swarm

Parallel AI agents can be coordinated without direct messaging by using stigmergic pheromones and explicit task queues. This approach enables agents to perform multi-file tasks indirectly, avoiding conflicts and managing complex workflows across large codebases.

Stigmergy is an indirect coordination mechanism where agents leave pheromone trails in the environment to guide others. In multi-agent coordination, pheromones help agents avoid conflicts and manage task exploration across files without needing direct communication.

To orchestrate features with safe concurrent edits, post a swarm task and spawn workers using a defined lifecycle. Agents coordinate via pheromone states and explicit task queues, ensuring distributed task decomposition and conflict avoidance across modules.

Pheromone-based coordination is suitable for multi-step workflows in large codebases. The defined swarm lifecycle, task states, and worker protocol support distributed coordination, task decomposition, and dependency handling across multiple files and modules.

Use stigmergic coordination instead of direct messaging when parallelizing work across multiple files or modules where conflicts are likely. Pheromones provide indirect coordination to guide exploration and ensure safe concurrent edits without direct agent communication.

Parallel agent coordination supports task dependencies and progress tracking through explicit task queues. Work items are managed with defined task states and a worker protocol, allowing agents to handle dependencies and track progress throughout the swarm lifecycle.