It's quite rare for problems to be dominated by hot loops in the same way that matrix multiplication is.
Think about something like speeding up a compiler or a web server or a spreadsheet. There's no 50-line function that you can spend a few hours optimising and speed up the whole thing.
That's part of the reason why Python programs (except maths heavy stuff like ML) tend to be so slow despite everyone saying "just write your hot code in C". You can't because there is no hot code.
This advice dates back to when Python was primarily used by scientists to drive simulations. I remember hearing this advice in the early 2000s as a physics student using vpython to drive N-body simulations. They told us to do the physics in C, but everything else in Python due to the simulation math taking too long in raw Python. We couldn’t make the visualization run at a reasonable frame rate without those optimizations.
These days Python is being used for everything, even things without hot loops as you note. Yet the advice persists.
Think about something like speeding up a compiler or a web server or a spreadsheet. There's no 50-line function that you can spend a few hours optimising and speed up the whole thing.
That's part of the reason why Python programs (except maths heavy stuff like ML) tend to be so slow despite everyone saying "just write your hot code in C". You can't because there is no hot code.