Agentic AI Wiki
Deep-Dives / Multi-Agent Systems

Multi-Agent Systems

When multiple agents pay off, when one beats many, and the topologies, failure modes and debate patterns in between.

  1. When (and When Not) to Go Multi-Agent
    Price the coordination tax before you split: the three honest reasons to add an agent, and when one agent with tools wins.
  2. Multi-Agent Topologies
    Star, pipeline, hierarchy, mesh — their O(·) message cost and failure profiles, and how to pick the sparsest wiring that still works.
  3. Supervisor / Worker Orchestration
    The pattern that actually ships: plan, dispatch isolated workers, aggregate — and why the supervisor is the bottleneck.
  4. Debate, Voting & Ensembles
    Most of the gain is ensembling, not debate; without engineered diversity, debate collapses to the initial majority.
  5. Shared Memory & the Blackboard
    A blackboard replaces N² messages with one shared store — and inherits write contention, stale reads, and lost updates.
  6. Multi-Agent Failure Modes
    Error propagation, groupthink, deadlock/livelock, cost explosion — the system-level bugs single-agent tooling cannot see.