What practice involves crafting inputs to improve AI output?

Prompt engineering is the practice of designing and refining the inputs given to AI systems to enhance the quality and relevance of the outputs they generate. This technique is particularly crucial in the context of large language models and other AI-driven applications, where the way a question or prompt is framed can significantly impact the AI's response. By experimenting with different phrasing, structure, and detail within the inputs, practitioners can better steer the AI to produce more accurate, contextually relevant, and insightful answers.

In contrast, data governance focuses on managing and ensuring the availability, usability, integrity, and security of data within an organization. Digital transformation refers to the broader process of incorporating digital technology into all areas of a business, fundamentally changing how you operate and deliver value to customers. Structured data pertains to information that is organized in a defined manner (like databases) and is easily searchable, but it is not specifically about crafting inputs for AI systems. Thus, prompt engineering uniquely addresses the task of enhancing AI output through carefully constructed inputs.