Aethon: A Reference-Based Replication Primitive for Constant-Time Instantiation of Stateful AI Agents

Aethon introduces a reference-based replication primitive for constant-time instantiation of stateful AI agents. Existing agent systems typically reconstruct state across invocations, leading to latency, inconsistency, and limited scalability. Aethon reframes agents as long-lived, stateful systems that can be instantiated directly from reference without duplicating underlying data. This enables persistent identity, efficient cloning, and continuous execution across large-scale deployments. We present the architectural model, memory abstraction, and replication semantics underlying Aethon, and discuss implications for building production-grade agent systems with strong guarantees around performance, consistency, and governance.