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

@@ -175,7 +175,7 @@ UntypedAgent horoscopeAgent = AgenticServices.plannerBuilder()
 
 == Conclusion
 
-An agentic system made of multiple small but specialized agents can often outperform a single AI services based on a huge LLM at a fraction of the cost. The use of many interoperating agents poses the challenge of coordinating them effectively to achieve complex tasks. Different agentic patterns offer various trade-offs between reliability and flexibility, and no single pattern is suitable for all scenarios. Therefore, a customizable architecture that allows users to define and combine different agentic patterns is essential.
+An agentic system composed of multiple small, specialized agents can often outperform a single large language model–based AI service, and do so at a fraction of the cost. However, using many interoperating agents introduces the challenge of coordinating them effectively to accomplish complex tasks. Different agentic patterns present distinct trade-offs between reliability and flexibility, and no single approach is suitable for all scenarios. This is why a customizable architecture that enables users to define and combine diverse agentic patterns is essential for building truly adaptable AI systems.
 
 By implementing a generic `Planner` interface, LangChain4j enables users to create their own agentic patterns and seamlessly integrate them with existing ones. This flexibility allows for the development of sophisticated agentic systems tailored to specific needs, balancing the strengths of various orchestration strategies.