What is the role of prompt engineering in RAG system quality?

Prompt engineering is critical for RAG quality as it guides the LLM on how to use retrieved context. The system prompt should instruct the model to answer only based on provided context, cite sources, and acknowledge when information is insufficient. Effective RAG prompts include clear role definition establishing the assistant as a domain expert, explicit context usage instructions like only answer from the provided documents, output format specifications like structured responses with headers and bullet points, citation format requirements, handling of uncertainty directing the model to say when it cannot find the answer, and tone and style guidelines matching the organization voice. Avoid prompts that encourage the model to use its own knowledge as this defeats the purpose of RAG grounding. Test prompt variations systematically using evaluation frameworks to measure their impact on faithfulness, relevance, and completeness metrics.