Update _posts/2025-11-12-agentic-ai-patterns.adoc

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

Author: mariofusco

_posts/2025-11-12-agentic-ai-patterns.adoc

@@ -101,7 +101,7 @@ image::goap.png[width=50%, align="center", alt="The GOAP-determined sequence of
 
 The primary advantage of this goal-oriented strategy is that it deterministically identifies the shortest sequence of steps necessary to transition from the initial state to the final goal. However, in some cases, a sequence of agent invocations calculated purely along the optimal path in the dependency graph can become a limitation. For instance, by definition, a shortest path contains no loops, yet in practice, a loop may be necessary to allow an agent to reflect on its own work and iteratively refine its output.
 
-As anticipated, the LangChain4j agentic framework allows to overcome this limitation making it possible to seamlessly combine this goal oriented agentic system with any other agentic pattern either provided by the framework or custom made. For instance the final agent generating the writeup could be complemented with a reflection loop, using another agent that provides a score for the generated writeup.
+As mentioned earlier, the LangChain4j agentic framework overcomes this limitation by allowing seamless integration of the goal-oriented system with any other agentic pattern, whether provided by the framework or custom-built. For example, the final agent responsible for generating the write-up could be complemented by a reflection loop, using another agent that evaluates and scores the generated content.
 
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