Beyond the Chatbot: A Blueprint for Trustable AI- Google Developers Blog

This post details the implementation of a 'Split-Brain' architecture for real-time AI guidance in a racing scenario. It showcases the use of Antigravity (AGY) for orchestrating stateful agentic systems, compressing a three-month development cycle into two weeks. Gemini Nano is used at the edge for ~15ms response times via Web API, while Gemini 3.0 handles higher-level reasoning. The 'Perception Team' utilized Maps MCP for track layout rendering and 60FPS telemetry. Neuro-Symbolic Training with QLoRA was employed for mathematically verifying AI advice against physics. Persona-based routing with a 'Gemini Squad' of agents (e.g., Crew Chief, Telemetry Engineer) was implemented to manage cognitive load and deliver context-aware guidance.