A new paper proposes the Agent Operating System (AOS), a vendor-neutral reference operating architecture for distributed agentic systems. The work, submitted to arXiv on 4 Aug 2026, aims to fill a gap in how AI agents are governed and coordinated across complex environments.
The paper, titled "The Agent Operating System (AOS): A Reference Operating Architecture for Distributed Agentic Systems," was written by Ankur Sharma and Deep Shah. It carries the arXiv ID 2608.03214 and falls under the cs.AI category. Version 1 was submitted at 06:50:49 UTC on the same date. The PDF file size is 3,698 KB. A DOI is available via the arXiv-issued DataCite link, with registration pending.
Why an Operating Architecture Now
Large language models have shifted AI from isolated prediction services into components of long-running, distributed systems. Agentic systems now reason, invoke tools, retrieve external state, delegate tasks, and act on behalf of users and organizations.
The existing ecosystem includes agent frameworks, workflow engines, model-serving platforms, memory systems, communication protocols, and observability tools. These technologies improve execution, but they lack a stable, implementation-independent operating architecture.
That missing layer is what AOS targets. The paper argues that current tools do not provide a consistent way to govern intent, select capabilities, preserve authority across delegation, control uncertainty, coordinate runtime behavior, or reconstruct why consequential actions occurred.
Two Planes Inside AOS
AOS is built around two internal planes. The Control & Governance Plane handles intent, policy, trust, authority, confidence, auditability, observability, and human oversight.
The Runtime & Coordination Plane manages agent lifecycle, workflow coordination, model and tool routing, context and memory coordination, scheduling, traffic management, and runtime assurance.
These two planes work together to form the operating core of a distributed agentic system. The paper specifies AOS concepts, invariants, interface objects, optimization objectives, deployment profiles, and reliability responsibilities.
Boundaries and Integration
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AOS does not claim to cover everything. Platform services such as Linux or Windows, container runtimes, and physical infrastructure sit outside the AOS boundary.
Integration with these external components happens through explicit interfaces. This keeps AOS focused on the operating layer while remaining compatible with the broader infrastructure stack.
The authors are careful not to overstate the proposal. AOS is not presented as a replacement for existing frameworks or infrastructure. Instead, it is proposed as the operating architecture for composing heterogeneous components into governable, reliable, observable, and interoperable agentic systems.
Open Questions and Tradeoffs
The paper does not pretend to have all the answers. It identifies tradeoffs and unresolved research questions that remain open for the community.
Those open items include how to balance control with flexibility, how to maintain authority across long delegation chains, and how to keep auditability practical at scale. The authors leave these as explicit areas for further work.
A Stable Layer for a Fast-Moving Field
The core claim is that agentic systems need a stable operating layer, much like traditional operating systems provide for applications. AOS is that proposed layer, designed to be implementation-independent and vendor-neutral.
The paper offers a concrete starting point for researchers and engineers building distributed agent systems. It gives them a shared vocabulary and a set of invariants to reason about governance and coordination.
With the paper now on arXiv, the proposal is open for community review and debate. The two authors have put forward a framework that could shape how future agentic systems are designed, deployed, and audited.