World Congress 2025 Aug 20, 2025 Session details

Agentic AI Systems for Critical Workloads

Mario Fusco

Move your generative AI prototypes from experimental notebooks into enterprise-grade Java. Discover how to build, orchestrate, and test autonomous agent workloads using LangChain4j and Quarkus.

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#1 about 2 min

Choosing Java over Python for enterprise AI integration

Java provides transaction management, observability, and security capabilities necessary for enterprise-grade generative deployments.

#2 about 2 min

Core components of autonomous agentic AI systems

Agentic systems combine a foundational model with tools, memory access, and orchestration to perform tasks with minimal human intervention.

#3 about 2 min

Workflow patterns versus independent agent architectures

Developers can orchestrate tasks using programmatically defined workflows or rely on independent agents that coordinate themselves.

#4 about 3 min

Navigating model selection and hallucination challenges locally

Local model deployment requires significant trial and error for prompt engineering and managing occurrences like tool hallucination.

#5 about 3 min

Implementing sequential and parallel agent workflow pipelines

Chaining agents sequentially allows progressive task refinement, while parallel execution effectively splits independent domains before combining results.

#6 about 3 min

Utilizing the mixture of experts routing pattern

A central router agent evaluates input contexts to accurately delegate complex requests to specialized domain experts.

#7 about 6 min

Testing strategies for non-deterministic AI system outputs

Validating probabilistic responses involves building classification functions using evaluation strategies like cosine distance or LLM-as-a-judge approaches.

#8 about 6 min

Transitioning to autonomous multi-agent task execution

Replacing programmatic routers with pure agentic capabilities offers greater dynamic flexibility at the expense of predictable debugging.

#9 about 5 min

Optimizing tool invocation and external API retrieval

Agents autonomously integrate external web services and internet searches to answer complex queries lacking initial context.

#10 about 2 min

Future API protocols and programmatic system structures

Upcoming integration frameworks like Google's A2A protocol will enable comprehensive logical looping and sequence building for agent orchestration.

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Overview of generative AI and the presentation agenda

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Shifting focus from isolated models to enterprise AI systems

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Balancing AI-assisted workflows with fully autonomous system agents

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Integrating local AI models into Java Quarkus applications

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