Multi-Agent Systems with ADK—Sequential, Parallel, Loop & LLM Delegation | Google ADK Masterclass #4

This masterclass covers building multi-agent systems using Google's Agent Development Kit (ADK), demonstrating how to overcome limitations of single monolithic agents through sequential, parallel, loop-based, and LLM-driven delegation patterns. The session teaches architectural patterns for decomposing complex tasks across multiple specialized agents, enabling better scalability, maintainability, and task-specific optimization. Key patterns include chaining agents sequentially for dependent tasks, running agents in parallel for independent work, implementing loops for iterative refinement, and using LLM-driven delegation to dynamically route tasks to appropriate agents.

Key Points

• •Monolithic single-agent systems struggle with complexity, scalability, and task specialization—multi-agent architectures solve this by decomposing work across specialized agents
• •Sequential agent patterns execute agents in dependency order, where one agent's output feeds into the next agent's input for dependent tasks
• •Parallel agent patterns run multiple agents concurrently on independent tasks, reducing total execution time and improving efficiency
• •Loop-based patterns enable iterative refinement where agents repeatedly process, evaluate, and improve outputs until quality thresholds are met
• •LLM-driven delegation uses language models to intelligently route tasks to the most appropriate agent based on task characteristics and agent capabilities
• •Agent composition requires clear interface definitions (inputs/outputs) and state management to coordinate work across multiple agents
• •Error handling and fallback strategies are critical in multi-agent systems to gracefully handle agent failures and maintain system resilience
• •ADK provides built-in patterns and utilities for orchestrating sequential, parallel, and conditional agent workflows without manual coordination code
• •Task decomposition strategy should align with agent specialization—each agent should have a clear, focused responsibility
• •Monitoring and observability across multiple agents is essential for debugging, performance optimization, and understanding system behavior

Workflow Diagram

Concepts