AgelClaw: An Agentic Operating System for Autonomous AI Agent Orchestration

The emergence of large language models (LLMs) has catalyzed a paradigm shift from passive AI assistants to autonomous agent systems capable of sustained, goal-directed operation. This paper introduces AgelClaw, a proprietary Agentic Operating System (Agentic OS) that reconceptualizes traditional operating system abstractions for AI agent orchestration. AgelClaw implements a complete OS-equivalent architecture comprising a daemon-based kernel with preemptive scheduling, subagents as first-class processes, a Model Context Protocol (MCP) server ecosystem analogous to device drivers, persistent SQLite-based memory serving as a unified filesystem, and multi-provider AI routing functioning as a hardware abstraction layer. Notably, AgelClaw was developed by a single engineer, demonstrating that the Agentic OS paradigm is not only theoretically sound but practically achievable without organizational resources.