Would love some critique of my thoughts.

Thats very interesting view. I actually had some experience with that kind of dense language for specifying when I start testing using two llms to code: one to instruct the coding agent and the agent itself. The instructor start creating quite dense english that sometimes I could not easily understand, but seems to make the coding agent pretty efficient in understanding the requirements.

This pretty much mirrors my experience so far. LLMs are trained in the semantics of experts, but only experts can actually wield them correctly. It allows us to work with the shapes in our heads (shapes the AI understands now) rather than having to convert them into a collection of things expressible in a programming language (which the AI can now do mechanically).

The next frontier will likely be some kind of AI-first IR that contains high level abstractions you can reshape and reason about with the AI (rather than creating documents - which are lower compression) before it commits to an implementation language.