Three-agent-class ring architecture scales AI across entire organization

The architecture separates concerns into three agent classes sharing a contextual layer. Observer agents sit at the edge pulling external signals and writing structured events. Task agents pick up work from that stream, execute bounded actions, and write results back. Goal agents read the full execution history, build plans, sequence task agents, and re-plan when conditions shift. LangGraph powers the goal agent layer with conditional branching, checkpointed state, and resume capability after failure. CrewAI handles task coordination through role-based agent assignment, shared short-term and long-term memory, and a planning agent that sequences tasks before execution.

Underneath, Harbor provides every agent with scoped access to tools, files, and workflows—credentials stay in Harbor, not in model context. Every tool call produces a trace with full provenance, allowing failure debugging in under an hour instead of a day. The ring-based protocol routes messages across five layers: Kernel agents at Ring 0 manage agent lifecycle; Orchestrators at Ring 1 route by metadata; Goal agents at Ring 2 decompose intents; Task agents at Ring 3 execute with least privilege; Observer agents at Ring 4 post events continuously. As the conversation deepens, newer agents start with richer history, and coordination overhead per agent drops over time.