sorry, but that's not how code works. It's true that code quality could be terrible but in fact Google is famous/notorious for extreme code review at the line-by-line granularity, plus comments, design docs and more.

The real issues are (again) in dependencies and complex tooling. You can have beautiful code and then in the middle of it, an ML inference call that assumes a crazy ML model and set of hardware to run it on.

You ought to be able to arrive at the same conclusion, then, with these LLMs. Without arrays of GPUs, it would take thousands of years to train one. Without a corpus of billions or trillions of words, one would produce output of very limited utility.

I think you have to consider that some things are systems, and it is the assembly of their components that imparts the true quality.

It's not poor code quality to depend upon available dependencies.