opc-architecture

OPC's agent orchestration works by spawning child Maestro instances as parallel agents. It coordinates these distributed AI agents using hooks to intercept events and a PostgreSQL database to manage inter-agent communication and state persistence.

You coordinate multiple AI agents by using hooks to intercept Maestro events and scripts to manage inter-agent communication. State persistence and data sharing across agents are handled through a PostgreSQL database.

The Orchestrated Parallel Claude (OPC) architecture is a framework that extends Maestro for distributed systems. It manages the lifecycle of multiple AI agents, from user command to execution and feedback, by spawning them as child processes.

Yes, OPC uses the Maestro framework to spawn new child instances for parallel agent execution. This allows developers to build complex multi-agent workflows where different agents handle tasks like research, implementation, and testing simultaneously.

OPC persists state across distributed agents by integrating a PostgreSQL database with the Maestro framework. Scripts manage the operational flow, ensuring inter-agent communication and state data are maintained throughout the agent lifecycle.

Use OPC instead of standard Maestro when your multi-agent system requires advanced coordination mechanisms, such as spawning child processes, intercepting events via hooks, and managing persistent state across distributed agents in a PostgreSQL database.