Human stewardship matters more than who typed the code
Human stewardship matters more than who typed the code
Posted Jul 24, 2026 11:17 UTC (Fri) by grothesque (guest, #130832)Parent article: Codeberg: Protecting our FLOSS commons from LLMs
Here is one concrete example: Together with colleagues, I have created a library (https://pypi.org/project/kwant/) that has become pretty successful in its particular domain of quantum physics: since its initial release in 2013 “Kwant” has been used in the preparation of at least 1000 scientific publications by physicists all over the world. Even so, we never managed to create a self-sustaining open-source community around this project. This is not surprising: even widely used general-purpose libraries struggle to attract contributors. Our library has a narrow field of application, and advancing it requires expert knowledge that only a few dozen (very busy) people have.
Kwant itself does not fall under Codeberg’s restrictions, but it shows that useful software does not necessarily have a large team behind it. LLM-based agents are a welcome help in developing and maintaining such niche projects.
As a researcher, I only have a small team of people. Understandably, these young colleagues are mostly focused on their research and not on code quality. I, however, care greatly about code quality. And I am confident to have the necessary experience, having started as a teenage coder in the 1990s, and having continued this journey ever since. (There was a time when I took pride in hand-crafting x86 assembly. It was fun, and I learned a lot, but this is not an efficient way of writing all code. Why do people believe that one must hand-type all the code that one cares about?)
*Reasonable* LLM use is empowering. To me this means using Pi (https://pi.dev/) as a sparring partner for developing and challenging new ideas. (I value human sparring partners, but these are not always available, especially for tedious tasks. LLM agents are also useful in their own way, for example by having extremely broad, if fallible, encyclopedic knowledge.) I use agents for accelerating code review, debugging, and refactoring.
Here is a non-scientific project that I was able to realize recently with LLM assistance: a frontend to Bubblewrap that streamlines the creation of ad-hoc sandboxes directly on the command line (https://github.com/grothesque/sandkasten). This project is still young, and I haven’t advertised it widely, but I believe that it has promise. In a narrow sense, most of its code lines have been generated by an LLM, but I have nevertheless spent more than a hundred hours of my human time on this project. A lot of human thought went into every aspect of it. I would not have had the time to create something like this manually.
I considered moving this project over to Codeberg. Not anymore.
Mindless vibe-coding is not the only way of coding with LLMs. I do see the problems that Codeberg mentions, but forbidding LLM-generated code is not the right solution in my opinion. Codeberg’s terms of use classify projects based on how their code lines were typed. I believe that what matters is genuine care and good engineering.
