I actually have very similar experiences. I want to like Julia and I look at it from time to time. The hype is always that it allows one to write C-speed code with the simplicity of python, without the idiosyncrasies of numpy. But every time I look I find just as many little things to look out for if one cares about performance, don't use abstract types is another one.

I understand why this is the case and I don't have an issue generally with it, but considering that I know Python well, and know how to speed up Python using numba, pythran or cython, I don't see what I would gain by investing in Julia.

Instead I've now decided to learn Rust, as it fills a different niche and I can use it for writing python modules for some of my bottleneck code.