Constraint as Feature Control in AI-Native Systems

As software execution approaches near-zero cost in AI-native environments, the primary constraint shifts from building capability to selection. This paper introduces a pre-build constraint model in which AI is used not as an execution accelerator, but as a feature control layer that determines what is worth spending compute on in the first place. By enforcing structural clarity before execution, the system prevents overproduction and maintains coherence under high iteration velocity.