You might be able to enforce constraints through logit manipulation, essentially a logical extension of Top-K/Top-P with a more complex conditional ruleset rather than (or in addition to) a probabilistic one. Also, in most models, logits go through a normalization stage where, theoretically, a lot more can happen than just normalization. All of that said, I have no idea how, or even whether, SudoLang achieves this.
SudoLang seems to target a specification that is likely to work across LLMs without pretraining or special tooling, and as such I don't see much about logit manipulation in this project. But your idea, especially the conditional ruleset, is for sure thought-provoking.
