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  • Writer's pictureAlly Ingram

Prompt engineering tip for the day

Give me a new professional prompt engineering tip for the day. Give examples. Search the web and cite sources.


Prompt engineering is a crucial skill for optimizing the performance of AI models like ChatGPT and generative image platforms. Here are some professional tips and best practices gathered from various sources:

  • Watch for Length: AI models often struggle with very long prompts due to the complexity involved in parsing and prioritizing the elements. It's important to make the prompt as long as necessary but no longer​​.

  • Choose Words with Care: Use clear and direct wording. Avoid ambiguity, colorful language, metaphors, and slang, as they can produce unexpected results. However, sometimes ambiguity can be used deliberately to provoke unexpected outputs​​.

  • Pose Open-Ended Questions or Requests: Generative AI is designed to create, so open-ended questions are more likely to yield detailed and comprehensive outputs​​.

  • Include Context: Adding context to your prompts helps AI models tailor their output to the intended audience and the level of detail required​​.

  • Set Output Length Goals or Limits: While AI tools generally can't adhere to precise word or character limits, they can follow approximate guidance like "Provide a two- or three-sentence response"​​.

  • Avoid Conflicting Terms: Ensure all terms in the prompt are consistent and avoid negative language unless necessary​​.

  • Use Punctuation to Clarify Complex Prompts: Punctuation helps AI models parse and operate on complex prompts more effectively​​.

  • Embedding and Model Fine-Tuning: Understanding and utilizing embedding and fine-tuning can optimize AI performance for specific tasks or behavior characteristics​​.

  • Importance of Prompt Engineering: Tailoring AI outputs, enhancing user experience, and scaling solutions are key aspects. For instance, role prompting can guide AI's responses based on a specific context or domain​​.

  • Benefits of Prompt Engineering: Enhanced maneuverability, creativity, precision, propriety, and adaptability of AI models are significant benefits of effective prompt engineering​​.

  • Basic Concepts of Prompt Design: Clarity, context, brevity, explicitness, iteration, and experimentation are essential in crafting effective prompts​​.

  • Types of Prompts: Role prompting, shot prompting, option-based prompting, etc., can be used to adapt AI models to various situations and queries​​.

These tips showcase the importance of precise, context-aware, and thoughtful prompt engineering in leveraging the full potential of AI models for various applications.

give examples of each


Certainly! Here are examples for each of the prompt engineering tips mentioned:

  • Watch for Length:

  • Too Long: "Please provide a detailed analysis of the economic impacts of climate change on different industries, including but not limited to agriculture, technology, manufacturing, and energy, considering various global regions and potential future scenarios."

  • Optimized: "Summarize the impact of climate change on agriculture and technology industries."

  • Choose Words with Care:

  • Ambiguous: "Tell me something cool about space."

  • Clear: "Explain the concept of black holes in space."

  • Pose Open-Ended Questions or Requests:

  • Closed: "Did the Roman Empire fall in 476 AD?"

  • Open-Ended: "Explain the factors leading to the fall of the Roman Empire."

  • Include Context:

  • Without Context: "Explain quantum computing."

  • With Context: "Explain quantum computing for high school students."

  • Set Output Length Goals or Limits:

  • Without Length Goal: "Describe the process of photosynthesis."

  • With Length Goal: "In two sentences, summarize photosynthesis."

  • Avoid Conflicting Terms:

  • Conflicting: "Give me a brief, detailed report on the French Revolution."

  • Non-Conflicting: "Provide a brief overview of the French Revolution."

  • Use Punctuation to Clarify Complex Prompts:

  • Without Punctuation: "Explain the causes of World War II and its effects on Europe."

  • With Punctuation: "Explain the causes of World War II; then, describe its effects on Europe."

  • Embedding and Model Fine-Tuning:

  • General: "How can I improve customer satisfaction?"

  • Fine-Tuned: "Based on recent customer feedback data, suggest specific strategies to improve customer satisfaction in our online retail store."

  • Importance of Prompt Engineering:

  • Role Prompting Example: "As a nutritionist, list five beneficial foods for heart health."

  • Benefits of Prompt Engineering:

  • Enhanced Creativity: Instead of asking, "What are the benefits of exercise?", using a creative prompt like, "Imagine exercise as a medicine. Describe its benefits and recommended dosage."

  • Basic Concepts of Prompt Design:

  • Explicitness: "List three major causes of the French Revolution and their implications."

  • Types of Prompts:

  • Shot Prompting: "What is the capital of France?"

  • Role Prompting: "As a historian, describe the significance of the Renaissance period."

  • Option-Based Prompting: "Evaluate the pros and cons of renewable energy versus fossil fuels."

These examples illustrate how different approaches and refinements in prompt engineering can significantly alter the AI model's responses, leading to more precise, relevant, and useful outputs.

Include complete source citations and include the full URLs


Sure, here are the complete source citations with full URLs for the information provided:

  • Lakera - "A Step-by-step Guide to Prompt Engineering: Best Practices, Challenges, and Examples":

  • Source: Lakera

  • URL:

  • LambdaTest - "Prompt Engineering Tutorial: A Comprehensive Guide With Examples And Best Practices":

  • Source: LambdaTest

  • URL:

These sources provide a comprehensive overview of prompt engineering, including best practices, techniques, and examples.

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