Continuity-Bounded Coordination: Why Multi-Agent Systems Still Drift

Continuity-Bounded Coordination: Why Multi-Agent Systems Still Drift Most current AI orchestration stacks solve connectivity, not coordination. Transport protocols connect models to tools. Workflow engines connect services to triggers. Memory layers persist context per agent. None of them define a bounded coordination semantics across heterogeneous agents operating over time. The core problem is not message passing. It is state drift under irreversible cognitive transitions. When multiple agents — LLMs, executors, bots, humans — interact with shared corpora or shared operational state, three structural effects accumulate. First, semantic divergence: different agents converge to different interpretations of the same system state. Second, partial propagation: state updates reach some stores but not others. Third, cold-start amplification: newly initialized agents begin from unboundedly stale context. These are not edge cases. They are the default operating regime of any multi-agent syste