Only thing "interesting" to me there would be the automatic differentiation bugs ...but is there any argument as to them being the fault of the language, instead of just poor engineering from the library developers' part?

I mean, one can't expect all algorithms to work correctly with all datatypes just because the compiler allows that code to run ...you write tests and guarantee numerical stability for a small subset of types you can actually do it for, and then it's the code's consumers' job to ensure it work with types it's not documented to work and such, no? ...Julia is quite a dynamic language, JITed or what not, its semantics are closer to Python and Lisp than to Rust or Haskell ...maybe don't expect guarantees that aren't there and just code more defensively when making libraries others depends on?

Probably the Python + C(++) ecosystems works better bc their devs know they are working in loose, dynamic and weekly typed shoot-your-foot-off type languages and just take action and code defensively and test things properly, whereas Julia devs expect the language to give them guarantees that aren't there.