It is odd that you would say that, because it is a very common complaint about languages with dynamic typing. As the program grows larger static typechecking becomes more and more helpful.
Regardless, python has tools to do that. Instagram and Dropbox in particular have written quite a lot about their internal usage and built and open sourced additional tooling (e.g. MonkeyType - that lets your code type annotate itself).
How about organizations that hit the scaling point, but are not big enough to invest into tooling like that?
It's exactly the kind of tooling that makes your life easier if you have multiple teams and wanted to start enforcing static type checks with MyPy and having an IDE that understood your types.
So before Python had types was it hard to scale or not?
Seems like you are defending "Python with types and lots of tooling" rather than Python "nice and simple language (until not)".
It's kind of like saying that AMD processors or Microsoft Word are hard to scale - it's not entirely meaningless as a criticism but it's close to it.
Python is not a language for writing ultraperformant multi threaded code but, of course, that's not what it used for or was ever intended to do and is an entirely separate issue to scalability.
Reasonable people disagree about well defined, important matters.