Update _posts/2025-05-08-agentic-ai-with-quarkus-p3.adoc

Co-authored-by: Clement Escoffier <[email protected]>

Author: mariofusco

_posts/2025-05-08-agentic-ai-with-quarkus-p3.adoc

@@ -39,7 +39,9 @@ The resulting traces show the sequence of steps performed to fulfill the user re
 .Tracing routing workflow pattern execution
 image::routing-workflow-trace.png[align=center, alt="Tracing routing workflow pattern execution"]
 In this example, we use the same model to classify and generate the response. However, it is possible to use specialized models for the classification and each experts.
-However, Quarkus integration makes straightforward to also turn these LLM services into tools that can be invoked by other LLMs, simply annotating them with `@Tool` followed by a short description of the purpose of that tool, while preserving the possibility of also invoking the single expert directly as an independent LLM service.
+Now, let’s see how we can transform this workflow approach into a more agentic one.
+
+Quarkus integration makes it straightforward to turn these AI “expert” services into _tools_ that another AI service can invoke. You only need to annotate the AI service methods with `@Tool` and configure the caller AI service with `@Toolbox`. This approach preserves the possibility of also invoking the single expert directly as an independent LLM service, and also using specialized models for each expert.
 
 [source, java]
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