The article addresses frequently asked questions about AI evaluations (evals), providing insights into best practices for assessing AI products, particularly focusing on error analysis and the iterative process of improving evaluation systems. It emphasizes the importance of domain expertise, systematic testing, and understanding failure modes to enhance AI performance effectively. Additionally, it offers guidance on how to present the value of evaluations to teams and to integrate them into the development process.