Topologies & Coordination Patterns
How agents are wired together — queen-led, mesh, hive mind, adaptive, supervisor, conversational, and role-based topologies.
Adaptive Topology Switching
An adaptive topology switches between queen-led, mesh, hive-mind, and other shapes at runtime based on workload signals (task complexity, agent count, latency, cost) — the most sophisticated coordination pattern, exemplified by ruflo’s adaptive mode, with significant complexity cost.
Conversational Orchestration
Conversational orchestration — the AutoGen pattern — coordinates multiple agents through a multi-turn dialogue rather than dispatch-and-return: agents take turns speaking in a shared transcript, with a moderator deciding who goes next, and agreement emerges from the conversation itself.
Hive Mind Pattern
A hive mind is a topology where many simple agents share a common memory store and produce emergent behavior that no individual agent encodes — closer to swarm intelligence than to a structured organization, useful when the problem benefits from many independent partial solutions that combine.
Mesh Topology
A mesh topology lets every agent talk to every other agent directly, with no central coordinator — useful when peers genuinely need to negotiate, but expensive in tokens and hard to debug, so it is rarely the right default.
Queen-Led Hierarchy
A queen-led topology has a single high-authority “queen” agent that allocates tasks to a pool of workers, arbitrates conflicts, and decides when work is done — ruflo’s flagship topology and the most token-efficient way to coordinate 5+ agents on a complex task.
Role-Based Orchestration
Role-based orchestration — popularized by CrewAI — assigns work by role (researcher, writer, editor) rather than by topology shape, with each role’s persona, tools, and termination condition baked into a reusable definition; the topology emerges from how the roles are wired together.
Supervisor Pattern Deep Dive
The supervisor pattern is the framework-vocabulary cousin of queen-led: one supervisor agent routes tasks to specialist agents and gathers results — it is the strong default recommended by Anthropic’s “Building Effective Agents,” and the topology you should pick when in doubt.
Topology as a Design Decision
The shape of how agents connect — single, supervisor-led, mesh, hive mind, queen-led, or adaptive — is a deliberate design decision with concrete cost, latency, and reliability consequences, not an emergent property of running multiple agents.
Topology Selection Decision Tree
A practical decision tree for picking a topology: start with single-agent, escalate to supervisor / queen-led only when single-agent demonstrably falls short, escalate beyond that only for specific patterns (mesh for negotiation, hive-mind for exploration, conversational for discussion, federation for cross-trust).