Explore how specialized agents can become a coordinated higher-level system through communication, shared state, memory, routing, tools, world models, validation, and governance.
Select a layer to focus the map.
Research, coding, vision, planning, retrieval, verification and domain-specific agents.
Clear responsibilities, capabilities, authority, and task boundaries.
Agent identity, provenance, trust and authorization inside the collective.
Each agent contributes its own model, context, tools and specialized capabilities.
Messages, schemas, handoffs, events and shared communication protocols.
Controls which agents run, in what order, and with which context and tools.
Directs tasks to the most appropriate agent, model, tool or provider.
Voting, debate, critique, consensus, competition and aggregation.
Goals, plans, progress, dependencies, unresolved issues and resource state.
Shared experience, decisions, procedures, failures and learned knowledge.
Controls which information reaches which agent and what can be summarized or forgotten.
A shared representation of the environment, constraints, actors and possible outcomes.
Search, code, APIs, databases, enterprise systems and external capabilities.
Changes to software, services, devices, machines or physical environments.
Physical observations from cameras, audio, lidar, telemetry and other sensors.
Distributed intelligent systems acting through robots, vehicles, devices or machines.
Traces agent activity, routing, handoffs, tools, memory, cost, failures and latency.
Measures whether collective coordination actually improves task outcomes and reliability.
Connects heterogeneous agents, models, frameworks, tools and infrastructure.
Permissions, approval, resource limits, escalation, auditability and human control.