I think Python is probably way better suited to be the superglue you mention, and in many areas it already serves that function. Many Python libraries are high-level bindings for low-level C/C++/Fortran (or recently, Rust) libraries. Examples are numpy, scipy, tensorflow, PyQt, ....
Rust is great in the sense that it is very suitable for being embedded into other software as it doesn't have a runtime system (like e.g. Golang) and can be compiled for almost any architecture. Rust's usability for "regular" programmers and technical users is horrible in my opinion. I e.g. worked with scientists a lot (and was one myself) and in my lab everyone could wrap their head around Python in a couple of days and become productive very fast, whereas most people would throw in the towel when they had to write low-level code in C/C++. In terms of learning curve and complexity I would put Rust somewhere in the same ballpark with C++. There are many differences and Rust has a much better developer experience as it has a modern package manager and the toolchain is much nicer, but it's still a low-level language with many intricacies.
Rust is great in the sense that it is very suitable for being embedded into other software as it doesn't have a runtime system (like e.g. Golang) and can be compiled for almost any architecture. Rust's usability for "regular" programmers and technical users is horrible in my opinion. I e.g. worked with scientists a lot (and was one myself) and in my lab everyone could wrap their head around Python in a couple of days and become productive very fast, whereas most people would throw in the towel when they had to write low-level code in C/C++. In terms of learning curve and complexity I would put Rust somewhere in the same ballpark with C++. There are many differences and Rust has a much better developer experience as it has a modern package manager and the toolchain is much nicer, but it's still a low-level language with many intricacies.