Multi-Agent Collaboration Pattern
The Multi-Agent Collaboration pattern distributes a complex task across multiple specialist agents that work in parallel or sequence — each agent optimized for its part of the task, coordinated by an orchestrator.
What Is Multi-Agent Collaboration?
The Multi-Agent Collaboration pattern distributes a complex task across multiple specialist agents. Each agent is optimized for a specific domain or capability. An orchestrating agent (or workflow) coordinates their work, combining their outputs into a final result.
When to Use It
- Tasks that require deep expertise in multiple distinct domains simultaneously
- Tasks that can be parallelized — breaking them into simultaneous sub-tasks reduces overall time
- Contexts where a single agent would have too many tools to select from reliably
When NOT to Use It
- Tasks that are sequential by nature — parallelism adds no value
- Simple tasks where the orchestration overhead exceeds the benefit
- Early-stage implementations where you haven't yet mastered single-agent deployment
How It Works
An orchestrating agent receives the goal and decomposes it into sub-tasks. It dispatches each sub-task to a specialist agent — an HRIS agent, an IT provisioning agent, a communication agent. The specialists execute and return results to the orchestrator, which assembles them into the final output or coordinates the next round of tasks.
Governance in Multi-Agent Systems
Every agent-to-agent interaction needs the same governance as agent-to-system interactions. Workato's Control Plane logs multi-agent interactions — each sub-agent's actions are traceable to the originating orchestrator and the original user request. Define agent-to-agent authorization explicitly: not every agent should be able to call every other agent.