If anything, Julia becoming popular with academics makes me extremely skeptical about its missing guardrails. Obviously anecdotal, but I have many years of experience working with academics and statisticians and I know to be wary when they suddenly like a new technology. Usually it's because it makes it easier to swallow errors somehow, or because their friend wrote it and sent them an email about it.
Ha! That's hilarious. Yeah, I've seen some real horrorshows of programming in my field.
I think it's important to realize, though, that academics do have a special use-case when programming. That is, academics don't pick e.g. Python because they are bad programmers and don't know what they are doing, but because Python is a good fit for their needs. I see Julia as an excellent - near-perfect, in fact - academic programming language. That Julia excels at this use case does not mean it's bad at everything else.
Just giving you a hard time... I do think the performance improvements alone make Julia a serious contender. I've seen a lot of valuable engineering time spent rewriting algorithms in C++ for scientists who know Python. To speed up their iteration loop without bringing in performance experts would be great.
