Even if the different domains are different it should still be possible to generalize the basic framework and strategy used. I imagine layers of models each constrained by the upper metamodel and a fitness function feeding a generator to create the next layer down until you reach the bottom executable layer. In a sense this is what humans do no? Begin with the impact map model , derive from that an activity model, derive from that a high level activity support model, derive from that acceptance criteria, derive from that acceptance test examples, derive from that a low level interaction state machine an so on...
In the human case I belive the approach modelled by the kanban katas seems appropriate. Nested stacks of hypotheses to try in a disciplined PDCA cycle. BR John
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