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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.
