Agent-OS: Operating System Abstractions for Multi-Agent Orchestration

ABSTRACT

Current Agentic AI frameworks rely on high-level Python libraries that awkwardly manage memory, context windows, and tool execution at the application layer. We propose Agent-OS, a novel operating system abstraction layer designed specifically for multi-agent workloads. By pushing cognitive load balancing, semantic memory paging, and agent inter-process communication (IPC) down to the kernel level, Agent-OS drastically improves resource utilization. Empirical benchmarks demonstrate that running agent swarms on Agent-OS reduces memory overhead by 45% and increases concurrent agent capacity on standard hardware by a factor of three.