Prompt Engineering: The Art of Getting What You Need From Generative AI

An Ivan Allen College communicator went to prompt engineering school with Assistant Professor Yeqing Kong. In this article, she shares what she learned.

a robot hand reaches out to a human hand

By Stephanie N. Kadel

If you’ve spent even an hour or two on ChatGPT or another generative AI model, you know that getting it to generate the content you want can be challenging and even downright frustrating.

Prompt engineering is the process of crafting and refining a specific, detailed prompt — one that will get you the response you need from a generative AI model. This kind of “coding in English” is a complex and tricky process. Fortunately, our faculty at the Ivan Allen College of Liberal Arts at Georgia Tech are engaged in teaching and research in this exciting emerging field.

I met with Assistant Professor Yeqing Kong in the School of Literature, Media, and Communication to talk about prompt engineering. She shared three approaches to crafting a prompt that she has collected from leading experts. Kong will be teaching these methods, and much more, in her new Fall 2024 course, “Responsible AI for Communication.”

“This new course aims to equip students with the skills to integrate AI tools into the content creation process in ways that are both effective and ethical,” says Kong.

After we spoke, Kong invited me to try crafting a prompt using the rhetorical approach, the C.R.E.A.T.E. framework, and the structured approach to prompt engineering. These methods, as well as my results, are described below. I hope you’ll try these approaches on a prompt of your own!

Where I Started Out

For the purposes of this article, I decided to see if I could get ChatGPT to write a short social media post for this article. Here is my first attempt, without any of Kong’s methods applied:

Writer: “Write a 50-word social media post to share an article on AI Prompt Engineering Methods.” ChatGPT: “Dive into the latest advancements in AI prompt engineering methods! Our article explores innovative techniques shaping the future of AI interaction. From fine-tuning prompts to optimizing outputs, discover how these strategies are revolutionizing the way we interact with artificial intelligence. Check it out now! #AI #Engineering #Innovation”

Now let’s apply some of the prompt engineering methods Kong shared with me.

Method No. 1: The Rhetorical Approach

The rhetorical approach to prompt engineering was developed by Sébastien Bauer, an academic at the Universitat Autònoma de Barcelona. This method involves describing your main claim — “THE most crucial point,” as he puts it — and then your rhetorical situation. As part of this approach, the prompt may include descriptions of:

  • The audience.
  • The context. Where will the audience read this?
  • The author and ethos. This might include your role or credentials.
  • Pathos. What should your audience feel or believe?
  • Logos. What logical points do you want to emphasize?
  • Arrangement. For example, chronological or alphabetical.
  • Style and delivery. For example, “Limit your response to 100 words and avoid using the second person.”

Since I didn’t really have an explicit or challenging point to support in my social media post, I described the rhetorical situation in my prompt.

Writer: “Write a 50-word social media post for LinkedIn to share an article I wrote on AI prompt engineering methods that were curated by Assistant Professor Yeqing Kong at Georgia Tech. Add that I used these methods to prompt ChatGPT to write this social media post. My audience is primarily Georgia Tech faculty, staff, students, and administrators. I want to encourage them to read the article, and hope they will feel enthusiastic about trying out the methods for themselves.” ChatGPT: “Excited to share my latest article on AI prompt engineering methods, curated by Assistant Professor Yeqing Kong at Georgia Tech! Dive in to discover innovative techniques. Bonus: this post was generated using these methods to prompt ChatGPT! Georgia Tech faculty, staff, students, and administrators, let's explore and experiment together! #AI #GeorgiaTech #Innovation”

If you get a response that’s off the mark, don’t give up! Revise and resubmit. In all, I went through about eight iterations before I got to the final version of this prompt. (For those interested, details are in the sidebar.)

Refining a Prompt

Prompt engineering is definitely a refinement process, and I got better at it as I went along. Identifying and addressing information that the AI finds confusing or extraneous is key.

For example, I told ChatGPT that I’m Gen X in one version, in hopes that it would infer something about my social media style. Instead, it included this odd sentence about being “a proud Gen X member” and made the post sound like a sales pitch. (“Don’t miss out!”)

I took out the Gen X bit and told it the post is for LinkedIn, which solved these issues. But it still wasn’t quite what I wanted, so I kept going. The final result (pictured in the article) was much closer to what I wanted.

Method No. 2: The C.R.E.A.T.E. Framework

In the C.R.E.A.T.E. approach developed by AI consultant and author Dave Birss, prompts are framed by addressing the AI as “you.” The acronym stands for:

  • Character – Describe the role the AI is to assume. Kong says you can add in aspirational elements like “You are an experienced writer who crafts concise text without filler words or jargon”
  • Request – Clearly and specifically define the request. “I want you to…”
  • Examples – Give examples if you have them
  • Additions – Refine the task. Describe a point of view to consider or a style to use
  • Type of Output – For example, a 100-word summary or a chronologically organized bio
  • Extras – Any further information you wish to provide, including reference text

The resulting prompt is a little like an instructor’s assignment, as you can see:

Writer: “You are an experienced writer who creates news articles about the exciting work happening at the Ivan Allen College of Liberal Arts at Georgia Tech. I want you to create a LinkedIn post to share your latest article, which describes three approaches to AI prompt engineering. These approaches were curated by Georgia Tech Assistant Professor Yeqing Kong, who will be teaching a course in prompt engineering in Fall 2024. Limit your response to 60 words, and credit ChatGPT with writing this post.” ChatGPT: “(rocket emoji) Exciting News from Ivan Allen College of Liberal Arts at Georgia Tech! (world emoji) Explore the latest article on AI prompt engineering, featuring three curated approaches by Assistant Professor Yeqing Kong. Get ahead in the AI game! (robot emoji; book emoji) Fall 2024 brings a must-attend course by Prof. Kong. Kudos to ChatGPT for crafting this insight! #AI #Education #TechInnovation #GeorgiaTech #ChatGPTWrites (newspaper emoji, sparkle emoji)”

More information on the C.R.E.A.T.E. approach is available in Birss’ LinkedIn Learning course.

Method No. 3: The Structured Approach

The structured approach was developed by Lance Cummings, an AI content specialist and an associate professor at the University of North Carolina Wilmington.

The formula for this approach, as Cummings describes it in “The Anatomy of a Prompt,” is as follows:

  1. Start with a role and a goal. Broadly describe the overarching aim and purpose
  2. Provide context and background
  3. Clearly define the task. Make your expectations explicit and detailed
  4. Provide any reference content the AI will need to complete the task

To try out Cummings’ approach, I pasted the draft content of this article (up to this point), following this text:

Writer: “You are a writer who creates news content for Georgia Tech's Ivan Allen College of Liberal Arts. I need you to create a 60-word LinkedIn post to accompany your latest article. Please highlight what's most exciting about the article. Credit ChatGPT with writing the social media post. The post should generate interest in reading and in trying some of the methods described. To craft the post, please refer to the following draft text of the article: Prompt Engineering: The Art of Getting What You Need From Generative AI”

ChatGPT responded:

ChatGPT: “(rocket emoji) Exciting News from Ivan Allen College of Liberal Arts at Georgia Tech! (Earth emoji) Explore the latest article on AI prompt engineering, featuring three curated approaches by Assistant Professor Yeqing Kong. Get ahead in the AI game! (robot emoji)(book emoji) Fall 2024 brings a must-attend course by Prof. Kong. Kudos to ChatGPT for crafting this insight! #AI #Education #TechInnovation #GeorgiaTech #ChatGPTWrites (newspaper emoji)(sparkle emoji)”

I plan to post the response I got using Method #1 (the rhetorical approach), but I'm going to add in a couple of the emojis I got with the response above.

“You don’t need to stick to just one of these methods,” Kong adds. “You can draw elements from all three. Crafting a prompt is about finding the most effective and clear way to present the language model with its task, while providing context, details, and reference material as needed.”

Generative AI Models and the Liberal Arts

In early 2023, it seemed half the world was enthralled — and the other half appalled — by ChatGPT. Some thought generative AI, which creates original content in response to a prompt, would be especially bad news for the liberal arts. A year or so later, Kong disagrees.

“Generative AI has increased the demand for the very skills we worried it would replace, such as writing, editing, and critical thinking,” says Kong. “These liberal arts skills are also the key to prompt engineering.”