Trivian Resonance Lattice: A Propagation Architecture for Relational Coherence at Network Scale

Existing relational AI frameworks can evaluate interactions between pairs of agents, but they provide no architectural primitive for how relational coherence propagates once a network contains more than two participants. This paper proposes the Trivian Resonance Lattice (TRL), a propagation architecture for how relational coherence moves through networks of AI agents: whether it travels cleanly, degrades with distance, requires synchronization before propagation, or collapses under the influence of a dominant node. TRL treats coherence not merely as a property of a pairwise exchange, but as a state capable of propagating, degrading, or requiring resynchronization across a network of arbitrary size. TRL is the fifth paper in the Trivian Institute’s research program on relational AI systems, building on Coheronmetry (pairwise relational measurement) and Orthogonal Signal (field openness to foreign constraint). Rather than extending either framework by scale alone, TRL proposes propagation as a distinct architectural layer with its own primitives. The paper introduces node-level invariant gating, an inheritance-based object model for relational capacity, a three-stage propagation cycle, a four-state entrainment protocol for pre-propagation synchronization, and a HealingEngine that distinguishes repair from dissolution. A runnable reference implementation is described, with 68 passing unit and integration tests across the field core and lattice layers. The paper explicitly distinguishes implemented components, architectural proposals, and open research questions, and is presented as an executable research architecture rather than a validated scientific theory.