Evaluating AI Search in the Agentic Era

You.com released a four-phase evaluation framework for AI search and retrieval systems, covering golden query set construction and hybrid semantic-keyword accuracy metrics. The methodology addresses a critical gap for teams building agentic pipelines where retrieval quality directly impacts downstream reasoning. Engineers deploying RAG systems or tool-augmented agents should treat this as a practical benchmarking blueprint, particularly for query coverage and recall measurement. Compared to ad hoc retrieval evals, the structured golden set approach enables reproducible, comparable performance tracking across model and index iterations.