Autonomous Agent Architecture: How RVOS Orchestrates Intelligence
A deep dive into the agent architecture that powers RVOS — how agents communicate, share context, and coordinate complex workflows.
At the heart of RVOS is an agent orchestration layer. Unlike simple API wrappers that send a prompt and return a response, RVOS agents are persistent, context-aware entities that can communicate with each other and access shared system resources.
Each agent in RVOS has a defined role, a set of capabilities, and access to the shared knowledge graph. When you initiate a workflow, the orchestrator determines which agents are needed, assigns tasks, and manages the flow of context between them.
The key architectural decision is the shared memory layer. Instead of each agent maintaining its own isolated context window, agents read from and write to a common project state. This means the research agent findings are immediately available to the writing agent without manual handoff.
Coordination happens through a combination of direct messaging and a shared event bus. Agents can request information from each other, subscribe to relevant changes, and react to system events. This creates emergent workflows where multiple agents collaborate on complex tasks.
The architecture is designed to be model-agnostic. Agents can be powered by different AI models depending on their role — a research agent might use one model while a creative writing agent uses another. The orchestration layer abstracts away these differences.