📅 2026-09-06
AI, Lagrange, Programming, Life
Recently, I was asked if I would be willing to set a strict "no AI" policy on Lagrange. I will try to figure out my stance and justification for it in this post.
The topic of Generative AI is something I've been mulling over for several months now. If you've done anything computer-adjacent over the past couple of years, you will not have missed (although you may have wanted to) the topic of LLMs and AI. The breathless hype; the aggressive adoption in the industry; the incredible and worsening crunch on memory components; the questionable billions of dollars being invested back and forth; the rush to build data centers; and, most pertaining to this post, the holy war in the open source community, declaring death to the clankers, may they pry my keyboard from my cold, dead hands. My own employer is very much on the AI bandwagon, and through this contractual obligation, I have had the opportunity to use frontier agentic models for software development. This is to say, I am not basing my opinions on hearsay or "vibes", but actual evidence and experience of using these tools.
As a flexible technology, Gen AI has many facets to it: speech, music, images, video, text, program code, to name a few. An interesting note to keep in mind is that all these have traditionally been something that only human skill and creativity could achieve at a high, meaningful quality. For example, text-to-speech was always robotic and stilted before machine learning entered the picture. With modern techniques, you can generate extremely natural-sounding speech. When it comes to the more creative arts, while technically proficient, the results of Gen AI lack soul. The same applies to prose as well as images and audio. You can generate paragraphs of pleasant, well-flowing text, but ultimately it is hollow and plastic-wrapped. So far, nothing has changed the fact that actual art is born when the human mind imbues meaning and message into a medium; it is fundamentally a form of communication out-of-band with its actual physical manifestation.
Gen AI has been progressing at a rapid rate. A few years ago we were shaking our heads and/or astonished by the first image generation models that managed to actually produce convincing results (extra fingers notwithstanding). The image generation then quickly ramped up in quality and speed, soon turning into video generation. Nvidia is about to grace us with DLSS 5, real-time neural augmentation of video games to make the visuals more "realistic". In practice, this is Gen AI transforming rendered graphics at a rate of tens of images per second, on your own GPU. The same kind of curve of rapid progress has been evident in the textual domain, with GPT models evolving from nonsensical paragraphs to highly plausible-sounding, glossy articles. Then we got interactive chatbots, and out of those, the coding agents. Today, those agents are able to traverse massive code bases and comprehend them to such an extent that they are able to discover novel exploits and bugs.
It is evident to me that we are once again living through a great disruption in the world of computers. The previous great shift was the rise of the smartphone, the little device that powers our daily lives nowadays in large parts of the world. That shift has impacted and continues to impact society as a whole. I believe Gen AI is also going to have lasting repercussions for years to come.
When it comes to open source projects in particular, we are also faced with the acerbic force of activism. People who work on open source tend to have certain philosophical and dogmatic convictions about freedom and liberties, and an inherent assumption of reciprocity: if you benefit from my lovingly crafted code, you better also contribute something back, so we can all enjoy the virtuous cycle of progress. This is a great model for something that, for a large part, does not rely on monetary incentives. However, now that multiple large corporations are hungrily using all that open source code (and rare books, all of the internet, and whatnot) to train their LLMs, open source folks are appalled. They feel ripped off. Here are the billionaires extracting even more (unearned!) wealth from the fruit of our labors. Add to that the high costs of producing these models: using up valuable resources like water and electricity, polluting the environment with toxins and noise, and drowning the internet in a raging torrent of scrapers that download each and every page they can find. The full picture is quite unpalatable.
Objections in the realm of software do not end at the ethics, though. When you start using modern coding agents to develop software, it involves a fundamental trade-off where you give up control and low-level understanding but get the ability to achieve more complex, wide-ranging objectives. But what about code quality? Can you even understand what it does? Valid concerns; there were similar ones when we started using compilers instead of writing assembly language by hand. Another point of comparison is the whole industrial revolution where highly-skilled artisans were being replaced by production lines and factories. I understand it involved quite a bit of unrest. (For instance, famously, a certain bunch of textile workers in England got really upset about being supplanted by machines and went on quite the rampage.) That is to say, we've been here before, and past experience shows people will not take it lying down when their livelihood and core identity is being threatened and rendered obsolete.
Therefore, it is easy to understand why many are upset and willing to take extreme positions to defend their view of internet decorum and how software should be written and distributed.
Given all this messiness, what should my personal stance be?
As mentioned above, I have been using frontier models and coding agents for several months at work. This was when I discovered a key factor in my own stance: if I don't really care about the code personally, why should I spend precious time and energy writing it by hand? The company only cares that the objectives are met; the code is a mere implementation detail.
When it comes to hobby projects like Lagrange, I do very much care about the source code, how it is written, and which features are included and which are not. Nine years ago, I designed and wrote a whole library (the_Foundation) so I could make complex C programs in the specific way that I prefer: low-level and understandable from top to bottom. Lagrange is built on this library as well. So, I tend to be biased against introducing factors that are counter to these principles.
However, software projects are much more than source code. For instance, there is a whole lot of busywork when it comes to compiling portable code on multiple platforms: build environments, dependencies, release automation, packaging, and distribution. Necessary and useful things, but not a particularly fun way to spend one's free time. I have used coding agents to help with this kind of scaffolding. It has saved time and helped improve the project's (modest) infrastructure. As a concrete example, the apt.skyjake.fi Debian repository is totally vibecoded, managed by a systemd-run bot that builds packages in the background automatically as versions are published. I could've learned how to set up the Docker containers for the various versions of Debian, fixed the details of the cross-compiling, and set up scripts to compose the Apt repository, but I judged this was several weeks' worth of time better spent on actual improvements in the app. To put it bluntly: I didn't really care about these aspects, so outsourcing them was acceptable.
I am not an activist nor an idealist. I have no burning desire to join the holy war against AI. History shows that these disruptions are a wildfire that ravages the land until new life can grow again, and that fighting the blaze, while brave and commendable, is ultimately futile. Alas, the voices and actions of individuals are no match against the crushing pressure (the billions of dollars) of an industry seeking to increase its profits and productivity. Capitalism paired with the collective action problem is firmly driving this train. (See also: the lack of any meaningful response to climate change.)
I find my views on Gen AI aligning quite well with Linus Torvalds: now in the fall of 2026, it is a useful and capable tool, but you should still keep a tight hold on the reins and be mindful of what you're doing. Be the one with the vision, and make sure it is your vision and not the machine's.
Summarizing this into an actual policy:
For a "no AI" purist, this probably sounds like the misguided ramblings of a slophead. You may be thinking that "wtf, Lagrange is now a 24/7, slop-around-the-clock, pile of AI garbage." Well, I have been writing Lagrange since 2020 (by hand, naturally) with the very pragmatic standpoint of making it the perfect Gemini client for my own needs. (After all, what is Gemini about if not empowerment to implement one's own clients and servers.) I don't intend for that to change any time soon, even if certain aspects will be handled by a coding agent. Gemini is still about keeping things as simple as they need to be; no avalanche of vibecoded features will be forthcoming.
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The original Gemtext version of this page can be accessed with a Gemini client: gemini://skyjake.fi/gemlog/2026/09/choosing-sides-in-the-holy-war.gmi