Runi: Architecting a Real-Time, Multi-User AI Session System with Google Gemini

This is a submission for the Built with Google Gemini: Writing Challenge Runi: Architecting a Real-Time, Multi-User AI Session System with Google Gemini What I Built with Google Gemini Runi is a real-time, multi-user AI session framework designed to embed a large language model inside a structured collaborative environment. Instead of treating Google Gemini as a conversational interface, I designed it as a state-aware reasoning layer operating within a distributed session architecture. The system's goal is not simply to generate responses. It is to: Manage structured session state\ Enforce permission-aware AI behavior\ Coordinate multi-user interactions\ Persist and update pinned objects\ Operate within deterministic guardrails System Architecture Overview Runi is built around four primary layers. 1. Real-Time Session Layer Each session is a structured document stored in Firestore containing: Session ID\ Member list with assigned roles\ Pinned object references\ Active system-layer app