I recently sent a brief answer to @krille on Mastodon about what managing an average FOSS project looks like in 2026. Christian is the main author of a Flutter app (FluffyChat, a Matrix client). Indeed, this deserves a more extensive discussion.
I recently sent a brief answer to @krille on Mastodon about what managing an average FOSS project looks like in 2026. Christian is the main author of a Flutter app (FluffyChat, a Matrix client). Indeed, this deserves a more extensive discussion.
The use of AI tools for development (AI-aided development, AIAD) and intellectual work is a disputed, hot topic. I’m generally on the pragmatic side in that regard. While the environmental impact of AI systems is evident and a reasonable concern, these tools, when used with a grain of salt and a responsible approach, can solve problems that would otherwise be hard to manage. Keep man in the loop, to say it in one sentence, and do not pretend that such tools can fully replace human judgment and capabilities.
Some months ago, I participated in this Mastodon poll. My thesis was that, in general, there is no presumptive quality flag that can be added to a product, whether it was created with AI-aided tools or not. My opinion sparked a small, heated controversy among some readers.
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.
I have already addressed the implications of modern LLMs, specifically their training, in the context of copyright and licenses for both code and original content. A 'IANAL' disclaimer applies to this post, but my honest opinion is that such training is a legitimate type of reading and learning after study, unless explicitly excluded in licenses among the licensee's rights.
My last post dealt with some ideas about copyright that need more in-depth analysis. First, as it was common in the old good days, IANAL applies to this post and the whole topic. The final results of current litigations in courts that touch on some of the primary companies involved in the whole AI thing could ultimately differ from what is now the common sense point of view (mine). This post could become rapidly obsolete, so another disclaimer is due for this aspect, too.
My last post captured the attention of my old fellow Sandro 'strk' Santilli on Mastodon, who sent a provocation about the whole AIAD thing. So, the challenge is accepted.
Like many other developers, I recently started using some LLM-based AI systems as helpers for coding in a few languages. I'm not a fan of VSCode, and I prefer a more traditional approach to coding: I hate to cope with code completion servers and use one of my preferred editors, Vim or Emacs. Navigating by tags is more than enough for me. That said, this is the summary of my current experience in the new world of AI-aided approach to coding (i.e., AI-aided development or AIAD for brevity).