Overview

AI Engineering for Web Developers Build Production-Ready LLM and RAG Apps with React, Next.js, and Tailwind CSS Artificial intelligence is no longer experimental-it's powering real products used by millions. But how do you move beyond simple demos and actually build reliable, scalable AI features into modern web applications? AI Engineering for Web Developers is your practical, hands-on guide to building production-ready applications powered by large language models (LLMs) and retrieval-augmented generation (RAG). Designed specifically for web developers, this book shows you how to integrate AI into real-world apps using React, Next.js, and Tailwind CSS-without needing a machine learning background. Whether you're new to AI or looking to level up your engineering skills, this book walks you step by step through modern AI application architecture, prompt engineering, vector embeddings, semantic search, and secure deployment strategies. What You'll Learn- How large language models (LLMs) work in real production systems - How to design and implement retrieval-augmented generation (RAG) pipelines - Embeddings, vector databases, and semantic search explained clearly - Building a robust LLM API layer in Next.js - Streaming AI responses in modern web applications - Prompt engineering, guardrails, and hallucination mitigation - Rate limiting, logging, monitoring, and observability for AI workloads - Designing AI agents and tool-calling workflows - Performance optimization, cost control, and token budgeting - Security, privacy, and compliance basics for AI-powered apps Built for Web DevelopersIf you already know JavaScript and have experience with React or Next.js, you're ready. This book focuses on implementation-not abstract theory. You'll build real features including: - AI-powered chat and summarization tools - Documentation and knowledge-base copilots - End-to-end RAG systems with chunking and ingestion pipelines - Production-ready AI dashboards with Tailwind CSS - Deployment strategies for staging and production environments Every chapter emphasizes reliability, scalability, and clean architecture-so your applications work not just in development, but in production. From Experiment to ProductionMost AI tutorials stop at basic demos. This book goes further. You'll learn how to handle API timeouts, retries, streaming responses, rate limits, abuse prevention, logging, and monitoring. You'll understand how to structure AI services cleanly within a modern full-stack architecture and how to measure performance and return on investment. By the end of this book, you won't just understand AI concepts-you'll have the skills to design, build, deploy, and operate real LLM-powered web applications. If you're ready to combine modern web development with practical AI engineering-and build intelligent applications that are secure, scalable, and production-ready-this guide will show you how. Start building the next generation of AI-powered web apps today.

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