The breakthrough with C++ templates, was to provide a macro system which creates an AST for a static language, at compile time, using (surprise!) a template of the desired code. Contrast with the C preprocessor, which works on the token stream (there's more to it if you're curious, but in a way that makes it worse, not better).

Of course, a macro system operating on the AST is an older idea than C, this is one of the essential features of Lisp. But Lisps have always been dynamic languages. In some other timeline, there was an s-expression language for writing static programs, which used Lisp-style macros, and thereby avoided the problems with C++ templates. But we don't live in that timeline, it's a road not taken.

This template system enabled C++ programmers to write code which was generic over not just types, but features of types, and much else, it's all rather complex.

The problem, in essence, is that it was thought that template-expansion could be a decidable process implemented using a sub-Turing-complete language. So it was built using a second syntax, which was intended to be restrictive but flexible. Uh-oh!

C++ templates are Turing complete, as it turns out. So what C++ has is a second language. You could write your entire program in that language, and execute it at compile time. For everything you can do in C++, there's a second way to do it in templates, with its own syntax and semantics. Invariably, this language is much more verbose, and just... weird, in big and small ways. The sum of this is a system which is difficult to understand, and which generates notoriously terrible errors. This isn't intended as a complete summary of C++ template's shortcomings and weird features. That would take longer.

Zig just lets you run Zig at compile time. It's much, much better. Instead of trying and failing to make the problem decidable, Zig brute-forces the question by providing a branch quota: this is similar to gas in the EVM, or what Piccolo, a Rust implementation of Lua, calls "fuel". Comptime comes with a complexity limit, after which it quits, and which can be boosted for operations where the quota is insufficient.

So there aren't two languages to learn, just the one: Zig. That glosses over some things, like loop and switch constructs have inline equivalents for comptime, but the general premise holds.

There are other things which C++ makes easy which are less easy in Zig, like runtime polymorphism. But comptime is just a massive improvement over templates.

The libc qsort is type erased and only works on arrays. So to sort Widgets we note down how big a Widget is and how many there are, then we forget these are Widgets and we provide qsort with just a type erased pointer to the array [of Widgets], the size and count, and we provide a function pointer (we'll need to ensure it's suited for specifically sorting Widgets) to a custom function we wrote which receives a pair of type erased pointers [to Widgets] to decide which comes before the other.

A lot of performance optimisations are left on the table when we do this, and of course because it's type erased it also loses type safety. We can't reliably apply our algorithm to any other collection, and we can't easily re-use the comparison functions either.

The STL's generics mean you preserve type safety and you can use this for any (conforming) collection type, and you can re-use comparisons because those are generic too. Along the way you pick up the performance optimisations that were lost with type erasure.

Better still, all of this is optional. You can perform the type erasure explicitly if, for example, you have a thousand different types and want to emit code to sort them all even if it's a little slower, rather than emit a thousand different sort implementations, if the code size is crucial for example.

The one well-known "generic" algorithm in libc is qsort. But qsort only works with pointers, and so can only sort continuous containers. You can't sort a linked list with qsort. In contrast, the STL has a more general concept of iterators that know how to fetch their next element (and some iterators can do more than just that). This allows the STL to have a std::sort algorithm that works on arrays, linked lists, trees, and whatever other data structure you want to come up with.

So the crucial idea is that the STL provides a large set of algorithms that work on all containers. No matter what kind of weird container you have, as long as you can provide an iterator for it, you can use most of the ~100 different standard algorithms on it. You can sort, find specific elements, partition, find the max element, filter elements, etc.

And the idea also goes the other way around. The STL also provides common containers that you'll need, such as linked lists, growable arrays, associative containers, strings. Of course, all the STL algorithms work with the STL containers.

Then, if you want to write your own algorithm, you only need to write it once in terms of iterators and then you can use it with all the different containers. No need to write the same routine twice.

The last big accomplishment is that all this can be done with almost no runtime overhead. All the types are resolved at compile-time, and generic algorithms can be specialized if you have a more efficient implementation for a specific container. This means that if you wrote a manual implementation of an algorithm that specifically matches one container, it would not be much faster or consume fewer resources than just using the generic STL algorithm. At the time the STL was originally incorporated, I think this was unique and no other language was actually capable of doing this.