Yes this is pretty common in large enterprise-ey tech companies that are successful. There are usually a small group of vocal members that have a strong conviction and drive to make a vision a reality. This is contrary to popular belief that large companies design by committee.
Of course it works exceptionally well when the instinct turns out to be right. But can end companies if it isn’t.
There is no free lunch. The amount of prompt writing to give the LLM enough context about your codebase etc is comparable to writing the tests yourself.
Code assistance tools might speed up your workflow by maybe 50% or even 100%, but it's not the geometric scaling that is commonly touted as the benefits of autonomous agentic AI.
And this is not a model capability issue that goes away with newer generations. But it's a human input problem.
My team has been prototyping something very similar with encoding business operations policies with LEAN. We have some internal knowledge bases (google docs / wiki pages) that we first convert to LEAN using LLMs.
Then we run the solver to verify consistency.
When a wiki page is changed, the process is run again and it's essentially a linter for process.
Can't say it moved beyond the prototyping stage though, since the LEAN conversion does require some engineers to look through it at least.
But a promising approach indeed, especially when you have a domain that requires tight legal / financial compliance.