Speaker

Start integrating powerful AI capabilities into your Java and Kotlin applications today.

Spring AI helps you solve the core challenge of connecting your enterprise Data and APIs with AI models, opening the path to building practical multi-agent automations.

In this session, led by the project lead, we will demonstrate practical use cases through live coding demos.

You'll learn to implement key Generative AI patterns including Conversation Memory, Tool/Function calling, and Modular RAG (Retrieval Augmented Generation).

We'll explore approaches for building multi-agent systems and leveraging observability through metrics, tracing, and logging to understanding how your systems perform.

The session will also cover techniques for managing AI hallucinations using relevancy and fact-checking evaluators.

By the end of this session, you'll have everything you need to start integrating generative AI into your existing Java and Kotlin applications using Spring AI.

The Model Context Protocol (MCP) introduces a powerful approach for AI agent development by standardizing how AI models interact with external tools and resources.

This talk explores MCP's architecture, diving deep into its core capabilities: tool discovery and execution, resource management with URI templates, and dynamic prompt handling.

We'll examine how Spring AI MCP - Java MCP SDK, implementation transforms these specifications into practical agent capabilities, demonstrating how to evolve traditional AI applications into full-fledged agents that can interact with external systems, manage resources, and handle complex workflows through standardized interfaces.

Through live coding examples, we will learn how to combine the Spring AI framework with MCP to create agents that can effectively understand context, make decisions, and take actions across various external systems.