You can ask any professional python programmer how much time they've spent trying to figure out the methods that are callable on the object returned by some pytorch function, and they will all tell you it's a challenge that occurs at least weekly. You can ask any C++ programmer how much time they've spent debugging segfaults. You can ask any java programmer how much time they've spent debugging null pointer exceptions. These are all common problems that waste an incredible amount of time, that simply do not occur to anywhere close to the same extent in Rust.
It's true that you can get some of these benefits by writing tests. But would tests have prevented the issue that OP mentioned in his post, where acquiring a mutex from one thread and releasing it from another is undefined? It's highly doubtful, unless you have some kind of intensive fuzz-testing infrastructure that everyone talks about and no one seems to actually have. And what is more time-efficient: setting up that infrastructure, running it, seeing that it detects undefined behavior at the point of the mutex being released, and realizing that it happened because the mutex was sent to a different thread? Or simply getting a compile error the moment you write the code that says "hey pal, mutex guards can't be moved to a different thread". Plus, everyone who's worked on a codebase with a lot of tests can tell you that you sometimes end up spending more time fixing tests than you do actually writing code. For whatever reason, I spend much less time fixing types than fixing tests.
There is a compounding benefit as well. When you can refactor easily (and unit tests often do not make refactoring much easier...), you can iterate on your code's architecture until you find one that meshes naturally with your domain. And when your requirements change and your domain evolves, you can refactor again. If refactoring is too expensive to attempt, your architecture will become more and more out-of-sync with your domain until your codebase is unmaintainable spaghetti. If you imagine a simple model where every new requirement either forces you into refactoring your code or spaghettifying your code, and assume that each instance of spaghettification induces a 1% dev speed slowdown, you can see that these refactors become basically essential. Because 100 new requirements in the future, the spaghetti coder will be operating at 36% the productivity of the counterfactual person who did all the refactors. Seen this way, it's clear that you have to do the refactors, and then a major component of productivity is whether you can do them quickly. An area where it's widely agreed rust excels at.
There are plenty of places we can look at Rust and find ourselves wanting more. But that doesn't mean we shouldn't be proud of what Rust has accomplished. It has finally brought many of the innovations of ML and Haskell to the masses, and innovated new type-system features on top of that, leading to a very productive and pleasantly-designed language.
(I also left this comment on reddit, and am copying it here.)