Prompt engineering – the art and science of crafting inputs to generative AI – has rapidly emerged as a foundational skill in leveraging large language models (LLMs) for diverse applications. Since the emergence of generative AI, researchers and practitioners alike have recognized that the effectiveness of AI outputs hinges not only on model architectures and data, but equally on the creativity, clarity, and strategic design of the prompts themselves.
Today, we published our guide to prompt engineering. The 16 pages document provides a structured approach to prompt engineering, illustrating how to design prompts that maximize model performance while aligning with pedagogical goals such as language learning, sustainable development, and Socratic questioning. You can download it for free from our new toolkit page our new toolkit page.