Authors - Devang Rupesh Dalvi, Gaurav Suresh Malik, Abhishek Jairaj Kunder Abstract - Prompt engineering has emerged as an essential paradigm in leveraging desired behaviors from large language models (LLMs) without altering their parameters. Although the majority of the current literature has revolved around the introduction of novel prompt engineering strategies, there has been comparatively less emphasis on the contribution of the evaluation and optimization of prompts in concrete systems. In this paper, we offer a specialized review of prompt engineering from an evaluation/optimization centric viewpoint with a larger nod to conceptual developments and illumination rather than detailing the comparisons of approaches. Furthermore, we attempt to establish the concrete importance of prompt engineering via a real-life application, which resulted in improved performances in tasks through the process of prompt refinement and informal evaluations without the need to change the architecture and weights of the models. The paper will also introduce the deficiencies in prompt engineering in the realms of re-producibility, robustness, and the unavailability of standardized approaches in the aspect of concrete evaluations.
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