Dimitris has 25 years of experience in IT and he is currently Sr. Director of Engineering (Red Hat) at IBM in charge of the Cloud Native Runtimes group that includes the Quarkus, Vert.x, SpringBoot, and Node.js teams. He also served as the JBoss AS project lead and he has been a JBoss addict and contributor from the early start-up days. He worked previously at Intracom and Motorola in the areas of NMS/OSS, designing reusable frameworks and distributed systems. Dimitris studied computer science at the Technological Educational Institute of Athens and received an M.Sc. by research from University College Dublin, Ireland.
Dimitris is also a passionate advocate of Open source technologies and has presented at a variety of events and conferences around the world. He has been an invited speaker at various Java/Linux community events and user groups, and he has delivered inspirational talks on technology and Open Source in universities and educational institutes. In his spare time he has also helped with the organization of technology enablement events for children, like Scratch Days, Devoxx4Kids and JCrete4Kids.
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.
As software engineers, we are faced with lots of choices. Additionally, when developing libraries or frameworks that are used by lots of other software engineers to build their products, even small decisions can have unforeseeable and unintended consequences down the line.
From timeless classics like the importance of naming in software and the proper reuse of existing components, to the unknowns of build time optimization and all the way to bold decisions like rewriting the entire I/O layer and everything in between, this session will give you valuable insights into how and why important decisions were made when developing Quarkus, with the hope of helping you avoid our mistakes and leverage what we got right.
Although the story focuses on decisions made in the context of Quarkus, no actual knowledge of Quarkus itself is necessary to follow along with this talk.
Come and meet with members of the Quarkus team presenting at Devoxx
Greece, to discuss about anything Quarkus related, or even if only to
meet and greet with some of the key folks that make Quarkus possible.
Bring along your good humor
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