Or maybe extend the traditional categories of macro and micro with another one, call it 'nano'... the micro agent indicates where each unit ought to be in 9 frames, and the nano agent figures out how to take them there. Since the timescale is so short, the agent could brute-force enumerate possible moves to some extent and figure out which is optimal, like chess AI. Or use a separate network.

I guess that's inelegant when a deep network already has its own concept of fine-grained versus coarse-grained layers, and should be able to do this on its own with the right training method.

That sounds like an interesting research angle. The thing about AI research is there are so many open ends there are essentially unlimited research options. If you can pose it as a problem and identify a reasonable programming approach then you have an avenue for AI research. Deep Learning isn't the end of AI research. It is the beginning.