menu_bookAI-Powered Angular

Building AI-Powered Apps with Angular

Master the future of web development. Learn to build next-generation agentic applications using Google AI and Gemini models within the Angular ecosystem.

Book Cover
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Expert Insight

Integrating Gemini models transforms static Angular interfaces into proactive digital assistants.

The Minds Behind

The Authors

Giorgio Boa

Giorgio Boa

Google Developer Expert and Angular specialist focused on large-scale architectures and the convergence of AI and frontend engineering.

Fabio Biondi

Fabio Biondi

Full-stack consultant and trainer. Expert in high-performance Angular applications and building intelligent workflows for enterprise clients.

Chapters

Step-by-step guidance through the neural frontier, from AI foundations to professional cloud deployment.

Chapter 01psychology

AI for FrontEnd Developers

Explore how AI is reshaping the landscape for frontend developers and the transition to intelligent interfaces.

Chapter 02rocket_launch

Getting Started with Google Gemini

Set up your environment and make your first API calls to Google Gemini using Angular.

Chapter 03terminal

Working with Prompts

Learn the art and science of prompt engineering to extract high-quality responses from LLMs.

Chapter 04web

Building a UI in Angular with Google Gemini

Integrate Gemini directly into your Angular components to create dynamic, AI-driven user experiences.

Chapter 05image

Creating Images with Gemini and Angular

Harness the power of multimodal AI to generate and manipulate images directly within your application.

Chapter 06movie

Producing and Managing Videos with VEO Models

Dive into advanced video generation and management using the latest VEO models.

Chapter 07dns

Gemini QuickStart with Angular SSR

Optimize your AI applications for speed and SEO with Angular SSR and Gemini.

Chapter 08hub

Building a MCP with Node, GenKit, and Angular

Architect robust, scalable AI backends using Model Context Protocol, Node.js, and GenKit.

Chapter 09search

Implementing Vector Search with RAG

Master Retrieval-Augmented Generation (RAG) using Firestore and vector search for grounded AI responses.

Chapter 10storage

Smart Data Handling and Storage Strategies

Best practices for caching, managing, and storing AI-generated data efficiently.

Chapter 11fact_check

Bulletproof Testing and Debugging

Professional techniques for testing AI integrations and ensuring deterministic results in a probabilistic world.

Chapter 12gpp_maybe

Error Handling, Security and Debugging

Comprehensive strategies for securing your AI apps and handling complex error states gracefully.

Chapter 13cloud_upload

Deploying Your AI-Powered App to the Cloud

Take your application from local development to a global scale using cloud-native deployment.