Decision-Grammar

This is not about dance. This is a field note on evaluating non-verbal, pre-linguistic social understanding in AI systems. Why the dance floor can function as an evaluation surface for AI understanding 1｜Dance is rhythmic negotiation, not instruction-following In a dance floor setting, interaction is not driven by explicit commands. Coordination emerges through shared rhythm, timing, and fluctuating tension. This interaction mode reflects a class of problems future AGI systems must handle: non-verbal, non-logical, rhythm-driven coordination under uncertainty. ...

Entrepreneurial decision-making differs not only in ambition or speed, but in the structure of uncertainty it must absorb. A useful distinction can be made between chess-like, go-like, and poker-like decision grammars—not as cultural metaphors, but as operational models. Chess operates under conditions of near-complete information. All pieces are visible, roles are fixed, and objectives are explicit. Although tactical complexity can be high, uncertainty is localized and feedback is relatively immediate. ...

The concept of the Minimum Viable Product (MVP) is often treated as a universal principle of startup execution. Its actual effectiveness, however, depends on the structure of the decision environment in which it is applied. MVP originates from chess-like environments. These are contexts where objectives are explicit, feedback is rapid, and actions are largely reversible. Under such conditions, a minimal artifact can reliably test a hypothesis, and failure produces interpretable information. ...