Agent Operating Systems (Agent-OS): A Blueprint Architecture for Real-Time, Secure, and Scalable AI Agents

Large-model (LM) agents are proliferating across domains, yet current systems remain ad-hoc pipelines without operating system (OS)-level guarantees for scheduling, memory, real-time responsiveness, and end-to-end security. Today's agent architectures resemble the pre-OS era of computing—a chaos of duplicated solutions lacking fundamental abstractions for resource management, isolation, and coordination. Existing frameworks (e.g., tool-calling, Model Context Protocol, Agent-to-Agent messaging) address isolated aspects but lack a unified, security-by-design, latency-aware foundation suitable for enterprise and safety-critical deployments. This paper introduces the conceptual \textbf{Agent Operating System (Agent-OS)} as a computational substrate for agentic workflows. We present this not as a system fully realizable today, but as an architectural North Star to guide the next decade of agent infrastructure research. We propose a unified requirements specification encompassing functional requirements (lifecycle, memory, tools, orchestration, observability, safety, governance) and non-functional properties (reliability, scalability, interoperability, compliance, real-time, security), extended with explicit latency classes—Hard Real-Time (HRT), Soft Real-Time (SRT), and Delay-Tolerant (DT). An abstract layered architecture is defined, comprising Kernel, Services, Agent Runtime, Orchestration, and User layers, with cross-cutting concerns for security, governance, and observability. Following a system engineering requirements-driven methodology, we (i) trace historical roots and survey emerging 2025 systems, (ii) synthesize requirements with latency taxonomies, (iii) formalize \emph{Agent Contracts} for portability and enforcement, and (iv) map these to the layered architecture. The Agent-OS provides a blueprint for scalable, interoperable, and trustworthy agent deployment for next-generation Agentic-AI-powered smart cities, autonomous systems, and enterprise AI - even as full realization may require years of collective research effort.