The study evaluates different orchestration mechanisms for AI agents in customer service, highlighting that declarative agents with natural-language skill files outperform imperative agents in accuracy and error reduction when retrieval quality is high. However, all agents struggle significantly when faced with incomplete or skewed evidence, indicating that retrieval quality is crucial for performance.