Medium

This post details the evolution of Palantir's framework for evaluating generative AI systems, focusing on designing testing plans, defining 'good' outputs through syntax and semantics, and leveraging ground truth data. It emphasizes understanding end-to-end workflows and testable AI tasks, and outlines methods for curating evaluation data using benchmarks and domain expertise.