Each genre has a fairly tight envelope within which to operate. Regardless 90% of tracks never make it to the finish line because hobbyists haven't learnt them well enough to groove them out. If with a little help these tracks were all finished then bedroom producers will over time learn what works and be able to explore more.

I think the parent comment was saying that the problem is not quantity, but quality.

Warping my mind back into a hobby-enthusiast music producer mindset:

an MCP that generates presets for a limited pipeline with many sweet spots sounds... interesting?

To me, the idea of being able to have, say, a chain of a simple VA synth + delay + compressor and a very simple step sequencer, combined with prompting and a genAI model that spits out patches, sounds very endearing and interesting.

Much more interesting than Gemini or Suno for example.

Depends on the training and input space of course.

I deliberately described a limited setup, the controls of which could be described in less than a kilobyte.

Many dance music synth patterns could be described by simple means (tracker/step sequencer, looping, a few knobs).

That's what makes a lot of music interesting.

I can easily imagine a producer creating very individual and interesting output by unleashing the right models.

I think, just like with human producers, constraints liberate.

An AI controlling a very limited synthesis chain is more interesting than a very complex synthesis chain controlled by a human with no musical "vibe".