orchestration

To coordinate parallel agents, a central conductor spawns multiple worker agents to execute background tasks in parallel, enforcing explicit dependencies and synthesizing structured results into a cohesive outcome for complex software workflows.

Multi-agent orchestration is a task management technique where a central conductor coordinates a swarm of AI workers, applying explicit dependencies and guided context to ensure parallel workstreams deliver cohesive, synthesized outputs.

Yes, you can run a PR review by spawning multiple worker agents in a single message to perform parallel analysis, which the system then aggregates and synthesizes into a single, polished result.

Multi-agent task management works for codebase exploration and bug fixes by distributing parallel analysis across worker agents, enforcing explicit task dependencies, and aggregating structured results for cohesive delivery.

Synthesizing results from parallel workstreams involves the central conductor aggregating structured outputs from all worker agents, leveraging guided context to ensure consistency and deliver a single polished outcome.

You should avoid using a multi-agent swarm for simple, linear software engineering tasks that lack explicit dependencies, as the overhead of coordinating parallel workers and synthesizing results outweighs the benefits of parallel execution.