A hierarchical multi-agent architecture with multi-level organizational structure. A top-level executive agent manages mid-level team lead agents, who each manage their own pool of specialist workers. Teams within teams — the hierarchy maps to domain separation.
Copy and paste the following FlowZap code into a project in your FlowZap account to see this template diagram.
executive_agent {# Executive Agent
n1: rectangle label="Route Master Goal"
n1.handle(bottom) -> research_lead_agent.n2.handle(top) [label="Assign Research"]
n1.handle(bottom) -> content_lead_agent.n5.handle(top) [label="Assign Content"]
}
research_lead_agent {# Research Lead Agent
n2: rectangle label="Manage Retrieval Team"
n2.handle(bottom) -> web_search_agent.n3.handle(top) [label="Web Task"]
n2.handle(bottom) -> db_retrieval_agent.n4.handle(top) [label="DB Task"]
}
web_search_agent {# Web Search Agent
n3: rectangle label="Live Web Search"
n3.handle(right) -> research_lead_agent.n2.handle(right) [label="Web Data"]
}
db_retrieval_agent {# DB Retrieval Agent
n4: rectangle label="Internal Knowledge RAG"
n4.handle(right) -> research_lead_agent.n2.handle(right) [label="Internal Data"]
}
content_lead_agent {# Content Lead Agent
n5: rectangle label="Manage Production Team"
n5.handle(bottom) -> writer_agent.n6.handle(top) [label="Draft Topic"]
}
writer_agent {# Writer Agent
n6: rectangle label="Draft Document"
n6.handle(bottom) -> qa_agent.n7.handle(top) [label="Draft Text"]
}
qa_agent {# QA Agent
n7: rectangle label="Fact Check"
n7.handle(right) -> content_lead_agent.n5.handle(right) [label="Final Content"]
}
A hierarchical multi-agent architecture that scales orchestration by stacking supervisors and team leads (a tree structure), which mirrors enterprise org structures and helps partition context. This is the 'enterprise-grade agentic AI architecture' when a single orchestrator cannot manage all workers directly. Ideal for large enterprises and multi-domain workflows.
A supervisor-worker multi-agent architecture where an orchestrator agent receives a high-level goal, breaks it into subtasks, delegates each to specialist worker agents (researcher, writer, QA), monitors execution, handles failures, and synthesizes results. The orchestrator manages but does not execute tasks itself.
A sequential pipeline multi-agent architecture where agents are arranged in a strict sequence. Each agent transforms or enriches the output of the previous one, then passes it forward. No central orchestrator — the flow is deterministic like an assembly line.
A swarm multi-agent architecture where multiple agents work on the same or related tasks simultaneously, with no central coordinator. Their outputs are then aggregated, voted on, or merged by a dedicated aggregator node. Agents may compete — the best output wins.
The most architecturally sophisticated multi-agent pattern. Agents are assigned not just roles but opposing incentives. A Planner is optimistic about goal completion. A Critic is constitutionally skeptical and holds veto authority. Errors get caught through adversarial pressure rather than trusting a single model's self-assessment.
An org-chart architecture with multi-level structure. A top-level supervisor manages team leads, who each manage their own pool of specialist workers. Teams within teams. Best for enterprise-scale automation with 10+ specialized agents spanning multiple domains.