This feels like the OpenSSL problem where we do probably need some kind of industry organization to maintain these things. There’s a chicken and the egg problem that these AI companies need someone to keep maintaining tailwind if they want it to keep working in their prompts.
Maybe that limits the ability for the head of tailwind to run their own business and make more income, but something gotta give.
In my opinion LLMs are intellectual property theft. Just as if I started distributing copies of books. This substantially reduces the incentive for the creation of new IP.
All written text, art work, etc needs to come imbued with a GPL style license: if you train your model on this, your weights and training code must be published.
By your analogy human brains as also IP thefts, because they ingest what's available in the world, mix and match them, and synthesize slightly different IPs based on them.
WTF? This is a completely unacceptable comment on HN. I don't know why you would think that is acceptable after being registered here for so long. The entire reason HN exists is to be better than that.
I support your right to have an opinion, but in my opinion, thank God this is just your opinion.
Copyright, as practiced in late 20 and this century, is a tool for big corps to extract profits from actual artists, creators, and consumers of this art[0] equally. Starving artists do not actually benefit.
Look at Spotify (owned and squeezed by record labels) giving 70% of the revenue to the record labels, while artists get peanuts. Look at Disney deciding it doesn't need to pay royalties to book writers. Hell, look at Disney's hits from Snow White onwards, and then apply your "LLMs are IP theft" logic to that.
Here's what Cory Doctorow, a book author and critic of AI, has to say about it in [1]:
> So what is the alternative? A lot of artists and their allies think they have an answer: they say we should extend copyright to cover the activities associated with training a model.
> And I'm here to tell you they are wrong: wrong because this would inflict terrible collateral damage on socially beneficial activities, and it would represent a massive expansion of copyright over activities that are currently permitted – for good reason!.
---
> All written text, art work, etc needs to come imbued with a GPL style license
GPL-style license has been long known not to work well for artifacts other than code. That's the whole reason for existence of Creative Commons, GNU Free Documentation License, and others.
The thing is, copyright law is not really on your side. Viewing copyrighted material without paying for it is not generally something people get fined for. A lot of training falls under fair use that overrides whatever license you come up with. Disney can’t stop me from uploading clips of their movies alongside commentary and review because fair use allows that. LLMs generally aren’t redistributing code, which is the thing that copyright protects.
If I inspect some GPL code and get inspired by it and write something similar, the GPL license doesn’t apply to me.
It has always been the case that if you don’t want other people to apply fair use to your works, your only recourse is to keep those works private. I suspect that now individuals and companies that don’t want their code to be trained on will simply keep the code private.
Now, there have been times where LLMs have reproduced verbatim copyright material. The NYTimes sued OpenAI over this issue. I believe they’ve settled and come up with a licensing scheme unless I’m mixing up my news stories.
Second thing, your issue becomes moot if there exists a model that only trains off of MIT-licensed code, and there is a TON of that code out there.
Third thing, your issue becomes moot if users have agreed to submit their code for training, like what the GitHub ToS does for users who don’t change their settings, or if giant companies with giant code bases just use their own code to train LLMs.
Where I agree with you is that perhaps copyright law should evolve. Still, I think there’s a practical “cat is out of the bag” issue.
Is there such a license? Or any license with special clauses for LLMs? Is it enforcable? Could someone 'poison' an LLM training run with injecting just one such licensed document? I am genuinely curious about what levers exist (or are conceivable) to protect your own IP from becoming LLM training data, if regular copyright does not qualify.
"The value got extracted, but compensation isn't flowing back. That bothers me, and it deserves a broader policy conversation.
What I keep coming back to is this: AI commoditizes anything you can fully specify. [...]
So where does value live now? In what requires showing up, not just specifying. Not what you can specify once, but what requires showing up again and again."
This seems like a useful framing to be aware of, generally.
The internet has always kinda run on the ambiguity of "does the value flow back". A quote liberated from this article itself; all the content that reporters produce that's laundered back out through twitter; 12ft.io; torrents; early youtube; late youtube; google news; apache/mit vs gnu licenses; et cetera..
I know for a fact that all SOTA models have linux source code in them, intentionally or not which means that they should follow the GPL license terms and open-source part of the models which have created derivative works out of it.
yes, this is indirectly hinting that during training the GPL tainted code touches every single floating point value in a model making it derivative work - even the tokenizer isn't immune to this.
Tailwind Labs relied on a weird monetization scheme.
Revenue was proportional to the pain of using the framework. The sudden improvement in getting desired UI without relying on pre-built templates killed Tailwind Labs.
There are many initiatives in a similar spot, improving your experience at using Next.js would hurt Vercel.
Making GitHub actions runners more reliable, stable and economical would hurt Microsoft.
Improving accessibility to compute power would hurt Amazon, Microsoft and Google.
Improving control and freedom over your device would hurt apple and Google.
Why should we be sympathetic to the middleman again?
If suddenly CSS became pleasant to use, Tailwind would be in a rough spot. See the irony?
"Give everything away for free and this people will leave technology", geohot said something like this and I truly appreciate. Technology will heal finally
—-
I find it really crazy that they think would be good idea. I wonder how many false positive css stuff is being added given their “trying to match classes”. So if you use random strings like bg-… will add some css. I think it’s ridiculous, but tells that people that use this can’t be very serious about it and won’t work in large projects.
——
> Using multi-cursor editing
When duplication is localized to a group of elements in a single file, the easiest way to deal with it is to use multi-cursor editing to quickly select and edit the class list for each element at once
Instead of using a var and reusing, you just use multi cursors. Bad suggestions again.
—-
> If you need to reuse some styles across multiple files, the best strategy is to create a component
But on benefits says
> Your code is more portable — since both the structure and styling live in the same place, you can easily copy and paste entire chunks of UI around, even between different projects.
—-
> Making changes feels safer — adding or removing a utility class to an element only ever affects that element, so you never have to worry about accidentally breaking something another page that's using the same CSS.
> "Give everything away for free and this people will leave technology"
This is more interesting, although somewhat generally understood (can be conflated with people seeing "free" and "cheap" and therefore undesirable). It depends on your definitely of longevity but we certainly have a LOT of free software that has, so far, lasted the test of time.
That’s not at all why I bought Tailwind Plus. I bought it (at work) to have a solid collection of typical components and UI patterns, mostly expertly designed with a lot of attention to detail, to use as inspiration and as a shared language with other frontend devs and designers. I rarely (if ever) actually copy pasted any of their HTML or Tailwind styles. It’s mostly used as reference and inspiration. The fact that it’s implemented in Tailwind is mostly irrelevant (Tailwind really isn’t hard to use, especially after your first couple of small projects).
Calling it a stress test seems a bit off. Would we say that invention of lightbulbs was a "stress test" for candle related business models? Or would we just say that business models had to change in response to current events.
> Value is shifting to operations: deployment, testing, rollbacks, observability. You can't prompt 99.95% uptime on Black Friday. Neither can you prompt your way to keeping a site secure, updated, and running.
I agree somewhat but eventually these can be automated with AI as well.
I see "hackers" in these comments are now advocating to make "criminal contempt of business model" a serious thing, instead of a mere meme used to describe draconian copyright and patent laws.
It's a reddit alternative hosted by a venture capitalist firm, the startup culture is much more prevalent here than the hacker culture that inspires the website's <title> tag.
> You can't prompt 99.95% uptime on Black Friday. Neither can you prompt your way to keeping a site secure, updated, and running.
This is completely wrong. Agents will not just be able to write code, like they do now, but will also be able to handle operations, security, continuing to check, and improve the systems, tirelessly.
Framing it as a "conduit" disruption might make a lot of assumptions about the fundamental economic value of software in the future. In a world (whether near term or long term) where you can just ask the computer to make whatever software you want, what are the economics of retailing/licensing any software at all? Open source or otherwise?
Not to nitpick but if we are going to discuss the impact of AI, then I'd argue "AI commoditizes anything you can specify." is not broad enough. My intuition is "AI commoditizes anything you can _evaluate/assess_." For software automation we need reasonably accurate specifications as input and we can more or less predict the output. We spend a lot of time managing the ambiguity on the input. With AI that is flipped.
In AI engineering you can move the ambiguity from input to the output. For problems where there is a clear and cheaper way of evaluating the output the trade-off of moving the ambiguity is worth it. Sometimes we have to reframe the problem as an optimization problem to make it work but same trade-off.
On the business model front: [I am not talking specifically about Tailwind here.] AI is simply amplifying systemic problems most businesses just didn't acknowledge for a while. SEO died the day Google decided to show answer snippets a decade ago. Google as a reliable channel died the day Google started Local Services Advertisement. Businesses that relied on those channels were already bleeding slowly; AI just made it sudden.
On efficiency front, most enterprises could have been so much more efficient if they could actually build internal products to manage their own organizational complexity. They just could not because money was cheap so ROI wasn't quite there and even if ROI was there most of them didn't know how to build a product for themselves. Just saying "AI first" is making ROI work, for now, so everyone is saying AI efficiency. My litmus test is fairly naive: if you are growing and you found AI efficiency then that's great (e.g. FB) but if you're not growing and only thing AI could do for you is "efficiency" then there is a fundamental problem no AI can fix.
> if you are growing and you found AI efficiency then that's great (e.g. FB) but if you're not growing and only thing AI could do for you is "efficiency" then there is a fundamental problem no AI can fix.
exactly, "efficiency" nice to say in a vacuum but what you really need is quality (all-round) and understanding your customer/market
Companies providing AI services should offer ads for the things the AI is using. And I don't mean "Tailwind could pay Google to advertise in Gemini", I mean "Google should be clearly and obviously linking back to Tailwind when it uses the library in its output"
They already do this sort of thing inside outputs from Deep Research, and possibly without. But the output should be less muted, inline, recessed and more "I have used Tailwind! Check out how to make it better [HERE](link)"
They should be working with the owners of these projects, especially ones with businesses, and directing traffic to them. Not everyone will go, and that's fine, but at least make the effort. The infrastructure is in place already.
And yes, right now this would not be across-the-board for every single library, but maybe it could be one day?
It's the same problem news sites have been facing for years because of Google News and Facebook. Their solution so far has been country-level bans on it (Canada).
I was thinking something similar, but not so much an ad as a citation. A good starting point might be a law stating that when an LLM produces an answer, it cite its sources, with a link back to the content. Ideally, though, the producer of that content should receive some amount of financial compensation as well, similar to how an author or an actor receives royalties. If the LLM is making money off of this, so should the person who provide the LLM the value.
> So where does value live now? In what requires showing up, not just specifying. Not what you can specify once, but what requires showing up again and again.
Sounds like even more incentive for "managing" problems and creating business models around them instead of solving them.
Tailwind plus is available for one time payment that provides lifetime access to current and future components. With AI cutting off the flow for new buyers, revenue shrivels up much quicker than what it would've been if it was a recurring subscription.
>Open Source was never the commercial product. It's the conduit to something else.
this is correct. If you open source your software, then why are you mad when companies like AWS, OpenAI, etc. make tons of money?
Open Source software is always a bridge that leads to something else to commercialize on. If you want to sell software, then pick Microsoft's model and sell your software as closed source. If you get mad and cry about making money to sustain your open source project, then pick the right license for your business.
One of the biggest shortcomings of Open Source was that it implicitly defaulted to a volunteer model and so financing the work was always left as an exercise for the reader.
Hence (as TFA points out) open source code from commercial entities was just a marketing channel and source of free labor... err, community contributions... to auxiliary offerings that actually made money. This basic economic drive is totally natural but creates dynamics that lead to suboptimal behaviors and controversy multiple times.
For instance, a favorite business model is charging for support. Another one was charging for a convenient packaging or hosting of an “open core” project. In either case, the incentives just didn’t align towards making the software bug-free and easily usable, because that would actively hamper monetization. This led to instances of pathological behavior, like Red Hat futzing with its patches or pay-walling its source code to hamper other Linux vendors.
Then there were cases where the "open source" branding was used to get market-share, but licenses restricted usage in lucrative applications, like Sun with Java. But worse, often a bigger fish swooped in to take the code, as they were legally allowed to, and repackage it in their own products undercutting the original owners. E.g. Google worked around Sun's licensing restrictions to use Java completely for free in Android. And then ironically Android itself was marketed as "open source" while its licensing came with its own extremely onerous restrictions to prevent true competition.
Or all those cases when hyperscalers undercut the original owners’ offerings by providing open source projects as proprietary Software as a Service.
All this in turn led to all sorts of controversies like lawsuits or companies rug-pulling its community with a license change.
And aside from all that, the same pressures regularly led to the “enshittification” of software.
Open Source is largely a socialist (or even communist) movement, but businesses exist in a fundamentally capitalistic society. The tensions between those philosophies were inevitable. Socialists gonna socialize, but capitalists gonna capitalize.
With AI, current OSS business models may soon be dead. And personally I would think, to the extent they were based on misaligned incentives or unhealthy dynamics, good riddance!
Open Source itself will not go away, but it will enter a new era. The cost of code has dropped so much, monetizing will be hard. But by the same token, it will encourage people, having invested so much fewer resources creating it, to release their code for free. A lot of it will be slop, but the quantity will be overwhelming.
It’s not clear how this era will pan out, but interesting times ahead.
> You can't prompt 99.95% uptime on Black Friday. Neither can you prompt your way to keeping a site secure, updated, and running.
Uh, yeah you can. There’s a whole DevOps ecosystem of software and cloud services (accessible via infrastructure—as-code) that your agents can use to do this. I don’t think businesses who specialize in ops are safe from downsizing.
65 comments
[ 1.8 ms ] story [ 74.8 ms ] threadMaybe that limits the ability for the head of tailwind to run their own business and make more income, but something gotta give.
All written text, art work, etc needs to come imbued with a GPL style license: if you train your model on this, your weights and training code must be published.
You say that like it's a bad thing...
WTF? This is a completely unacceptable comment on HN. I don't know why you would think that is acceptable after being registered here for so long. The entire reason HN exists is to be better than that.
https://news.ycombinator.com/newsguidelines.html
Copyright, as practiced in late 20 and this century, is a tool for big corps to extract profits from actual artists, creators, and consumers of this art[0] equally. Starving artists do not actually benefit.
Look at Spotify (owned and squeezed by record labels) giving 70% of the revenue to the record labels, while artists get peanuts. Look at Disney deciding it doesn't need to pay royalties to book writers. Hell, look at Disney's hits from Snow White onwards, and then apply your "LLMs are IP theft" logic to that.
Here's what Cory Doctorow, a book author and critic of AI, has to say about it in [1]:
> So what is the alternative? A lot of artists and their allies think they have an answer: they say we should extend copyright to cover the activities associated with training a model.
> And I'm here to tell you they are wrong: wrong because this would inflict terrible collateral damage on socially beneficial activities, and it would represent a massive expansion of copyright over activities that are currently permitted – for good reason!.
---
> All written text, art work, etc needs to come imbued with a GPL style license
GPL-style license has been long known not to work well for artifacts other than code. That's the whole reason for existence of Creative Commons, GNU Free Documentation License, and others.
[0] "consumers of art" sounds abhorrent, yet that's exactly what we are [1] https://pluralistic.net/2025/12/05/pop-that-bubble/
The thing is, copyright law is not really on your side. Viewing copyrighted material without paying for it is not generally something people get fined for. A lot of training falls under fair use that overrides whatever license you come up with. Disney can’t stop me from uploading clips of their movies alongside commentary and review because fair use allows that. LLMs generally aren’t redistributing code, which is the thing that copyright protects.
If I inspect some GPL code and get inspired by it and write something similar, the GPL license doesn’t apply to me.
It has always been the case that if you don’t want other people to apply fair use to your works, your only recourse is to keep those works private. I suspect that now individuals and companies that don’t want their code to be trained on will simply keep the code private.
Now, there have been times where LLMs have reproduced verbatim copyright material. The NYTimes sued OpenAI over this issue. I believe they’ve settled and come up with a licensing scheme unless I’m mixing up my news stories.
Second thing, your issue becomes moot if there exists a model that only trains off of MIT-licensed code, and there is a TON of that code out there.
Third thing, your issue becomes moot if users have agreed to submit their code for training, like what the GitHub ToS does for users who don’t change their settings, or if giant companies with giant code bases just use their own code to train LLMs.
Where I agree with you is that perhaps copyright law should evolve. Still, I think there’s a practical “cat is out of the bag” issue.
What I keep coming back to is this: AI commoditizes anything you can fully specify. [...]
So where does value live now? In what requires showing up, not just specifying. Not what you can specify once, but what requires showing up again and again."
This seems like a useful framing to be aware of, generally.
The internet has always kinda run on the ambiguity of "does the value flow back". A quote liberated from this article itself; all the content that reporters produce that's laundered back out through twitter; 12ft.io; torrents; early youtube; late youtube; google news; apache/mit vs gnu licenses; et cetera..
yes, this is indirectly hinting that during training the GPL tainted code touches every single floating point value in a model making it derivative work - even the tokenizer isn't immune to this.
There are many initiatives in a similar spot, improving your experience at using Next.js would hurt Vercel. Making GitHub actions runners more reliable, stable and economical would hurt Microsoft. Improving accessibility to compute power would hurt Amazon, Microsoft and Google. Improving control and freedom over your device would hurt apple and Google.
Why should we be sympathetic to the middleman again?
If suddenly CSS became pleasant to use, Tailwind would be in a rough spot. See the irony?
"Give everything away for free and this people will leave technology", geohot said something like this and I truly appreciate. Technology will heal finally
I find the tailwindcss approach inexcusable and unmaintainable.
> Improving accessibility to compute power would hurt Amazon, Microsoft and Google.
Yeah, if they were not competing against each other.
> If suddenly CSS became pleasant to use, Tailwind would be in a rough spot. See the irony?
Honestly, I don't. If people suddenly adopted a heathier lifestyle, doctors, at least dentists, would be in a rough spot.
See the irony? Well, again I don't.
> <div class="text-{{ error ? 'red' : 'green' }}-600"></div>
—- I find it really crazy that they think would be good idea. I wonder how many false positive css stuff is being added given their “trying to match classes”. So if you use random strings like bg-… will add some css. I think it’s ridiculous, but tells that people that use this can’t be very serious about it and won’t work in large projects.
—— > Using multi-cursor editing When duplication is localized to a group of elements in a single file, the easiest way to deal with it is to use multi-cursor editing to quickly select and edit the class list for each element at once
Instead of using a var and reusing, you just use multi cursors. Bad suggestions again.
—-
> If you need to reuse some styles across multiple files, the best strategy is to create a component
But on benefits says
> Your code is more portable — since both the structure and styling live in the same place, you can easily copy and paste entire chunks of UI around, even between different projects.
—-
> Making changes feels safer — adding or removing a utility class to an element only ever affects that element, so you never have to worry about accidentally breaking something another page that's using the same CSS.
CSS in js fixed this long time ago.
—-
<div class="mx-auto flex max-w-sm items-center gap-x-4 rounded-xl bg-white p-6 shadow-lg outline outline-black/5 dark:bg-slate-800 dark:shadow-none dark:-outline-offset-1 dark:outline-white/10"> <img class="size-12 shrink-0" src="/img/logo.svg" alt="ChitChat Logo" /> <div> <div class="text-xl font-medium text-black dark:text-white">ChitChat</div> <p class="text-gray-500 dark:text-gray-400">You have a new message!</p> </div> </div>
So many classes you need to learn to use it.
They are still around.
> "Give everything away for free and this people will leave technology"
This is more interesting, although somewhat generally understood (can be conflated with people seeing "free" and "cheap" and therefore undesirable). It depends on your definitely of longevity but we certainly have a LOT of free software that has, so far, lasted the test of time.
Do people even know what they can do with CSS these days?
https://lyra.horse/blog/2025/08/you-dont-need-js/
I agree somewhat but eventually these can be automated with AI as well.
A stress test on a bank doesn't actually erase the revenue and financially jeopardize the bank.
Implementing layoffs is not a stress test.
This is completely wrong. Agents will not just be able to write code, like they do now, but will also be able to handle operations, security, continuing to check, and improve the systems, tirelessly.
Not to nitpick but if we are going to discuss the impact of AI, then I'd argue "AI commoditizes anything you can specify." is not broad enough. My intuition is "AI commoditizes anything you can _evaluate/assess_." For software automation we need reasonably accurate specifications as input and we can more or less predict the output. We spend a lot of time managing the ambiguity on the input. With AI that is flipped.
In AI engineering you can move the ambiguity from input to the output. For problems where there is a clear and cheaper way of evaluating the output the trade-off of moving the ambiguity is worth it. Sometimes we have to reframe the problem as an optimization problem to make it work but same trade-off.
On the business model front: [I am not talking specifically about Tailwind here.] AI is simply amplifying systemic problems most businesses just didn't acknowledge for a while. SEO died the day Google decided to show answer snippets a decade ago. Google as a reliable channel died the day Google started Local Services Advertisement. Businesses that relied on those channels were already bleeding slowly; AI just made it sudden.
On efficiency front, most enterprises could have been so much more efficient if they could actually build internal products to manage their own organizational complexity. They just could not because money was cheap so ROI wasn't quite there and even if ROI was there most of them didn't know how to build a product for themselves. Just saying "AI first" is making ROI work, for now, so everyone is saying AI efficiency. My litmus test is fairly naive: if you are growing and you found AI efficiency then that's great (e.g. FB) but if you're not growing and only thing AI could do for you is "efficiency" then there is a fundamental problem no AI can fix.
They already do this sort of thing inside outputs from Deep Research, and possibly without. But the output should be less muted, inline, recessed and more "I have used Tailwind! Check out how to make it better [HERE](link)"
They should be working with the owners of these projects, especially ones with businesses, and directing traffic to them. Not everyone will go, and that's fine, but at least make the effort. The infrastructure is in place already.
And yes, right now this would not be across-the-board for every single library, but maybe it could be one day?
It's the same problem news sites have been facing for years because of Google News and Facebook. Their solution so far has been country-level bans on it (Canada).
Sounds like even more incentive for "managing" problems and creating business models around them instead of solving them.
this is correct. If you open source your software, then why are you mad when companies like AWS, OpenAI, etc. make tons of money?
Open Source software is always a bridge that leads to something else to commercialize on. If you want to sell software, then pick Microsoft's model and sell your software as closed source. If you get mad and cry about making money to sustain your open source project, then pick the right license for your business.
Hence (as TFA points out) open source code from commercial entities was just a marketing channel and source of free labor... err, community contributions... to auxiliary offerings that actually made money. This basic economic drive is totally natural but creates dynamics that lead to suboptimal behaviors and controversy multiple times.
For instance, a favorite business model is charging for support. Another one was charging for a convenient packaging or hosting of an “open core” project. In either case, the incentives just didn’t align towards making the software bug-free and easily usable, because that would actively hamper monetization. This led to instances of pathological behavior, like Red Hat futzing with its patches or pay-walling its source code to hamper other Linux vendors.
Then there were cases where the "open source" branding was used to get market-share, but licenses restricted usage in lucrative applications, like Sun with Java. But worse, often a bigger fish swooped in to take the code, as they were legally allowed to, and repackage it in their own products undercutting the original owners. E.g. Google worked around Sun's licensing restrictions to use Java completely for free in Android. And then ironically Android itself was marketed as "open source" while its licensing came with its own extremely onerous restrictions to prevent true competition.
Or all those cases when hyperscalers undercut the original owners’ offerings by providing open source projects as proprietary Software as a Service.
All this in turn led to all sorts of controversies like lawsuits or companies rug-pulling its community with a license change.
And aside from all that, the same pressures regularly led to the “enshittification” of software.
Open Source is largely a socialist (or even communist) movement, but businesses exist in a fundamentally capitalistic society. The tensions between those philosophies were inevitable. Socialists gonna socialize, but capitalists gonna capitalize.
With AI, current OSS business models may soon be dead. And personally I would think, to the extent they were based on misaligned incentives or unhealthy dynamics, good riddance!
Open Source itself will not go away, but it will enter a new era. The cost of code has dropped so much, monetizing will be hard. But by the same token, it will encourage people, having invested so much fewer resources creating it, to release their code for free. A lot of it will be slop, but the quantity will be overwhelming.
It’s not clear how this era will pan out, but interesting times ahead.
Uh, yeah you can. There’s a whole DevOps ecosystem of software and cloud services (accessible via infrastructure—as-code) that your agents can use to do this. I don’t think businesses who specialize in ops are safe from downsizing.