Except computers attempt to model mathematics in an ideal world.
Unless your problem comes from something side effects on a computer that can’t be modeled mathematically there is nothing technically stopping you from modeling the problem as mathematical problem then solving that problem via mathematics.
Like the output of the LLM can’t be modeled. We literally do not understand it. Are the problems faced by the SRE exactly the same? You give a system an input of B and you can’t predict the output of A mathematically? It doesn’t even have to be a single equation. A simulation can do it.
I think the vast majority of SRE problems are in the “side effects” category. But higher level than the hardware-level side effects of the computer that you might be imagining.
The core problem is building a high enough fidelity model to simulate enough of the real world to make the simulation actually useful. As soon as you have some system feedback loops, the complexity of building a useful model skyrockets.
Even in “pure” functions, the supporting infrastructure can be hard to simulate and critical in affecting the outputs.
Even doing something simple like adding two numbers requires an unimaginable amount of hidden complexity under the hood. It is almost impossible for these things to not have second-order effects and emergent behaviour under enough scale.
Can you give me an example of some problem that emerged that was absolutely unpredictable.