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.
> Although i was under the impression that they usually preferred hand optimized assembly.
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.
And as a ffmpeg user with some old/weird hardware, I would much prefer click-and-hope support to no support at all. Ideally they’d have the resources for a real live human to hand-code assembly for every codec for every platform, but that’s probably not realistic. I’ll take what I can get and dust off my assembly skills if a click-and-hope implementation is close but not quite enough.
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?
Yes, contribution is what keeps a project alive. It's up to the people involved to maintain quality. That's management. Two different things, both important.
You can very likely do the click-and-hope on your own with a 20 $/month cursor/codex/claude/grok subscription.
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.
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.