You're talking about logic - SQL is basically a "logic language", it's just not entirely evident.
Logic programming was the AI paradigm for more or less most of the 20th century and has fallen out of favor.
Many people have talked about combining the neural net/extrapolation/brute-force approach with the logic approach. That hasn't born fluid yet but who knows.
There is somewhat renewed interest in hybrid approach. See, for example, DeepProbLog[1][2][3] - a combination of Deep Learning and probabilistic logic.
I don't think there ever has not been interest in hybrid approaches - I think each I've looked over ten or more years, there was at least one hybrid thing (Neural Turing Machines comes to mind). I think the problem is no one has figured out a way to make them "work".
Or not even that they don't function but you need a way to demonstrate that such things are "really good", that they solve real problems that neither "business logic system" (the real existing remnant of GOFAI) nor neural networks can solve. And the key both logic systems and neural networks have is how they pretty standardized. logic systems are like regular programming and neural networks have their train/test/verify cycle understood (and even with that, they're probably overused/misused at this point given the hype).
BPE as used in NLP might count as a successful hybrid approach. Maybe the hybrid approaches that work out will be really specific purpose like that for a while.
Logic programming was the AI paradigm for more or less most of the 20th century and has fallen out of favor.
Many people have talked about combining the neural net/extrapolation/brute-force approach with the logic approach. That hasn't born fluid yet but who knows.