Taking an extreme helicopter view I think I can see it, but on the other hand I'm not convinced it's a very interesting observation. Throughout history we used machines to make more complicated machines.

Edit with this quote:

Because you only have to provide Software 1.0 implementation for a small number of the core computational primitives (e.g. matrix multiply), it is much easier to make various correctness/performance guarantees.

This is true, but it raises another question which is (to me) comically hand waved aside:

how do you make correctness guarantees of the output of the neural net? It's not addressed, probably because it's very hard to do so.

It's like the NAND gates inside CPUs and GPUs. Since they are so simple building blocks, they are very easy to verify.

It does not follow that the business logic I write to run on these things, is easy to verify.

The same goes for neural nets, but more so.

I'm not saying these new AI tools aren't useful, they are. But it's easy to misunderstand what they can do.