Consider a problem like finding potential solutions to an equation. The way that AI today would solve this problem is to give you an algorithm that tells you "yes there's a solution", or "no there isn't," maybe with a somewhat-bogus quantification of confidence. An SMT solver would instead tell you "yes, here's a satisfying assignment", "no, there's no satisfying assignment", or "I don't know." In other words, existing PL techniques can guarantee that they'll never give you the wrong answer, while all of the guarantees in AI are only probabilistic.

At the same time, though, we've been able to make--and deploy on production codebases--significant improvements in compilers. Production software exists to automatically tune BLAS or FFT routines to your particular machine. We can automatically find bugs and generate evil testcases with concolic execution and whitebox fuzz testing. We're nearing the point where a compiler could superoptimize an innermost loop and develop faster--and provably correct--code than a human writing assembly by hand (it's already possible for small loops). Compilers and related tooling are already amazing tools in their power, and we've done stuff that's in many ways as or more impressive than AI, and yet our achievements are largely ignored outside our own small community.