Spring AI Advanced Developer Guide: Engineering AI Agents, RAG Systems, and Production-Ready Applications (Spring AI Developer Series)
J. Klat, Eric
Synopsis "Spring AI Advanced Developer Guide: Engineering AI Agents, RAG Systems, and Production-Ready Applications (Spring AI Developer Series)"
Building a basic AI-powered application is only the beginning. Real-world systems require reliable retrieval, intelligent tool use, security, observability, resilience, evaluation, and production-ready architecture. Spring AI Advanced Developer Guide takes the concepts introduced in the first volume and moves into advanced AI engineering with Java and Spring Boot. It is designed for developers and architects who want to move beyond simple model interactions and build sophisticated AI systems capable of interacting with data, invoking tools, coordinating workflows, and operating reliably in production environments. The book explores advanced patterns for retrieval-augmented generation, AI agents, tool calling, Model Context Protocol integrations, multimodal applications, local AI models, and enterprise-oriented AI architecture. It also addresses the engineering challenges that emerge when AI applications move from prototypes into real systems. Inside the Book, You Will Explore:Designing advanced retrieval-augmented generation architectures Improving retrieval quality, relevance, and contextual grounding Building AI agents with Spring AI Implementing tool calling and real-world application actions Designing multi-step AI workflows and agent orchestration Connecting AI applications through the Model Context Protocol Building multimodal applications that work with more than text Integrating locally hosted models into Spring Boot applications Designing AI systems that remain maintainable as complexity grows Protecting applications against prompt injection and other AI-specific threats Managing model failures, timeouts, retries, and service degradation Implementing observability and monitoring for AI workloads Tracking model usage and controlling AI-related costs Evaluating AI responses and measuring application quality Containerizing and deploying intelligent Spring Boot applications Applying production architecture patterns for scalable AI services The focus throughout the book is on engineering discipline: designing AI systems that are understandable, testable, observable, secure, resilient, and maintainable rather than simply demonstrating isolated AI features. By the end of this volume, you will be equipped to design and build sophisticated AI-powered Spring Boot systems that go beyond basic chat interfaces and integrate intelligent reasoning, retrieval, tools, external services, and production infrastructure. Spring AI Advanced Developer Guide is intended for experienced Java and Spring Boot developers, backend engineers, software architects, technical leads, and developers who have completed the fundamentals of AI application development and are ready to build more advanced systems.
