Artificial Intelligence in Education

An overview of Prompt Engineering from Stanford University. Discusses advanced practices that improve performance of customized AI models, and effective techniques in building a consistent and context-specific prompt that others can use.

AI is rapidly becoming a routine part of many of our professional and personal lives. But have you ever been unhappy with the results that AI generated for you? Do you wonder if you’re getting the most out of AI? This article provides an introduction to crafting effective prompts so that you maximize your benefits from AI.

The information, sentences, or questions that you enter into a Generative AI tool (“prompts”) are a big influence on the quality of outputs you receive. More descriptive prompts can improve the quality of the outputs. This guide gives you a basic overview of how to Generate better prompts.

Prompt engineering is the method to ask generative AI to produce what the individual needs. There are two main principles of building a successful prompt for any AI, specificity and iteration. The box below includes one example of a framework that can be applied when prompting any generative AI.

"This guide shares strategies and tactics for getting better results from large language models (sometimes referred to as GPT models) like GPT-4o. The methods described here can sometimes be deployed in combination for greater effect. We encourage experimentation to find the methods that work best for you."