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Improving ChatGPT Prompts: A Scientific Approach

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Introduction to Prompt Engineering

Crafting effective prompts has emerged as a crucial skill for 2024. Many users have relied on trial and error, along with random advice, to refine their prompts. However, without knowing whether these methods will yield better outcomes, the process can be tedious and time-consuming. Fortunately, recent studies are beginning to apply scientific techniques to assess the effectiveness of various prompting strategies. One notable study by Sondos Mahmoud Bsharat, Aidar Myrzakhan, and Zhiqiang Shen analyzed 26 different strategies.

Principles for Effective Prompting

The following excerpt from their research outlines all 26 prompting strategies evaluated.

Evaluation of Prompting Strategies

As you review this list, you may recognize some techniques you’ve previously encountered or tried, while others may seem unfamiliar or even peculiar. For instance, one strategy suggests, “Add ‘I’m going to tip $xxx for a better solution!’” This notion appears odd, as AI models cannot receive tips, nor would they have an incentive for such an action. The rationale behind this suggestion is that since large language models (LLMs) are trained on content created by humans, they might adapt to perceived motivations such as monetary rewards.

Spoiler: Offering a tip is not an effective way to enhance your prompt.

Top 6 Strategies for Enhancing Your Prompts

Based on the authors' findings, here are the six most effective strategies to improve your prompts:

  1. Incorporate the Audience

    Specify the intended audience in your prompt, for example, indicating that the audience consists of experts in a specific field.

  2. Enable Questioning

    Allow the model to ask clarifying questions to gather sufficient details and requirements from you. A prompt could be: “From now on, I would like you to ask me questions to…”

  3. Utilize Consistent Language

    When requesting text that mirrors a given example, instruct the model to use the same language as found in the supplied material, such as: “Please use the same language based on the provided paragraph.”

  4. Simplify Language

    For clarity or a deeper understanding of a subject, use prompts like: “Explain [specific topic] in simple terms.”

  5. Specify Keywords

    When you wish to guide the text with particular words, phrases, or sentences, prompt with: “I’m providing you with the beginning [text type]: [Insert text]. Finish it based on the provided content while maintaining flow.”

  6. Outline Requirements

    Clearly communicate the criteria that the model must adhere to in order to generate the desired content, using keywords, guidelines, or instructions.

Conclusion: The Science of Prompt Engineering

The advancement of prompt engineering indicates that creating effective prompts is more of a systematic science rather than mere artistic intuition. The research conducted by Sondos Mahmoud Bsharat, Aidar Myrzakhan, and Zhiqiang Shen, which evaluated 26 distinct strategies, sheds light on this vital topic. Their findings emphasize that a solid understanding of specific principles can greatly improve interactions with AI models. Overall, this research underscores the necessity of purposeful and informed prompt crafting, moving beyond the trial-and-error methods that many users, myself included, have depended on for years.

As AI technologies become increasingly integrated into our daily lives, it’s essential to grasp how to engage with them effectively in order to obtain optimal responses.

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