Someone on Mastodon (I’m sorry, but I don’t remember who exactly) published a short post that pointed to a rather technical economic study of the impact of AI on FOSS software development [1]. It is no secret that the AI debate is highly polarized, and the enthusiasts for the current trend in AI applications in the IT domain are at least as numerous as those who are concerned/skeptical. What is certain is that no one can, in the long term, prospectively evaluate the impact of AI on society, particularly in the IT world.
The main thesis of the paper is that AI-based code production will end the mainstreaming of FOSS software, as we have learnt over the last 15-20 years. The paper begins with well-known episodes from recent history (specifically, the Tailwind saga [2] and Stack Overflow's near-death experience [3]).
Of course, the paper presents a theoretical economic model to evaluate a possible impact scenario for the FOSS production model, which could or could not come to fruition, depending on the assumptions made.
My honest opinion is that a conscious and accurate use of AI can accelerate development. That is, in a bad and good sense, I mean directly on the basis of the experience and skills of people who use such models. Therefore, we are both seeing slop and high-profile creations with the aid of AI. Maybe slop contributions are more prevalent simply because mediocre developers are the majority, and mediocrity is the backbone of enterprise production (because it is the most replicable and independent of contributors and their capacities).
Like it or not, modern software industries do not need, and fight against, too much creative approaches. Enterprises need aurea mediocritas, not isolated geniuses. Also, depending on third-party creations, it apparently reduces the enterprise's technical debt because it is typically shifted onto someone else's shoulders. Of course, this is an approach that works until it fails miserably when such a third party disappears, changes its license model, changes its mind about the product, changes its APIs, and so on.
That said, one clear consequence of using AI helpers in coding appears to be the progressive disappearance of many packages, modules, and libraries, which can be easily replaced by AI-generated creations tailored to the task. Just to cite one practical example, Tailwind nowadays could be easily replaced by CSS and simple JavaScript components, with the obvious advantage of not depending on yet another third-party-controlled piece of code that could be subject to abrupt changes from one version to another without notice and break existing codebases. At the same time, Tailwind themes can be generated by AI without even consulting its documentation (which apparently had an immediate impact on the company's revenues).
Another advantage is that AI-based, tailored solutions would reduce the amount of code from external dependencies that solve problems for others, instead of focusing on the minimal set of features for your own needs (with all the implications of possible breakages arising from such an anti-minimalistic pattern).
Of course, using AI helpers in this way does not reduce the effort required to understand and create new software, but it probably raises the required competence to a higher level, which could be better in the long term, while encouraging quick-and-dirty approaches in the near term. The so-called vibe coding is not a black-and-white concept; it has a lot of grey tones directly depending on the awareness, responsibility, and skills of the developer: as said, it can accelerate in many senses - even to crash against a wall - increasing in an uncontrolled manner the technical debt when in the hands of the wrong individual. Even about that, Anthropic recognizes that AI abuse can negatively impact coding skills and debugging capabilities [6].
Add to this the current very high infrastructure load many networks are reporting, for which the AI bots currently seem to be the culprit [4]. This seems like very strange behavior for such botnets, given that web crawlers have been around since the 90s and should be able to handle infrastructure load fairly well by now. It seems that AI companies simply aren't fair enough on their own, or that the training phases of neural nets are definitely more demanding. Maybe both?
So, what do I see as the future for FOSS development as a whole? I am not a pessimist as in the cited article. For sure, I see fewer small contributions in the long term. Today, there is a massive production of AI-slop-based contributions to many prime-time projects, but I see this as incidental. In recent years, GitHub-based path of honors has been a major self-promotion channel for junior developers, which explains the drift toward low-quality contributions: devs are (were?) strongly motivated to contribute and find in AI slop an easy path to that, by creating personal portfolios. That’s also true for fake security-related reports (see the well-known Curl project case [5] and others). This is, of course, annoying, but in my view, that’s the result of current AI hype and should normalize in the mid-term.
Also, in the near future, I see less and less relevance in FOSS projects that are not sustained by a strong architectural idea, innovation-grade, a large community, and a consistent development effort (much bigger than a few weeks or months of work). That kind of project will become mainly background noise, let me say. Maybe that could impact whole categories of FOSS software: it is not a secret that many language hubs are full of packages/modules of dubious quality, often used because they are available just a use/import directive away. In many cases, such products will simply be replaced by an AI-based reimplementation. If the final result will be better or worse in average quality, only the future will show. For sure, the AIAD will cause a progressive democratization/popularization of the development process, giving average users access to possibilities once unavailable to them: we will probably see the production of a plethora of small tools and workflows built on agents rather than finished, refined products, like it or not.
The result could be an increase in FOSS products at the cost of lower average generality and code quality, with a few high-end, tailored products for mainstream applications instead. But was this really so different in the past? I don’t think so. The true difference is probably the increase in quantity in both sets of products, as potentiated by AI tools: if one does not do her/his homework, the result is clearly garbage, but that was true before AI, too.
“AI gives us the worst and the best - simultaneously.”
(Daniel Stenberg, the Curl Mantainer)
References
- Vibe Coding Kills Open Source.
- Tailwind Labs Lays Off Engineers, Citing the ‘Brutal Impact’ of AI.
- Dramatic drop in Stack Overflow questions as devs look elsewhere for help.
- OpenStreetMap is concerned: thousands of AI bots are collecting data.
- Death by a thousand slops.
- How AI assistance impacts the formation of coding skills.
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