I think many of us have already noticed that a growing number of open-source projects and libraries are moving towards commercial or dual-licensing models.
In the .NET ecosystem, several widely used libraries have taken this path over the past year or so. AutoMapper and MediatR introduced commercial editions under a dual-licensing model, Fluent Assertions began requiring a paid licence for commercial use with version 8, and MassTransit 9 became a commercial product.
These libraries were widely used in .NET applications and I mean widely used. Many projects treated them almost as a standard part of the ecosystem.
Now, the same change is reaching the frontend world. PrimeTek recently announced that future major versions of PrimeNG, PrimeReact and PrimeVue will no longer be released as open source.
All these projects were widely adopted, and many commercial applications depended heavily on them. Their licensing changes were primarily driven by the cost of long-term maintenance, but this raises a broader question:
Is AI also changing the world of open source?
You have probably already read many articles about code inflation. With AI, we can generate a huge amount of code in a very short time, even if the quality is sometimes questionable.
The same thing is happening in open source. Maintainers can now receive more AI-generated issues, pull requests and feature requests than they can realistically review. Producing code has become cheaper, but understanding, testing and maintaining that code still requires significant human effort. Maintainers can become overwhelmed very quickly.
AI may also discourage some developers from publishing their work publicly. Even small experiments, educational repositories and proof-of-concept projects can become training material for large language models. Some authors may therefore decide to keep their repositories private because they do not want AI companies learning from their work without permission, attribution or compensation.
Licensing creates another difficult question. Imagine that an author spends months building and publishing a project under the GNU GPL. An LLM reads the code and documentation and then helps create a competing closed-source implementation in a fraction of that time.
Proving that an AI-generated implementation was influenced by GPL-licensed code may be almost impossible for an individual maintainer.
Security is another concern. AI makes it easier to generate contributions, but it also makes it faster to discover vulnerabilities and incorrect code. Of course, finding vulnerabilities is generally a good thing. AI can help improve security and identify problems that might otherwise remain unnoticed. However, there is another side to this. Attackers can use the same tools to analyse publicly available source code, discover vulnerabilities much faster and exploit them for their own benefit. Without AI, this kind of analysis could require considerable time, expertise and effort.
None of these problems started with AI. Open-source maintainers have struggled with funding, burnout, cloud providers and commercial exploitation for years. However, AI may be accelerating all of these problems very quickly.
I am curious whether the next generation of developers will still be willing to publish their work in the same way. Even if much of the code is generated by AI, it will still require human effort to make it reliable, maintainable and useful.
Open source will probably not disappear. However, we may see more projects moving towards stricter licensing, free-to-use products with closed source code, or completely commercial development.
What do you think?
What about other major ecosystems, such as Java or Python? Is the same thing happening there too?
And if you were starting a valuable project today, would you still release it as open source?
Top comments (13)
Great article, as always!
I can add one more example from the frontend world that was making the rounds some time ago. Our beloved Tailwind 😉 reportedly ran into serious financial trouble and had to lay off a large number of engineers. Because of AI!
Their business model relied on developers visiting the documentation, where they could promote their paid products 😅. But once LLMs became really good at Tailwind, people simply stopped going there. Instead of searching the docs, they just asked ChatGPT (or another AI) to generate the classes they needed, or, for the more curious, simply asked what a particular class does.
From what I've heard, Python is seeing something similar in some ecosystems: the core libraries remain free, while more advanced tooling or services are increasingly becoming the paid part. Hard to be surprised.
I used to love that software engineering felt so egalitarian. Everyone had access to the same knowledge, documentation, and tools. That's actually quite rare compared to many other professions (I have a degree in a completely different field too, but that's a story for another day 😄).
In the end, though, what can we do? We might as well enjoy the summer by the Polish seaside... and then enjoy some Czech beer in October! 🍺
Thanks, Silwia, for such a thoughtful comment!
That’s crazy, I didn’t know about that. Or maybe I just forgot, since I’ve never used Tailwind very much. Thanks for sharing such a valuable example.
Losing funding because people stop visiting the documentation never occurred to me, but when I think about it, documentation traffic may be an important source of revenue for many smaller open-source projects as well. That’s a really interesting consequence of AI.
Python is especially interesting because I assume it is still one of the main languages used for AI development, so the situation there could be different. But I do not know the Python ecosystem well enough to say.
You also taught me a new word: “egalitarian.” I had to Google it. 😂 You are right, this will probably change, but I really hope we do not lose that spirit completely.
And Czech beer definitely has to be properly chilled, but I have heard that the Polish seaside is too cold even in summer. Is that true? 😄
Haha, the word egalitarian always makes me think of the French Revolution: Liberté! Égalité! 😄
As for the Baltic Sea... it's usually cold, and it's almost always windy. 😂 But today we're actually have 30°C! I live in Gdańsk, so that's first-hand information. 😎
Nice! We’ve considered visiting the Baltic Sea several times because we’ve seen so many beautiful photos of the beaches. But we were always a little worried about the water temperature and “it’s usually cold, and it’s almost always windy” seems to confirm our suspicion. 😂
It reminds me of a Czech saying: “The road is longer and worse too.” 😄
Hahaha, that's fair! 😂 I would say that if you're planning a trip, August gives you the best chance of getting nice weather. 😄
The water is definitely on the chilly side, it's not Croatia. 😂 But that doesn't seem to bother the tourists at all, the beaches are packed every summer. And honestly, our coastline really is beautiful. I may be a little biased since I live in Gdańsk, but I genuinely think it's worth visiting!
These are usual, nothing has changed. However, it's just a same person wearing a new "AI" hat 😂
Yes, the underlying problems are not new, but now they are wearing a much faster AI hat. 😄
However, I think there is one significant difference: several major libraries and frameworks have moved towards commercial licensing within a relatively short period. I do not remember seeing changes on this scale, across so many widely used projects, at any other point in the last decade.
Looks like everyone wants to make enough money before the AI takes a full control. Also, the future has become un-predictable with the "AI" and nobody knows whether the majority of them even will be able to keep up with a job. I am sure, there will be new jobs, new roles and responsibilities. However, we are still missing something.
I see it in a similar way. The desire to make enough money and the fear of losing jobs because of AI are definitely part of the reason.
“Before AI takes full control” sounds like something straight out of a sci-fi movie. 😂
New jobs such as AI engineers already exist, and I expect new roles to appear in QA, technical analysis and AI governance as well. But I am not sure there will be enough of them. And “we are still missing something” is painfully accurate
Solid post, Daniel. "Code got cheap, maintenance didn't" — that one lands especially hard when you're in QA. AI's pushing out 3x the code these days, but nobody's hiring 3x the testers. And open source maintainers were already running on fumes before LLMs turned the dial up. Tired? Same. Just skill me at this point🤣
Thanks, Xulingfeng! That’s actually a really solid point. Everyone talks about how much faster coding has become and how many more projects AI helps people produce, but QA is often completely forgotten. AI-generated code can be just as buggy as code written by developers. Automated testing may be able to scale alongside it, at least to some extent, but manual testing definitely cannot. You’ve genuinely made me think about this from another angle. 😄
And yep, accurate: “just skill me at this point” 😂
Right? Get turned into a skill on Tuesday, laid off on Wednesday 🤣
I really hope that doesn’t happen to me. 😂