Imagine having a quick, reliable way to get answers to complex questions about coal mining—everything from safety protocols to the risks of methane gas accumulation. That's the potential of AI-powered question answering systems. But coal mining is a unique beast; it's a complex field with ever-changing regulations and specific technical jargon. How can AI be smart enough to handle it? A new research paper explores the innovative use of "multi-turn prompt engineering" with large language models (LLMs) like GPT-4 to tackle this challenge. Instead of just throwing a question at the AI, researchers guide it through a series of structured prompts. Think of it like having a conversation with the AI, where you break down a complicated question into smaller, more digestible pieces. This allows the LLM to process information more effectively, focusing on relevant details without getting lost in technical jargon. This approach was tested with 500 real-world coal mining questions, ranging from straightforward queries to more open-ended, complex scenarios. The results were impressive. Compared to simply asking the AI a question directly, the multi-turn prompting method led to a significant boost in accuracy—around 15-18%! This suggests that LLMs, when properly guided, can be incredibly valuable tools for information retrieval in highly specialized fields like coal mining. This technology could revolutionize how miners access critical information, leading to quicker decision-making, improved safety, and more efficient operations. While further research is needed to explore the long-term implications and challenges, this study opens exciting new avenues for the application of AI in high-stakes industrial environments.