Coherence as a Relational Invariant: Governing the Stability of Intelligent Systems

Coherence as a Relational Invariant formalizes a structural boundary condition required for stable intelligent behavior across biological and artificial systems. The central claim is that structural coherence is not an emergent property of optimization, computation, or scale. It persists only when inference is structurally prevented from internalizing or rewriting its own reference geometry. The manuscript introduces the Structural Coherence Architecture (SCA), which models intelligence as the interaction between an inference process and an external relational geometry defined through Structured Relational Geometry (SRG). Core constructs include: • Symbiotic Closure Condition (SCC) — enforcing reciprocal alignment between inference and relational structure • Relational Mass Principle (RMP) — governing convergence toward richer constraint fields • Write-back prohibition — preventing inversion of the inference–reference boundary In biological systems, this invariant preserves local coherence over time. In artificial systems, when enforced architecturally, it enables the maintenance of global coherence across users, contexts, and long interaction horizons without collapsing into internal model substitution. Interpreted architecturally, this boundary functions as a governance primitive for intelligent systems, preserving referential authority outside the model itself and enabling persistent coupling between inference and authentic user-supplied reference geometry. The invariant is stated in falsifiable form and proposed as a structural safety primitive for grounded, corrigible intelligent systems.