This is still kind of a mishmash of early thoughts and I have a couple of different lines of thought, which I hope will come together. I'll start with a couple of observations:
1. Most programming languages and DSLs are uni-directional - the computer doesn't talk back to the human in the same language.
2. The mental models (not the language) humans use to communicate to each other, even when using a lot of rigor and few ambiguities, is often different than the languages and models used for computation.
The first idea is: there are some repeating structures in mental models. We think new concepts in terms of old by first thinking the structures (which are few and axiomatic, like the structure/function words in English) and then materializing the content, as well as refining the structures. E.g. I can say to a non-programmer that 'classes contain methods' and they kind of get the structure without knowing the content. In my mind this is represented as a graph, where the 'contains' relationship is an edge that connects two 'content nodes'.
[something called class] --(contains)-> [something called method]
Maybe structures can be made composable, and we can operate on graphs structurally, without knowing what the content means? While another operation might eventually figure out what the content means. The main assumption here is my thoughts are organized as graphs, where connections are both universal also domain specific but of few kinds. Can I talk to the computer in terms of such graphs?
The second idea is: I want to combine high level concepts and strategies from from somewhat different domains. E.g. if I know different strategies for 'distributing things into bins' (consistent hashing, sharding, etc.), I invoke this 'idea' manually whenever I have see a situation which looks like 'distribute things into bins' and make a choice - irrespective of scale. Can I get the computer to do this for me instead?
So the final thing here is to get to something like this: I take an idea (i.e. a node in a graph) from the distributed computing domain, merge it with a definition (another node) of a computation I created (e.g. persistence strategies), and have the computer offer options on how to distribute that computation (i.e. 'distributed persistence strategies'). Then I can make choices and combine it with a 'convert idea to machine code' strategy and generate a program. This is all a bit abstract at this point, but I'm also trying to find where this overlaps with prior art.