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

@@ -56,7 +56,7 @@ One of the examples included in the pull request mentioned earlier illustrates t
 
 To put this approach into practice, the entire agentic system must define a final goal, and each subagent must declare its own preconditions, the requirements needed to perform its task,  and postconditions, which describe the outcomes guaranteed once execution is complete. However, in agentic LangChain4j, all this information is already implicitly available: the preconditions and postconditions correspond to each agent’s required inputs and produced outputs, while the final goal represents the desired outputs of the entire agentic system.
 
-Following this idea, it is possible to calculate a dependency graph of all the subagents participating in the agentic system, and then to implement a `Planner` that is capable of analyzing the initial state of the `AgenticScope`, comparing it with the desired goal, and then using that graph to determine the sequence of agent invocations that can lead to the achievement of that goal.
+Following this idea, we can calculate a dependency graph of all the subagents participating in the agentic system. Based on that graph, it’s then possible to implement a `Planner` capable of analyzing the initial state of the `AgenticScope`, comparing it with the desired goal, and determining the sequence of agent invocations that can lead to achieving that goal.
 
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