A developer uses local LLMs to evaluate e-commerce search relevance by comparing product attributes against human-labeled data from Wayfair's WANDS dataset. They test various prompting strategies—including forced decisions, consistency checking, and single-attribute analysis—to create a reliable laptop-based search judge that can guide relevance improvements without expensive API costs.