Swarm Orchestration

Distributed agent orchestration coordinates multiple autonomous agents across dynamic topologies to execute tasks in parallel, automatically distributing workloads and balancing tasks to prevent manual overhead and bottlenecks.

You can coordinate multi-agent swarms by initializing a specific topology like mesh or hierarchical, spawning agents, and running parallel task orchestration to observe automatic load balancing and coordinated execution.

Yes, running scalable AI workflows with fault-tolerant coordination requires Node.js 18+ and the agentic-flow CLI v3.0.0-alpha.1 or higher as prerequisites to enable parallel task distribution and memory sharing.

The best way to maintain consistent state is using fault-tolerant coordination with built-in memory sharing, ensuring all agents across adaptive and mesh topologies stay synchronized during distributed problem solving.

Use adaptive topology for model training pipelines when task distribution requirements change dynamically, whereas a static mesh topology suits environments requiring fixed, predictable parallel execution without adaptive load balancing.