I'm curious if they used LLMs to do the tedious work of porting the (de/en)coders to different architectures, and how useful they are here.
So far, Claude has helped find missing backports for the upcoming 9.0 release."
Although i was under the impression that they ususally preferred hand optimized assembly. Not sure what their LLM/AI contribution policy looks like compared to other fundamental OSS projects.
Using LLMs/agents to do gap analysis and fill boilerplate doesn't rule out also reviewing the output and hand-optimising. That is how the tools should be used (if you aren't being a luddite like me and not using them at all) rather than click-and-hope vibe-coding.
The problem I see is that LLM use deters many potential contributors. I understand that in your use case this is not an issue since you prefer working code over theoretical contributors (as said makes a lot of sense), but I am noticing this in many projects that transitioned hard into an AI dependency. It puts a barrier to some people. If 99% of a project's contributions are via AI, is that project still alive?
edit: actually if you have the weird/exotic hardware you’re in the best position to do so as you can actually test whatever the coding agents would shit out.
only losers use tokens?
both play just similarly to the original phrases