Explore a full-stack architecture that combines a Next.JS frontend with a SQL database and Firebase Data Connect backend, using a Genkit agent, vector search and Retrieval-Augmented Generation (RAG) for intelligent, data-driven responses.

Build dynamic web experiences that use Gemini, Imagen, and Veo to create real time responses to user's drawings. Explore the architecture that integrates a Gemini, Functions, and Firestore backend with Angular and PhaserJS on Firebase Hosting.

Build agentic experiences with Firebase and Google Cloud. Explore Genkit-powered agents that can respond to multimodal user inputs, use tool calling to orchestrate complex tasks and include human-in-the-loop flows.

Explore the GenKit and Flutter based architecture for building a multi-platform app that seamlessly integrates AI input with Retrieval-Augmented Generation (RAG).

Learn how to use Gemini in Android Studio, Firebase and Google technologies to build an engaging Android app.

Learn how the Google engineering teams created a multiplayer crossword using Gemini, Flutter, and Firebase.

Learn how to use the Gemini API and the Google Gen AI SDK to prototype generative AI for web apps.

Learn how generative AI can be used in different stages of game development from preproduction to in-game solutions using Gemini AI and Gemma model.

Learn how to use the multimodal features of the Gemini model to analyze HTML documents and image files for the purpose of adding accessible descriptions to a webpage in a NodeJS script.

Learn how to build a modern serverless ecommerce web app using a Django and Cloud Run backend, Cloud SQL data storage, and Firebase.

Learn how to build a distributed, scalable ecommerce web app using microservices on Kubernetes.

Learn how to build a multi-tier web application with a Golang backend running on Cloud Run and using a CloudSQL database.