Spring AI in Practice: Building Multi-Agent Systems

Integrating artificial intelligence into enterprise applications requires more than just calling an API; it demands coordinated systems that can think, plan, and collaborate. This text-based course guides you through the process of building robust, multi-agent AI systems using the Spring AI framework. You will discover how to connect multiple specialized agents to solve complex business problems, manage conversational state, and build reliable backend architectures. By completing this course, you will transform from a traditional Java developer into an AI-enabled engineer capable of designing autonomous, multi-agent workflows. You will learn to structure agent communication, implement guardrails, and manage context efficiently. What you'll learn: - Understand the core architecture of Spring AI and how it integrates with enterprise Java applications - Design and implement multi-agent systems where specialized agents collaborate to complete complex tasks - Manage conversational state, memory patterns, and context window optimization in Java - Apply structured prompt engineering techniques directly within your application code - Configure retrieval-augmented generation (RAG) workflows to ground your agents in custom data sources - Implement safety guardrails and fallback mechanisms to ensure predictable agent behavior The course begins with foundational concepts of generative AI, large language models, and the Spring AI ecosystem. From there, you will progress through structured text-based lessons that cover agent coordination, state management, and production-ready integration patterns. This course is designed for Java developers, backend engineers, and software architects who want to build intelligent systems. No prior experience with AI or machine learning is required, though a basic familiarity with Spring Boot and Java is recommended. Start reading today to build your first collaborative AI agent system with Spring.