When would you use RAG, fine-tuning, prompt engineering, or a rules-based approach?

Focus on understanding the strengths and weaknesses of each approach: Retrieval-Augmented Generation (RAG), fine-tuning, prompt engineering, and rules-based systems. Discuss scenarios where each method excels, such as RAG for dynamic information retrieval, fine-tuning for specific domain adaptation, prompt engineering for optimizing model responses, and rules-based approaches for deterministic outcomes. Be prepared to provide examples of real-world applications for each method and articulate the trade-offs involved in choosing one over the others based on factors like data availability, complexity, and desired outcomes. Highlight your thought process in selecting the most appropriate approach for a given problem.