A developer builds an eval suite to test a RAG pipeline that answers questions from a 500-page internal knowledge base. The eval suite includes 100 test questions covering all topics. After prompt changes, aggregate accuracy across all 100 questions remains 85% on both old and new prompts. However, user complaints spike about incorrect answers in a specific domain. What is the issue with the current eval approach, and what is the fix?