Kevin Dubois is a software architect and platform engineer with a career spanning over 20 years. He is often featured as a keynote speaker at conferences around the world where he shares his experience and knowledge about cloud native & AI software development, developer experience, open source and Java. Kevin is also an author and Java Champion. He currently works as a Senior Principal Developer Advocate at IBM, and is also Technical Lead for the CNCF Developer Experience Technical Advisory Group.
You’ve likely heard it everywhere lately: “This is the year of Agentic AI”!! Well, then why not roll up your sleeves and try creating your own Java-based Agentic AI app?
Thanks to the ease of use and superb developer experience of Quarkus and the nice AI integration capabilities that the LangChain4j libraries offer, it becomes trivial to start working with Agentic AI.
In this session, you’ll explore a variety of Agentic AI capabilities. We’ll start by creating a simple AI client to interact with an LLM. We’ll then explore how we can make this app “agentic” by adding a variety of agentic capabilities, such as local function calling, MCP, Agent2Agent, and more.
In addition, we’ll also try out different techniques and patterns to get your LLM leveled up to leverage these Agentic capabilities. We’ll also attempt to show that agents are in fact not always needed, and show alternative patterns to accomplish AI tasks.
Come to this session to learn how to build Agentic AI applications in Java from the experts and engineers actively working on Quarkus AI and LangChain4j. This is also an opportunity to provide feedback to the maintainers of these projects and contribute back to the community.
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