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In real-world systems, you rarely know the exact number of tasks or agents you'll need ahead of time. How can we dynamically assign and parallelize tasks based on runtime conditions? In Google's Agent Development Kit (ADK), the answer is simple but powerful: Dynamically create a ParallelAgent inside a Custom Agent, and use session.state as your shared communication bus. In this post, we'll cover: ✅ Why dynamic parallelism matters ✅ A minimal working example ✅ How to run and verify it ✅ Common pitfalls and best practices ✅ Extension ideas for scaling
In real-world systems, you rarely know the exact number of tasks or agents you'll need ahead of time.
How can we dynamically assign and parallelize tasks based on runtime conditions?
In Google's Agent Development Kit (ADK),
the answer is simple but powerful:
Dynamically create a ParallelAgent inside a Custom Agent, and use session.state as your shared communication bus.
In this post, we'll cover:
✅ Why dynamic parallelism matters
✅ A minimal working example
✅ How to run and verify it
✅ Common pitfalls and best practices
✅ Extension ideas for scaling
