I've done something similar for queries. Comments:

* Yes, this is a language, no its not a programming language you are used to, but a restricted/embellished natural language that (might) make things easier to express to an LLM, and provides a framework for humans who want to write specifications to get the AI to write code.

* Models aren't deterministic, but they are persistent (never gonna give up!). If you generate tests from your specification as well as code, you can use differential testing to get some measure (although not perfect) of correctness. Never delete the code that was generated before, if you change the spec, have your model fix the existing code rather than generate new code.

* Specifications can actually be analyzed by models to determine if they are fully grounded or not. An ungrounded specification is going to not be a good experience, so ask the model if it thinks your specification is grounded.

* Use something like a build system if you have many specs in your code repository and you need to keep them in sync. Spec changes -> update the tests and code (for example).