Mario is a senior principal software engineer at Red Hat working as Drools project lead. He has a huge experience as Java developer having been involved in (and often leading) many enterprise level projects in several industries ranging from media companies to the financial sector. Among his interests there are also functional programming and Domain Specific Languages. By leveraging these 2 passions he created the open source library lambdaj with the purposes of providing an internal Java DSL for manipulating collections and allowing a bit of functional programming in Java. 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.
Although there is no universally agreed definition of what an AI agent is, in practice several patterns are emerging that demonstrate how to coordinate and combine the capabilities of multiple AI services, in order to create AI-based systems that can accomplish more complex tasks.
These Agentic Systems architectures can be grouped in 2 main categories: workflows, where LLMs and tools are orchestrated through predefined code paths, and agents, where LLMs dynamically direct their own processes and tool usage, maintaining control over how they execute tasks.
Moreover the security and safety of Agentic Systems architectures is one of the biggest challenges for the adoption in mission critical scenarios. The possibility to serve the model on premise and the introduction of guardrailing techniques are key enablers.
The goal of this talk is giving a theoretical overview of Agentic AI in general and these patterns in particular, discussing their range of applicability and showing with practical examples how they can be easily implemented with Quarkus and its LangChain4j extension on premise using vLLM and Kubernetes.
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