Autonomous Micro-Enterprise Architectures (AMEA): Formalizing High-Concurrency Multi-Agent Orchestration and Zero-Marginal-Labor Scaling

Classical industrial organization and Coase's Theory of the Firm postulate that enterprise scale is constrained by internal administrative coordination costs, resulting in O(N) operational labor overhead for O(N) transaction throughput. Recent empirical phenomena—wherein micro-enterprises with fewer than five personnel scale to multi-billion-dollar transaction run-rates—demonstrate a structural breakdown of classical scaling limits. This paper formalizes the Autonomous Micro-Enterprise Architecture (AMEA), a systems framework integrating stateful multi-agent directed acyclic graphs (DAGs), deterministic API routing protocols, and bounded token-economic schedulers. We mathematically formalize state-transition invariants, present self-correction protocols under stochastic LLM non-determinism, and evaluate an empirical benchmark demonstrating a 94.8% reduction in marginal unit-transaction costs alongside a 31x increase in Revenue-Per-Employee (RPE). Finally, we demonstrate the architectural generalizability of AMEA across regulated e-commerce, algorithmic programmatic AdTech clearinghouses, and distributed autonomous service infrastructure.