How to Build Golden Datasets for Testing, Fine-tuning, and Evaluating AI Models

Golden datasets for testing, fine-tuning, and evaluation are three different artifacts. Each has its own quality bar, sourcing method, and failure modes. This guide covers what makes each type effective, where teams go wrong, and how human-in-the-loop annotation infrastructure turns quality principles into measurable, governed datasets.