What Curt is saying here is important, but easy to miss if you are not used to...

What Curt is saying here is important, but easy to miss if you are not used to thinking in operational grammar.

AI struggles with reasoning because most human language is fuzzy and open-ended. Words shift meaning. Emotions are vague. Ideas are layered with intuition. That makes it hard to calculate anything with certainty.

But when we give AI clear, operational referents, concepts as stable and causal as numbers in math or functions in programming, we give it what human reasoning often lacks: Closure. A clean system it can work inside of, without ambiguity.

Here is a practical example: Take something fuzzy like emotions. Normally, we just “feel” our way through them. But if we define them operationally, by what they cause people to do, how they drive behavior, how they predict choices, we can translate them into a system that can be measured, modeled, and understood.

Think of it like a Rosetta Stone for fuzzy information: You take something vague (emotions, culture, personality), and make it comparable to hard systems like logic or computation.

That is what operational language does. And that is what Curt means when he says we can give reasoning “closure.”

It is not philosophy. It is a scientific blueprint for building linguistic tools that work, especially tools like AI that need precision to function at scale.