This study investigates sophisticated prompting methods used to guide large language models more effectively. I analyzed techniques like zero-shot, CoT, ToT, and persona-based prompting for their ability to improve performance, accuracy, and explainability. In doing so, I also highlighted practical applications, current limitations, and future directions—including how Retrieval-Augmented Generation (RAG) can complement these techniques. The findings are based on a systematic literature review of 74 studies published between 2017 and 2025.
