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tags: Superprompting_guide
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# Superprompting
## Getting the most out of ChatGPT and friends

*Martin Callaghan*
*School of Computing, University of Leeds*
*April 2023*

The development of large language models (LLMs) like ChatGPT (in it's various incarnations) is beginning to have a significant impact on various areas in Higher Education, including teaching, research and administration.

However, to fully harness the power of these new tools, crafting high-quality prompts or "SuperPrompts" is a key skill. By using SuperPrompts, users can significantly improve the efficiency and effectiveness of LLM-generated responses, producing better outcomes and getting closer to the reequired objectives.

Better prompts lead to more accurate, relevant, and contextually appropriate responses, reducing the need for repeated iterations of questions (and the inevitable frustrations from the user...) and saving time for both lecturers and researchers.

SuperPrompts enable users to extract more value from LLMs, as the models can produce precise, well-structured, and nuanced responses tailored to the user's requirements.

Developing SuperPrompts is particularly important in pedagogical and management contexts, where clarity, context, and relevance are paramount. The use of SuperPrompts in education ensures that LLMs contribute effectively to the learning process, engaging students and addressing their diverse learning needs (Brown, Roediger III, & McDaniel, 2014).

In management and administration, the use of well-crafted prompts can streamline operations, enhance decision-making, and support better resource allocation (Drucker, 2006). I've seen discussions across social media that the use of LLM-based tools could potentially improve productivity by a multiplier of 7.

So, creating and using SuperPrompts effectively is essential for maximising the potential of LLMs like ChatGPT. By investing a little time and effort in crafting those high-quality prompts (and getting a few templates together for prompts that meet their needs), users can obtain more accurate and relevant responses, ultimately leading to more efficient and effective use of these powerful models in various applications.

### References
Brown, P.C., Roediger III, H.L. and McDaniel, M.A., 2014. *Make it stick: The science of successful learning*. Harvard University Press.

Drucker, P. F. (2006). *The Effective Executive: The Definitive Guide to Getting the Right Things Done*. HarperCollins.