It does not look like it due to its largest target audience (hardcore math nerds writing proofs), but Lean 4 is actually a meta-programming language, like Racket -- it is one single unified language for programming, meta programming, and theorem proving, on top of a small core. The implementation of Lean is almost entirely written in Lean, including components like LSP servers, the compiler itself, many efficient data structures, etc. It is a key use case to write real world programs, because the implementation itself is such a program.

In the long past, Lean 3 had this idea that you could use one language both for writing proofs, and writing proof automation -- programs that manipulate proofs and automatically do things. Like in the article itself, the 'grind' thing-a-mabob is proof automation. (Roqc has two separate languages for proofs and proof automation.) But there was a problem: Lean started as a theorem prover and the implementation tried to move towards "executing programs" and it didn't work very well and was slow. The prototype compiler from Lean 3 to C++ ran out of steam before Lean 3 got canned.

Lean 4 instead went and did things the other way around: it started as a programming language that was executable. The Lean 4 compiler was self-hosted during development for a long-time, way before anyone ported any big math proofs to it from Lean 3. Why did they do this? Because the key insight is that if you want to write programs that manipulate proofs (AKA programs), the best thing to have at hand is have a robust general programming language -- like Lisp or Racket. And so Lean is macro based, too, and like Racket it allows you to have families of languages and towers of macros that expand as deep as you want. Meta programs that write programs that write programs, etc...

So in Lean you write Lean programs that can manipulate Lean ASTs, and you write "reader macros" that allow you to use domain specific syntax right inside the source file for any kind of math or programming-language DSL you want. And all those macros and meta-programs are compiled and executed efficiently just like you'd expect. Finally, there is a total fragment of the language that you can actually write proofs over and reason about. And there is a big library called "mathlib" with lots of macros for writing math and math proofs in this language-framgent-we-can-reason-and-prove-things-with.

Lean 4 is very close in spirit to the Lisp idea, but modified for math proving and generalized programming. It's very unique and powerful.

> Are writing our next program in Lean then? Where does that run?

That first question is hard to parse. If you mean "Are you writing your next program in Lean then?" then: No, but in principle we could, it runs on each OS we use (Windows and Linux, standard x64 hardware). If you mean something else, I can't figure out what it would be.

> Either we prove things in the language we want to use

Sure, I mentioned SPARK/Ada. There are systems for C, Java, and others that also work and understand their types so you don't have to add extra modeling.

> which means modelling the behavior of the things we use in that language

It would already be done for you, you wouldn't have to model Ada's integers in SPARK, for instance.

> we prove things in Lean, but then cannot apply that to an actual implementation, because of issues like the one above.

https://lean-lang.org/doc/reference/latest/Basic-Types/Fixed...

If you knew your target system was using fixed-width integers, you'd use this.

yes, Lean is executable, and the proof of natural numbers runs with arbitrary width integers. they're stored as tagged pointers, with upto 63bit numbers being normal numbers, and larger numbers become GMP encoded.

Lean is actually pretty easy to learn and code in; also, if you are not interested in extreme performance, it is pretty much ready for basic applications (not sure about async and co.).

The problem is that you want to be doing all your coding monadically (so that it looks like the familiar imperative style), and I think there are still many problems about doing proofs on monadic code.

> Do you realize that making + do what the ordinary mathematical + does, is quite expensive? It requires arbitrary precision arithmetic and hence, potentially, memory allocations.

Yes I do. It's an acceptable cost in most cases (you will note much of the world runs on Python, a language in which + does behave sensibly, these days), and dangerous optimisations should be opt-in rather than opt-out.

In the worst case you should at least make your language fail-stop definite by making it error when the result of + is too large rather than silently continuing in an invalid state.