What is prompt engineering?
Prompt engineering is the art of crafting or designing prompts to unlock desired outcomes from large language models or AI systems. The concept of prompt engineering revolves around the fundamental idea that the quality of your response is intricately tied to the quality of the question you pose. By strategically engineering prompts, one can influence the generated outputs and improve the overall performance and usefulness of the system. In this section, we will learn about the necessary elements of effective prompt design, prompt engineering techniques, best practices, bonus tips, and tricks.
Elements of a good prompt design
Designing a good prompt is important because it significantly influences the output of a language model such as GPT. The prompt provides the initial context, sets the task, guides the style and structure of the response, reduces ambiguities and hallucinations, and supports the optimization of resources, thereby reducing costs and energy use. In this section, let’s understand the elements of good prompt design.
The foundational elements of a good prompt include instructions, questions, input data, and examples:
- Instructions: The instructions in a prompt refer to the specific guidelines or directions given to a language model within the input text to guide the kind of response it should produce.
- Questions: Questions in a prompt refer to queries or interrogative statements that are included in the input text. The purpose of these questions is to instruct the language model to provide a response or an answer to the query. In order to obtain the results, either the question or instruction is mandatory.
- Input data: The purpose of input data is to provide any additional supporting context when prompting the LLM. It could be used to provide new information the model has not previously been trained on for more personalized experiences.
- Examples: The purpose of examples in a prompt is to provide specific instances or scenarios that illustrate the desired behavior or response from ChatGPT. You can input a prompt that includes one or more examples, typically in the form of input-output pairs.
The following table shows how to build effective prompts using the aforementioned prompt elements:
Figure 5.5 – Sample Prompt formula consisting of prompt elements with examples