The system uses four structured files that agents read at session start to maintain durable memory of personality, user profile, operational protocols, and current state. It supports multi-agent hierarchies (orchestrator, leads, specialists) and integrates with tools like Claude-Code. The approach accumulates real context over time rather than relying on model improvements, enabling AI assistants to provide continuity across conversations.