to add and maintain as it is extending the project to interoperate with others.
And that long term commitment to maintenance hasn't come out of the vibe coded ecosystem. Commitment is exactly what they don't want, rather they want the fast sugar high before they drop it and move on to the next thing.
The biggest threat to open source is the strip mining of the entire ecosystem, destroying communities and practices that have made it thrive for decades. In the past, open source didn't win because it always had the best implementation, but because it was good enough to solve problems for enough people that it became self sustaining from the contribution of value.
I feel that will continue, but it's also going to take a set back from those that aren't interested in contributing value back into the ecosystem from which they have extracted so much.
The worst part is building something open source, getting positive feedback, helping a couple of startups and then some big corporation comes along and implements a similar product and then everyone gets forced by their bosses to use the corporate product against their will and people eventually forget your product exists because there are no high-paying jobs allowing people to use it.
With hindsight, Open Source is basically a con for corporations to get free labor. When you make software free for everyone, really you're just making it free for corporations to Embrace, Extend, Extinguish... They invest a huge amount of effort to suppress the sources of the ideas.
Our entire system is heavily optimized for decoupling products from their makers. We have almost no idea who is making any of the products we buy. I believe there is a reason for that. Open source is no different.
When we lived in caves, everyone in the tribe knew who caught the fish or who speared the buffalo. They would rightly get credit. Now, it's like; because none of the rich people are doing any useful work, they can only maintain credibility by obfuscating the source of the products we buy. They do nothing but control stuff. Controlling stuff does not add value. Once a process is organized, additional control only serves to destroy value through rent extraction.
AI backdoors are already a well known problem, and vibe-coded free software is always going to present a substantial risk. We'll see how it plays out in time, but I can already see where it's heading.
After enough problems, reputation and humans in the loop could finally become important again. But I have a feeling humanity is going to have to learn the hard way first (again).
This is a bullshit argument, and I'm surprised that people aware enough of these issues would try to push it.
Closed (or online-only) software prevents not only the end user from modifying it, but also 'unlicensed' hackers that the end user can ask for help.
See the "right to repair" movement as a very close example. The possibility of an 'ecosystem' of middlemen like these, matters !
My prompts to Claude has evolved from "what program / data source do I need to do this" to "what program / data source do I need, to make you do this for me".
After a few iterations, any data source without a free API feed, or any program without a free CLI interface are edited out of the gene pool, so to speak.
Some kind of artisan "proper" quality work, compared to cheap enterprise AI slop.
I think Pete Hegseth would disagree with this statement.
Conflict of interests is the norm. It should be illegal for a company founder or director to own stock of a supplier. It should be illegal for shareholders to own stocks of two competing companies. Index funds should be illegal.