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Agent frameworks promise to make AI systems easier to build. But the hard part isn’t just creating agents, it’s coordinating them. Writing, reviewing, debugging, and deploying agentic systems requires clear roles, shared state, observability, and control over how work moves between components.

In this episode, we explore Google ADK, Google’s code-first framework for building, evaluating, and deploying multi-agent systems. Rather than treating agents as prompt chains, ADK models them as software components: agents are objects, tools are regular functions, and workflows are composed through explicit orchestration primitives.

You’ll learn:

* Where ADK fits in the agent framework ecosystem

* What happens under the hood: how ADK models agents, tools, sessions, state, and memory, and how sequential, parallel, and loop agents express most real-world workflows.

* What a real workflow looks like in practice: through the example of an automated writing assistant, we’ll see how a theme agent, writer agent, and critic agent collaborate to draft, review, revise, and stop when the output is ready.

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