[2604.12129] Aethon: A Reference-Based Replication Primitive for Constant-Time Instantiation of Stateful AI Agents

Computer Science > Artificial Intelligence arXiv:2604.12129 (cs) [Submitted on 13 Apr 2026] Title:Aethon: A Reference-Based Replication Primitive for Constant-Time Instantiation of Stateful AI Agents Authors:Swanand Rao, Kiran Kashalkar, Parvathi Somashekar, Priya Krishnan View a PDF of the paper titled Aethon: A Reference-Based Replication Primitive for Constant-Time Instantiation of Stateful AI Agents, by Swanand Rao and 3 other authors View PDF HTML (experimental) Abstract:The transition from stateless model inference to stateful agentic execution is reshaping the systems assumptions underlying modern AI infrastructure. While large language models have made persistent, tool-using, and collaborative agents technically viable, existing runtime architectures remain constrained by materialization-heavy instantiation models that impose significant latency and memory overhead. This paper introduces Aethon, a reference-based replication primitive for near-constant-time instantiation of stateful AI agents. Rather than reconstructing agents as fully materialized objects, Aethon represents each instance as a compositional view over stable definitions, layered memory, and local contextual overlays. By shifting instantiation from duplication to reference, Aethon decouples creation cost from inherited structure. We present the conceptual framework, system architecture, and memory model underlying Aethon, including layered inheritance and copy-on-write semantics. We analyze its impli...