Developer Proposes AI Operating System Built Around Context as a Core Runtime Resource

A developer writing for DEV Community has outlined a conceptual framework for an AI Operating System (AOS), arguing that agentic AI systems need formal runtime primitives rather than simply more agents. The central idea treats context — what an AI agent can see, access, and consume — as a schedulable resource analogous to how traditional operating systems manage memory and processes. The author's existing framework already includes 24 agents, 53 skills, and inter-agent contracts across platforms like GitHub Copilot, Cursor, and Gemini, with context engineering serving as an early implementation of this principle. Design notes for a fuller AOS sketch governance pairs such as Memory Engineer and Memory Auditor or Orchestrator and Scheduler, though the author stresses these remain open questions rather than a shipped system. The piece argues that a trustworthy AOS must prioritize checks on agent output — including structural validation, independent review, and human approval for irreversible actions — over simply expanding what agents can do.