The shape of your agent swarm decides whether it scales or collapses on the first failure. The topology is the architecture — and most swarms pick it by accident.
Multi-agent topology is the decision everyone makes and nobody discusses. A hub-and-spoke swarm fails differently from a mesh, and a pipeline fails differently from both. The topology should be a design choice, not a default.
The Topologies, and When Each Wins
Issue-tree the options:
- **Hub-and-spoke.** One orchestrator routes to specialists. Wins when you need central control and a clear audit path. Loses when the hub becomes the bottleneck.
- **Pipeline.** Agents hand off in sequence. Wins when the workflow is linear and each step is well-scoped. Loses when a step fails and blocks everything downstream.
- **Mesh.** Agents talk peer-to-peer. Wins when the work is exploratory and collaborative. Loses when nobody can answer "who decided what."
Design the Topology for Failure
The topology that survives production is the one designed for failure, not for the happy path. Hub-and-spoke with a fallback orchestrator; pipeline with bypass and escalation at each step; mesh with a shared log so every decision is reconstructable.
- Who takes over when the hub fails?
- Where does a stuck step escalate?
- Where is the shared decision log?
The Audit Path
The audit path is the design constraint that picks the topology for you. If you need a single reconstructable decision log — which regulated work always does — mesh becomes expensive and hub-and-spoke becomes cheap, regardless of performance.
How FACTA Frames It
FACTA's multi-agent work designs swarms where each agent has a clear role, scope, and handoff — with observability and guardrails. The topology is a design decision made against the failure modes, not a framework default.
Conclusion
Swarm topology is the architecture, and it should be a design choice. Pick it against the failure modes and the audit path — not against the framework's default.
About FACTA
FACTA helps startups and growth-stage teams turn AI into production systems that keep running — not demos that impress once.
We design the architecture around the parts that actually break under real usage: tooling you own, credentials you control, failover, cost controls, observability. The boring infrastructure that keeps a system alive after launch.
Led by Matías Baglieri and Carolina Fogliato, we focus on one thing:
AI leadership that builds. Not just advises.
Tell us your workflow and we'll tell you which topology survives its first failure.
See agent handoffs for the contract that makes any topology work.
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