Mario is a senior principal software engineer at IBM working as Drools project lead. Among his interests there are also high performance systems and generative AI, being an active contributor of widely adopted projects like Quarkus and LangChain4j. He is also a Java Champion, the JUG Milano coordinator, a frequent speaker and the co-author of "Modern Java in Action" published by Manning.
Developing AI applications today goes beyond simple single-model interactions. We're seeing a shift towards agentic AI systems, where multiple specialized agents work together, each capable of independent reasoning. The real challenge for an AI architect lies in orchestrating these agents to collaborate effectively towards a common goal.
Given the diverse and complex tasks these systems handle, a "one-size-fits-all" approach to coordination just doesn't work. We'll explore the spectrum of agentic patterns, from reliable but rigid workflows to highly flexible, autonomous agent orchestration using LLMs, and everything in between.
Beyond just sequencing agents, effective communication is vital. Agents need a shared space to exchange results and enrich each other's contexts.
This talk will cover:
- The pros and cons of various agentic patterns.
- Practical demonstrations of how to combine these patterns using 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.
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