Important to think about the system as a whole, as a distributed cognition system.
The brain actually is doing a LOT of the work! The external spaces are part of the system, but the data model encompasses more than the scratches on paper or on the whiteboard. We can gain insight into this by noticing how things cluster or repeat over time across different media, both in the head and in the world.
This might be one reason that Andy Matuschak and Michael Nielsen think that Z: The most transformative insights must come from a single "mind". Because it's really challenging to (or we haven't yet figured out how to) enable a medium with data model properties of compression, context, and compositionality that spans multiple minds; a distributed system that enfolds or spans more than one mind and their workflow.
Our current workaround is to have people spend LOTS of time together in an intense collaboration to get to the point where this is possible, or to have people who are very similar already get together.
But there is a very significant barrier to team-based Convergence because of this bottleneck of not being able to have a shared "dataset" of ideas that satisfy the properties. Our external representations that are shareable lack one or more of those properties. We've designed models for some that could have these properties, but nobody will use them.
I'm experimenting with sharing parts of my personal Roam graph, where I do most of my knowledge work, trying to understand and create systems that support creative knowledge work, especially ones that are open and sustainable.