Multi-agent systems (MAS) scaling toward large deployment densities encounter significantcoordination overhead and high bandwidth costs from verbose state communication. We presentan architecture enabling linear O(N ) bandwidth scaling and low-latency coordination throughsemantic bitmask encoding. Our design adapts semantic validation concepts to dynamic, statefulagent coordination, coupling: (1) a fixed 64-bit feature encoding with frequency-based schemapruning; (2) a bicameral control/data separation using an in-memory SchemaManager for asyn-chronous schema consensus and WebSocket/HTTP transports for synchronous bitmask deliv-ery; and (3) a hierarchical weighted arbitration mechanism for decision synthesis. We presentan implemented 4-layer architecture for general-purpose distributed environments, alongside aconceptual 5-layer design incorporating pattern detection tailored for financial trading envi-ronments. Evaluation using the open-source reference implementation demonstrates a compact24-byte wire layout, presenting an estimated bandwidth reduction compared to natural languagebaselines and a 3.7× optimization over dynamically computed JSON serialization (∼89 bytes).Theoretical sharding mechanisms, advanced pattern generation layers, and information-theoreticanalysis bounds are identified as areas for future theoretical and development work.Keywords: multi-agent coordination, semantic compression, bitmask protocols, low-latencycommunication, scalable consensus, financial trading systems