We also do "real work," and that uses libraries that use C(++) under the hood, like scipy, numpy, and tensorflow. We do simulations of seismic waves, particle physics simulations, etc. Most of our app is business logic in a webapp, but there's heavy lifting as well. All of "our" code is Python. I even pitched using Rust for a project, but we were able to get the Python code "fast enough" with numba.

We separate expensive logic that can take longer into background tasks from requests that need to finish quickly. We auto-scale horizontally as needed so everything remains responsive.

That's what I mean by "architected well," everything stays responsive and we just increase our hosting costs instead of development costs. If we need to, we could always rewrite parts in a faster language, provided that costs less than the development costs. We really don't spend much time at all optimizing python code, so we're not at that point yet.

That being said, I do appreciate faster-running code. I use Rust for most of my personal projects, but that's because I don't have to pay a team to maintain my projects.