On Sun, May 31, 2026, 4:24 PM Dan Eble <[email protected]> wrote: > <Snip>
As a reviewer, I strongly desire two things: > > 1. openness about the origin of the code I'm reviewing > 2. accountability of the human submitter (not reviewers) > for the code that is merged > > For the MR that is in draft now, there were tells in the patch, but I > had to ask the submitter twice before he confirmed that it was > "AI-assisted." To streamline this in the future, I propose configuring > a template for default MR descriptions something like this: > > ##### Description > > <!-- Describe your motivation and your work briefly > to orient reviewers. If you have not described > your commits well, go back and do that first. --> > > ##### Question > > What percentage of this work is AI-generated? <!-- 0-100 --> > > Do you think that would effectively address that specific concern? > > --- > > Another situation arises at the confluence of these things: > > * Anyone with middle-class money and some patience can > rather easily submit a high-line-count patch that solves > a narrowly defined problem and passes regression tests. > > * Unless the submitter first examines the generated code > carefully to confirm that it aligns with his intent more > broadly, that kind of generated code demands even more > of reviewers' time and attention than before. > > * The number of active reviewers (those who have been > leaving comments) is currently small. > > * Our current "countdown" policy effectively treats > silence as approval, and moves changes forward as long > as there are no objections within a certain time. > > Therefore, I suggest adopting a new policy: AI-generated program code > does not automatically move forward without a human reviewer's > acknowledgment. It should be full acknowledgment, not, for example, > "C++ LGTM; don't know about Scheme." > > It would fall to the "patch meister" to help people follow this policy > and to allow sensible exceptions, such as if a contributor with a good > record vouches for the quality of his own AI-generated submission in an > area where he has developed expertise. > > --- > > Is there any other guidance that we active contributors should follow > when dealing with AI-generated submissions? The floor is open. > I totally agree with you, Dan. Ai generated code MUST be.clearly identified. And it MUST be approved by human reviewers. I trust Dan, and David, and Werner, and Harm, and other regular contributors. And I trust new contributors that work through the issues of getting patches approved. I believe that most new contributors start with relatively low-line-count patches. And only get.to high-line-count patches when they have understanding and capability with the lilypond codename. AI-generated patches can easily ne larger, but there is no.guarantwe that the AI agents actually reflect appropriate understanding of the code base. Adding them to LilyPond will add cognitive debt, which I believe is much worse than technical depth. When AI -generated code is created, there is a strong likelihood that nobody in the world understands why that particular code works and is an appropriate solution for the problem under consideration. This makes reviewing AI-generated code essential, and also supremely difficult. If the submitter used AI to supplement the work, and can explaon.how this work is conceptually and implementationally correct, then the review may be more feasible. Carl
