I don’t find that to be true with Julia. Keep in mind that Julia is intended to not only replace python and R but also C++ in a science setting. The academic programmers who write the high performance code parts usually do this in C/C++ and Fortran and thus tend to be quite familiar with a lot of low level computer science stuff.

Looking at generated assembly code for a Julia function is a pretty normal thing to do. I am an old C/C++ developer and find myself very much at home with Julia.

Sure I have used Python and Ruby before but those always make decisions around memory layout and code generation inaccessible.

Thinking about Julia as yet another Python, R, Ruby or a JavaScript is just wrong. It doesn’t really fit existing categories well.