I practice something like adversarial uncertainty? I'm borrowing "adversarial" from machine learning and agentic systems, it's about theoretical opposition, not about being moral enemies. the approach is one in which I read the thing, and then read again trying to prove that reading wrong, and then read again trying to prove both of those readings wrong from a third angle, and so forth, until I've sort of scanned the entire space of possible morphisms represented by the conversation.
and then I hold those all open, in superposition. I don't land on a collapsed reading. the whole thing stays in a sort of provisional geometry. when I run *meaning* through the system, it's running it through all of these superposed filters/funnels/whatever, and I'm looking at the spread and the color and the polarization of the light that comes out the other end, observing the scatter. the output is always a range of output, not a *point*. sometimes, in a realtime moment, you can completely transform the output with two small changes to the system. can't happen if the whole system doesn't stay superposed.