#VDZ26 
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.

Devoxx

A conference talk by IBM engineers Mario Fusco and Kevin Dubois covering agentic AI patterns implemented in LangChain4J. They walk through building multi-agent systems using four core workflow patterns: sequence (chaining agents one after another), loop (iterating until quality threshold is met), parallel (concurrent agent execution), and routing (conditional agent dispatch). The talk introduces a pluggable Planner abstraction that lets developers implement custom orchestration patterns and compose them with existing ones. Key concepts include shared agentic scope for cross-agent context, agent monitoring with HTML report generation, a supervisor pattern where an LLM dynamically decides which agents to call, and a goal-oriented pattern using graph-based shortest-path planning. Live demos show a story generation pipeline, a medical/legal/technical question router, and a currency transfer supervisor. The framework is part of LangChain4J's agentic module, actively releasing monthly updates.

Agentic AI Patterns by Kevin Dubois and Mario Fusco