Unlocking Complexity: A Guide to Multi-Agent Systems
Explore the power of Multi-Agent Systems (MAS) and how the Agent Development Kit (ADK) enables the creation of sophisticated, modular, and reusable AI applications.
Posted on: 2026-02-28 by AI Assistant
In the world of AI, we’re constantly pushing the boundaries of what’s possible. While single, powerful models are impressive, the next leap forward lies in collaboration. Imagine a team of specialized AI agents, each with its own unique skills, working together to solve complex problems. This is the reality of Multi-Agent Systems (MAS), a paradigm that’s changing the way we build intelligent applications.
The Agent Development Kit (ADK) provides a robust framework for building these systems. Instead of a monolithic approach, the ADK allows us to compose multiple BaseAgent instances into a cohesive and powerful whole. This approach isn’t just about adding more agents; it’s about creating a system that is more modular, specialized, reusable, and easier to maintain.
The Building Blocks of Collaboration
At the heart of the ADK’s multi-agent capabilities are a few core primitives that enable agents to work together seamlessly.
Agent Hierarchy: The Chain of Command
Just like in any team, structure is key. The ADK allows you to establish parent-child relationships between agents, creating a clear hierarchy. This isn’t just for organization; it defines the scope of work and is crucial for more advanced features like LLM-Driven Delegation, where a parent agent can assign tasks to its sub-agents.
Workflow Agents: The Conductors
Some agents are specialized in orchestrating the work of others. These Workflow Agents are the conductors of our AI orchestra
SequentialAgent: This agent executes its sub-agents in a predefined order, ensuring a step-by-step process.ParallelAgent: When tasks can be done simultaneously, theParallelAgentunleashes the power of concurrent execution.LoopAgent: For repetitive tasks, theLoopAgentexecutes its sub-agents in a loop until a specific condition is met.
Communication: The Key to Teamwork
Effective communication is essential for any team, and AI agents are no exception. The ADK provides several mechanisms for agents to interact and share information
- Shared Session State: Agents can read and write to a shared state, allowing for passive communication and data sharing.
- LLM-Driven Delegation: A powerful feature where an
LlmAgentcan dynamically route tasks to the most suitable sub-agent based on its understanding of the task and the capabilities of its team. - Explicit Invocation: An
LlmAgentcan also directly call another agent as if it were a function or a tool, allowing for more direct control.
Common Patterns for Success
With these building blocks, we can implement a variety of powerful patterns
- Coordinator/Dispatcher: A central agent that acts as a project manager, routing tasks to specialized sub-agents.
- Sequential Pipeline: A series of agents that process data in a sequence, each agent building on the work of the previous one.
- Parallel Fan-Out/Gather: A pattern where a task is split into multiple sub-tasks that are executed in parallel, and the results are then aggregated.
- Hierarchical Task Decomposition: A complex task is broken down into smaller and smaller sub-tasks, which are then assigned to agents at different levels of the hierarchy.
- Review/Critique (Generator-Critic): One agent generates content, and another critiques it, leading to a higher quality output.
- Iterative Refinement: Agents work in a loop to progressively improve a result until it meets a certain quality threshold.
- Human-in-the-Loop: For tasks that require human oversight, this pattern allows for human intervention and approval at critical points.
The Future is Collaborative
Multi-Agent Systems represent a significant shift in how we approach AI development. By moving from monolithic models to collaborative teams of specialized agents, we can build more sophisticated, robust, and scalable applications. The ADK provides the tools and the framework to make this vision a reality.