Developing AI applications today isn’t just about experimental single-model interactions. Organizations are rapidly adopting AI and to do that, the requirements for enterprise software become increasingly more complex. Advanced Agentic AI systems address this need, where multiple specialized agents work together, each capable of independent reasoning. The real challenge for architects lies in orchestrating these agents to collaborate effectively towards a common goal. Unfortunately though, "one-size-fits-all" or “off-the-shelf” approaches to coordination just don't work due to the complex nature of software. In this session we'll explore the spectrum of agentic patterns, from reliable and predictable, but rigid workflows to highly flexible, autonomous agent orchestration using LLMs, and everything in between. This talk will cover: * The pros and cons of various agentic patterns. * Practical demonstrations of how to combine these patterns in an enterprise software environment with Java, LangChain4j and its Quarkus extension. * How to leverage the provided infrastructure for agent collaboration. * The flexibility to implement and seamlessly integrate your own custom agentic patterns.

Talk Level:
INTERMEDIATE

Bio:
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.