How to Build Multi-Agent Architectures with Google ADK

Why Single Agents Don't Scale Well Whenever we’re prototyping an AI application, we begin by creating a single agent that’s in charge of everything, from understanding the request, planning, calling tools, and generating the final response. This is fine for a simple use case, as this is easy to implement. However, as complexity grows, the agent must manage a lot of different tasks, like validation and multiple tool calls in the same iteration loop. This can make context difficult to debug and understand because everything is happening inside a single model call.