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:

1. 
   movie_writer: Takes the raw user input concept and expands it into a high-stakes, descriptive three-sentence movie plot.


2. 
   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.