Overview
AI agents are reshaping how enterprise software is conceived, built, and operated. Yet many teams remain stuck at the prototype stage—bolting isolated AI services onto Java backends and encountering security, latency, and integration headaches. AI Agents with Java gives experienced developers and architects a clear, practical path to designing autonomous systems directly in the JVM, bringing scale, reliability, observability, and governance to agentic AI.
Drawing on decades of combined enterprise experience, Java Champions Alex Soto Bueno, Mario Fusco, and Markus Eisele offer a hands-on blueprint for moving from one-off AI add-ons to fully autonomous systems. Through real-world patterns, architecture diagrams, and production-ready examples, they show how to build long-running, stateful agents, apply zero trust principles and fine-grained access controls, and integrate seamlessly with APIs, backend services, and cloud native workflows.
- Understand the leap from AI-enabled apps to fully autonomous agentic systems
- Model planning, memory, and world knowledge with Java frameworks like Quarkus, LangChain4j, and LangGraph4j
- Build and deploy stateful agents that self-correct and adapt over time
- Implement MCP and A2A standards for secure multi-agent collaboration
- Design for enterprise-grade security, compliance, observability, and debugging for agentic systems
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