The AI development landscape forces a difficult choice: the infinite flexibility of open-source libraries or the rigid control of managed enterprise platforms. This dilemma is the root cause of the gap between an impressive demo and a reliable product—a gap filled with architectural compromises, accidental complexity, and endless 'glue code'. This talk charts a third, pragmatic path that avoids this compromise and bridges the gap by focusing on what truly matters.

We will tackle this challenge using Firebase Genkit, a framework built to make complex architectural tasks simple. In this session, we'll break down how to:

Build a Simple Architecture: Turn an idea into an observable, production-ready API using structured flows—a simple yet powerful architectural pattern for AI orchestration.

Ensure Simple Maintenance: See how built-in tracing saves hours of debugging compared to systems built from scratch.

Enable Simple Evolution: Show how a reliable architectural foundation allows you to easily evolve your application from a simple RAG bot to a complex AI agent, without creating technical debt.

This talk is for developers and architects who are tired of the hype and are looking for the most direct path to building the right architecture for real AI products that just work.