Actionable Coherence: Governing Systems Under Real-World Constraints

Systems across domains fail not primarily from lack of intelligence or resources, but from loss of coherence when operating under evolving real-world constraints. This paper introduces Actionable Coherence as an operational governance framework for maintaining viability during transitions. Actionable Coherence is defined as the measurable capacity of a system to accurately recognize constraints across scales, execute bounded transitions, select viable states under constraint, and preserve continuity over time. The framework integrates four closed-loop components: Recognition Fidelity (multi-scale constraint mapping with validation), Constraint-Bound Transition Architecture (CBTA) for structured movement, Constraint-Weighted State Selection (CWSS) for evaluating candidate states under constraint load, and the Usable State Progression Layer (USPL) for continuity and learning across cycles. Case studies across agriculture, governance, healthcare, and belief systems demonstrate a consistent failure geometry — delayed recognition, semantic drift, and unbounded transitions — and show how constraint-governed protocols produce bounded, recoverable outcomes. A measurement model, falsifiability criteria, and boundary conditions are provided for empirical evaluation. The central claim is operational: sustained viability emerges from structuring transitions under constraint, not from eliminating disruption or providing unbounded support.