Building a Multi-Agent AI Movie Production Team with Google ADK

🚀 What I Built I created a collaborative AI Multi-Agent system using Google's new Agent Development Kit (ADK). The system functions as an automated Hollywood Production Team designed to streamline creative brainstorming. The user submits a simple movie prompt (e.g., "A movie about a time-traveling chef"), and the specialized agents work sequentially to refine the idea into a viable film concept. 🧠 My Agent Architecture My multi-agent team uses a sequential workflow tracking architecture consisting of two specialized agents running on gemini-2.5-flash : movie_writer : Takes the raw user input concept and expands it into a high-stakes, descriptive three-sentence movie plot. movie_critic : Automatically intercepts the writer's completed story context to deliver constructive structural improvements. These agents are orchestrated via a SequentialAgent pipeline configuration that manages data handoffs automatically. 🛠️ Key Learnings & Challenges Framework Evolution: I learned how to structure project modules using ADK 2.0's directory scanning conventions ( __init__.py mapping definitions). Overcoming Roadblocks: I originally ran into layout separation issues on Windows where the backend command runner could not discover the python modules. Resolving this taught me how the google.adk.cli maps working directory environments ( ./app ). Handling API Constraints: Dealing with transient API capacity limits (like standard 503 backend service spikes) taught me how crucial error handling and session resets are when building live AI tools.