The Quick Guide to Prompt Engineering
Design and use generative AI prompts that get helpful and practical results in this concise and quick start guide. In The Quick Guide to Prompt Engineering, renowned technology futurist and AI thought leader Ian Khan delivers a practical and insightful resource for taking the first steps in understanding and learning how to use generative AI.
Unlocking the Secrets of Prompt Engineering
Enhance your writing with AI by mastering prompt engineering techniques and become an expert in developing and utilizing LLM prompts across applications Key Features Master prompt engineering techniques to harness AI's writing potential Discover diverse LLM applications for content creation and beyond Learn through practical examples, use cases, and hands-on guidance Purchase of the print or Kindle book includes a free PDF eBook Book Description Unlocking the Secrets of Prompt Engineering is your key to mastering the art of AI-driven writing.
Prompt Engineering for Generative AI: Future-Proof Inputs for Reliable AI Outputs
Large language models (LLMs) and diffusion models such as ChatGPT and Stable Diffusion have unprecedented potential. Because they have been trained on all the public text and images on the internet, they can make useful contributions to a wide variety of tasks. And with the barrier to entry greatly reduced today, practically any developer can harness LLMs and diffusion models to tackle problems previously unsuitable for automation.With this book, you'll gain a solid foundation in generative AI, including how to apply these models in practice. When first integrating LLMs and diffusion models into their workflows, most developers struggle to coax reliable enough results from them to use in automated systems. Authors James Phoenix and Mike Taylor show you how a set of principles called prompt engineering can enable you to work effectively with AI.
What is a prompt? What is prompt engineering?
A prompt is the set of instructions or questions provided by the user to the large language model to tell it to perform a task. A user can ask the system to create an output by using plain language. The LLM then utilizes its inner algorithms to return results to the user in a natural language response. The more specific and curated a prompt is, the more tailored the results will be for the user.
The basic components of an engineered prompt will identify what you want the LLM to do, context for why it is needed, expectations for output formatting and tone, and requesting where the information is coming from.
Prompt Engineering Basics
- Use plain language and be specific about what you want the LLM tool to do.
- Provide some background or context for the LLM so that it can produce results specific to your circumstances.
- Specify the tone or style you want the results to be generated, i.e. poetry, classical literature
- Refine results by asking for variations or specific adjustments to results.
The CLEAR Framework for AI Prompts
Generative AI resources require users to provide a prompt to start using the resource. Prompts are the set of instructions provided by the user to the LLM that communicate what you want it to do. Creating well defined prompts will get you better results when using AI. The CLEAR Framework, developed by Leo S. Lo, University of New Mexico, can be used in order to develop productive prompts.
| Concise: Use brief and clear language in prompts. Keep your language concise and explicit. |
| Logical: Use structure and natural progression within your prompt to produce a more natural relationship between concepts. |
| Explicit: Include specifics about the type of information and amount of output you are requesting. |
| Adaptive: Experimenting with various prompt formation will help the user reach the output desired. |
| Reflective: Continue to evaluate and revise upon prompts for perpetually improvement. |
Read more about the CLEAR framework by Lo, L. S. (2023). The CLEAR path: A framework for enhancing information literacy through prompt engineering. The Journal of Academic Librarianship, 49(4), 102720–. https://doi.org/10.1016/j.acalib.2023.102720
Below are video courses available through University Library subscriptions:
- Prompt engineering: for optimal LLM performancePrompt engineering is key to harnessing the immense capabilities of large language models. In this in-depth masterclass, data and AI specialist Valentina Alto unveils the art and science behind crafting effective prompts. You'll learn proven techniques to optimize prompting, control model behavior, reduce risks like hallucination, and overcome limitations.
- Prompt Engineering Deep DiveThis course delves into the emerging field of prompt engineering, focusing on how to effectively interact with AI models to achieve precise outcomes. As AI becomes increasingly integrated into various professional fields, understanding how to communicate with these systems is crucial. This course addresses common challenges faced by AI and data professionals, software developers, and business analysts in extracting accurate and relevant responses from AI models.