I'm sorry but you really sound like you judge APLs from an outsider pov. For sure, it's not job security that's keeping APLs afloat, because APLs are very easy to learn. A pro programmer would never use K or any APL. But pro mathematicians or scientists needing some array programming for their job will.
I have been a programmer, scientist, etc, at various times in my life and I have programmed in J. I don't think there is any compelling reason to use J over Matlab, R, or Python and very many reasons not to. Vector languages are mind expanding, for sure, but they have done a very poor job keeping up with the user experience and network effects of newer languages.
A few years ago I wrote a pipeline in J and then re-implemented it R. The J code was exactingly crafted and the R code was naive, but the R code was still faster, easier to read and maintain and, frankly, easier to write. J gives a certain perverse frisson, but beyond that I don't really see the use case.
I disagree. For the stuff I'm doing, I've been rewriting the same 1-screen program in different ways many times. J made that easy, R would make that much more tedious since I'd have >250 lines instead of 30. Of course if I'm doing something for which R has libs, I'll do it in R. Additionally, I'll very probably end up rewriting my final program in another language for speed and libs, because by then I'll know precisely what I want to write. IMO, the strength of array languages lies in easy experimentation.
