As AI moves from experimentation to production, Java developers face a new paradigm: building intelligent, context-aware systems that can reason, interact, and adapt. This session explores the evolution of AI-native Java applications through the lens of agent-based architecture, highlighting how the Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication patterns are transforming the design of modern intelligent services.

Attendees will learn how to move beyond single-turn interactions toward multi-agent coordination, persistent memory, and tool-augmented reasoning. The session discusses architectural trade-offs, performance versus flexibility, open source versus vendor-managed inference, and local versus remote model deployment, while also addressing how to embed security, observability, and governance into agentic systems. As enterprises shift toward AI-native platforms, Java’s maturity, reliability, and performance make it uniquely positioned to lead in this new era of intelligent software.

What You Will Learn

• How MCP and A2A patterns enable collaborative, intelligent agent ecosystems in Java

• Techniques for designing multi-agent systems with memory, reasoning, and tool orchestration

• Architectural trade-offs for performance, flexibility, and governance in AI-native design

Who Should Attend

Java developers, software architects, and AI practitioners building the next generation of intelligent, adaptive, and secure enterprise applications.