Currently, there is no established engineering standard specifically designed for what is referred to as 'prompt engineering'. This predominantly stems from the fact that interactions with a large language model (LLM) are fundamentally non-deterministic, or open-ended in nature. The concept of 'prompt engineering' emerges in this context as a crucial strategy for refining the constraints and guidelines in the instructions that one provides to the LLM. The design and precision of these prompts play a key role in shaping the responses generated by the LLM. Thus, the term 'prompt engineering' essentially signifies the study and practice of optimizing these instruction sets to elicit the most desirable and accurate responses from the LLM.