Developing Generative AI Agents in Java

Generative AI is shifting from static chat prompts to autonomous agents that can plan, execute tasks, and interact with external systems. Java developers can leverage their existing skills to build these sophisticated, self-directing AI systems. In this course, you will transition from writing traditional, rigid code to engineering dynamic Java applications driven by large language models. You will read through clear explanations, analyze code snippets, and master the architecture of modern AI agents. What you'll learn: - Understand foundational AI agent concepts, core terminology, and cognitive architectures. - Implement LLM orchestration in Java using modern tools and libraries like LangChain4j. - Design agents capable of tool use, API calling, and structured data output. - Apply memory management strategies to help agents maintain context across interactions. - Utilize modern Java features like records and virtual threads to handle concurrent agent tasks. - Integrate vector databases to enable retrieval-augmented generation (RAG) for agent workflows. The course begins with fundamental definitions of agency and LLM integration, progressing step-by-step to multi-agent collaboration patterns and tool integration. You will study structured text examples and complete written design exercises to solidify your understanding. This text-based course is designed for Java developers who are new to generative AI and want to build autonomous systems, with no prior machine learning experience required. Start reading today to build the next generation of intelligent Java software.