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Open-source frameworks are facing a reckoning as AI shakes an already fragile area of the software development industry.
Last month, Adam Wathan, co-founder of Tailwind Labs, which maintains the popular open source Tailwind CSS framework project, revealed it had laid off 75% of its team as a result of a near 80% drop in revenue. The culprit? AI tools were driving developers away from its documentation, a key source of revenue for the company.
“Tailwind is growing faster than it ever has and is bigger than it ever has been,” said Wathan in a Github pull request asking for further LLM documentation optimization. The problem is that the project’s documentation, which was the main way developers would find out about its commercial subscriptions, is already feeling a significant business impact from AI coding assistants providing suggestions and fixes directly within the IDE, saving them from needing to reference the documentation.
The struggles at Tailwind raise a question of whether this is a one-off specific to their business model, or if more frameworks will struggle with this shift.
A 2024 Harvard Business School study estimates that without open-source software, firms would pay 3.5 times more to build key software, which represents a total economic value of $8.8 trillion, highlighting the need for ensuring the development and maintenance of open-source in the AI age.
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Icing on a layered cake of problems
“What you can do without necessarily needing technical knowledge has just changed radically,” said Max Corbani, a venture investor focused on open-source projects. “It’s basically a business model stress test depending on the value you provide.”
This won’t just happen to open source, a whole layer of tooling, products and platforms are at risk of being eaten by AI, he said.
Amanda Brock, CEO of industry group OpenUK, highlights that there are two ways of looking at the Tailwind situation: “One is that they didn’t have a good enough business, otherwise it would have succeeded, and people would have [bought] their product. Another is that they are just unfortunate in their timing, where they’re not big enough to cope with this and put processes or resources in place that some of the bigger players are.”
The emergence of both AI scraping and slop is putting more pressure on open-source maintainers, Brock said. While the scale of open-source adoption over the last 10 years has been unprecedented, that hasn’t translated to better support for maintainers and their projects, she said. These demands are leading to an increased risk of burnout.
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‘Open source isn’t a business model’
Tom Wilkie, chief technology officer at open-source observability platform Grafana Labs, isn’t concerned about the disruption from AI because it operates an “open-core” model, which means it offers a free “feature-limited” version and a commercial offering, Grafana Cloud.
“We have to be a successful business first and an open-source business second,” said Wilkie, noting that less than 1% of its 25 million users are paid. “Open source is not a business model. You can’t just expect to give your software away for free and magically money appears.”
Some of the most successful open-source projects use the open-core model, such as Drupal and Linux, said Jeffrey Paul, VP of open-source solutions at digital transformation agency Fueled. But even the future of that business model could be under threat as AI agents become capable of building products on top of open source frameworks, envisions Konstantin Vinogradov, a venture investor in open-source projects and chairman of the Open Source Endowment.
How to survive
In the case of Tailwind, Wilkie believes AI is being used as an excuse for not building a successful business, pointing to the high failure rate of open-source businesses even prior to AI’s arrival.
While there’s no doubt that it has gotten tougher for projects to get exposure through organic search, doc pages, or Stack Overflow, there are other ways for open-source frameworks to get eyeballs, whether it’s from webinars, conferences, or building a traditional sales team.
“It just changes the calculus of how you find those audiences,” said Jono Bacon, founder and CEO of developer community consultancy Stateshift. He highlights that showing up on social networks, like Reddit, at events, and posting content on YouTube can drive organic traffic that gets rewarded inside an LLM and creates an opportunity for more visibility in this new world.
After news of Tailwind’s layoffs broke, several companies, such as Vercel and Google Studio, stepped up to provide sponsorship. While open-source experts see it as a step in the right direction, they aren’t convinced that corporate sponsorship is a long-term fix. “It’s a good thing, and I hope it will continue, but you might want to own your destiny,” Corbani said.
”It’s also a reality that there are many projects out there that don’t have major commercial entities attached to them and don’t have significant funding, but are critical components of the web and they don’t have that marketing, and even if they did want to do the marketing, they don’t have the time or the resources to do it,” Paul said.
Vinogradov is taking inspiration from the funding model of universities and developing an endowment fund structure, known as Open Source Endowment. Brock also sees a model where open source is recognised as a public good with enterprise, government, and philanthropic funding all being combined and centralised on a per-country basis to contribute to its survival.
There’s a consensus amongst open-source experts and contributors, however, that AI companies do not have a responsibility to fund the ecosystem’s sustainability.
“The code is open, it’s the nature of open source, it’s there for everyone to use. So what claims can we now go after?” said Carlos Rolo, an open-source contributor and manager of open-source contributions at NetApp. Instead, the responsibility to contribute falls on the companies that actually benefit from these frameworks, he said.
AI as a superpower
Even though it seems like AI is a dark cloud hanging over the open-source ecosystem, there are bright spots. For smaller and less well-resourced frameworks, they might be able to tap AI tooling or agents to improve the maintenance of codebases. “Maybe some silver lining in ‘the AI is coming to steal all our jobs’ worry is that perhaps in some cases it might help with some longevity,” Paul said.
Similarly, as developers find their careers disrupted by AI, they might also move toward the open-source ecosystem in search of community and connection. Long term, this could improve the sustainability of these frameworks, so long as those communities don’t become overwhelmed with AI slop.
Rather than act defensively, Wilkie recommends that frameworks become forward-thinking.
“Instead of complaining about it and claiming AI companies should pay them for their IP, I don’t understand why companies aren’t turning this into a superpower,” Wilkie said. “You’ve got this oracle that knows everything about your software, why not use that? … Why not make it so that all the previous niggles and complaints about your software go away?”
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