The first topic of discussion at the 2025 Maintainers Summit has been in the air for a while: what role — if any — should machine-learning-based tools have in the kernel development process? While there has been a fair amount of controversy around these tools, and concerns remain, it seems that the kernel community, or at least its high-level maintainership, is comfortable with these tools becoming a significant part of the development process.

Sasha Levin began the discussion by pointing to a summary he had sent to the mailing lists a few days before. There is some consensus, he said, that human accountability for patches is critical, and that use of a large language model in the creation of a patch does not change that. Purely machine-generated patches, without human involvement, are not welcome. Maintainers must retain the authority to accept or reject machine-generated contributions as they see fit. And, he said, there is agreement that the use of tools should be disclosed in some manner.

But, he asked the group: is there agreement in general that these tools are, in the end, just more tools? Steve Rostedt said that LLM-generated code may bring legal concerns that other tools do not raise, but Greg Kroah-Hartman answered that the current developers certificate of origin (“Signed-off-by”) process should cover the legal side of things. Rostedt agreed that the submitter is ultimately on the hook for the code they contribute, but he wondered about the possibility of some court ruling that a given model violates copyright years after the kernel had accepted code it generated. That would create the need for a significant cleanup effort.