This blog post discusses the evaluation framework employed by Red Hat for developing the it-self-service-agent AI quickstart. It details the iterative testing approach necessary for AI systems that generate variable outputs, emphasizes the importance of comprehensive evaluations, and outlines key stages of testing, including manual and automated evaluations with custom metrics. The post serves as a guide on implementing evaluations in agentic AI development to meet business goals effectively.