"- These systems can re-abstract and decompose things just fine. If you want to make it resilient or scalable it will follow whatever patterns you want to give it. These patterns are well known and are definitely in the training data for these models."

No? It absolutely does not do this correctly. It does what "looks" right. Not what IS right. And that ends up being wrong literally the majority of the time for anything even mildly complex.

" I'm sure we'll get some metrics soon on how functional these are for something like Windows, which, I believe is literally the world's single largest code base."

Now that's just not true at all. Windows doesn't even lay a finger to Google's code-base.

"and then make the results easy for a human to review."

This is in no way doable for anything not completely trivial from what an LLM produces. Software is genuinely hard and time-consuming if you want it to actually not be brittle and address the things it needs to and with trade-offs that are NOT detrimental to the future of your product.