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

Ronald Coase's Theory of the Firm holds that enterprise scale is constrained by internal administrative coordination costs, which historically grow superlinearly with transaction volume, forcing operational labor to scale roughly in proportion to throughput. This paper formalizes Autonomous Micro-Enterprise Architectures (AMEA): a systems framework in which stateful multi-agent directed acyclic graphs (DAGs), deterministic API routing, and bounded self-correction loops replace human administrative triage in high-concurrency transactional settings. We (1) formalize the micro-enterprise as an asynchronous multi-agent finite state machine with explicit state-validation predicates; (2) derive, under stated independence and bounded-drift assumptions, a bound on the probability that an uncorrected state reaches settlement, presented as a Proposition rather than an unconditional theorem; (3) describe a four-layer reference runtime; and (4) present an illustrative, parameter-driven simulation — not a production benchmark — that quantifies how the modeled cost structure shifts from variable human labor toward fixed compute under stated assumptions. We discuss two real-world reference points for ultra-lean, AI-native firms, Medvi and Midjourney, with appropriate sourcing and caveats, and outline a doctoral research agenda to test the model's predictions against real operational data.