Parallel voting and adaptive model selection: smarter agentic AI on a budget

In a previous article we discussed why no single agentic pattern can cover all use cases, and introduced a generic Planner abstraction that allows users to define their own orchestration strategies and combine them with the ones provided by LangChain4j out-of-the-box. For instance, there we demonstrated how a goal-oriented pattern could be extended with a reflection loop to iteratively refine a piece of generated content. Among other things, that example highlighted that having an agent evaluate its own output and loop until it reaches a quality threshold is a powerful technique.