Insights

Writing on AI testing, evaluation methodology, and quality engineering practice.

A survey of current practices, tools, and challenges in testing AI-powered software systems.

Traditional software testing paradigms fall short when evaluating large language models. Here is why.

Engineering patterns for testing and validating multi-step agent workflows in production.

Beyond accuracy: a framework for choosing evaluation metrics that align with real-world requirements.