Earlier quoted context omitted.
-1: as an ex-googler, I can say it was hard enough for Google itself to get its code to run, given gonzo infrastructure assumptions, proprietary libraries/languages, etc.
That speaks volumes of the code quality @ Google.
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.