AI Behavior Monitoring: A New Framework for Evaluating Generative Models

As generative AI systems become more advanced, evaluating their unpredictable behavior presents a growing challenge. A new paradigm called the AI Evaluation Stack is emerging to address this need, offering a structured approach to testing and quality assurance. This framework emphasizes the importance of using both deterministic and model-based assertions to rigorously assess AI outputs. By adopting such methods, developers can better monitor AI behavior and ensure reliability in real-world applications. The approach is particularly relevant for generative AI, where traditional evaluation metrics often fall short.