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5.3 - Examples of Good vs Bad Prompts

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Understanding Poor vs Good Prompts

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Teacher
Teacher

Today, we will talk about the difference between poor prompts and improved prompts. Can anyone give an example of a prompt they think might not work well?

Student 1
Student 1

What about 'Tell me about climate change?' That's so broad!

Teacher
Teacher

Exactly! It lacks specificity. A better approach would be 'Write a 3-paragraph summary explaining the causes and effects of climate change.' This way, the model knows exactly what to provide.

Student 2
Student 2

So, it's all about being clear?

Teacher
Teacher

Yes! Remember, clarity is key. We want to minimize ambiguity in our prompts.

Teacher
Teacher

Can anyone summarize why a specific prompt is important?

Student 3
Student 3

It helps in guiding the AI towards a specific answer without getting lost in too much information.

Teacher
Teacher

Great summary! Now let's move on to some specific examples of prompts.

Examples of Improved Prompts

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Teacher
Teacher

Let's take a look at another example. Instead of asking 'Give feedback on this resume,' how can we improve it?

Student 4
Student 4

Maybe say 'Act as a hiring manager. Give 3 strengths and 2 weaknesses in this resume.'

Teacher
Teacher

Exactly! By specifying the role, we shape the response. This specificity makes a huge difference in the quality of insights gathered.

Student 1
Student 1

What about summarizing an article?

Teacher
Teacher

Good question! Instead of 'Summarize this article,' you could say 'Summarize this article in 5 bullet points using clear, concise language.' It provides a clear structure and expectations.

Student 2
Student 2

So it's clear that structure helps with the outcome!

Teacher
Teacher

Absolutely! Remember, the better the input, the better the output.

Teacher
Teacher

Can anyone summarize the key points we discussed in this session?

Student 3
Student 3

It’s important to have clear, structured, and specific prompts to get the best AI responses.

Summary and Application

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Teacher
Teacher

Alright! To wrap up, can someone explain what we mean by better prompts leading to better outputs?

Student 4
Student 4

Better prompts are clearer and give more direction to the AI so it can respond accurately!

Teacher
Teacher

Exactly! And can we think of a situation where these prompt improvements could be applied?

Student 1
Student 1

When asking for any kind of report or feedback!

Teacher
Teacher

Very good! Crafting better prompts can significantly enhance our interactions with AI. Let's make sure to apply these ideas!

Introduction & Overview

Read a summary of the section's main ideas. Choose from Basic, Medium, or Detailed.

Quick Overview

This section presents distinctions between poorly designed and well-designed prompts.

Standard

This section highlights the importance of crafting specific prompts and offers examples of poor versus improved prompts. It emphasizes that clarity, structure, and precision in prompt design lead to better AI responses.

Detailed

Examples of Good vs Bad Prompts

This section discusses how the effectiveness of AI responses can be significantly influenced by the quality of prompts provided. It outlines the importance of crafting prompts that are clear, specific, and structured to guide AI models effectively.

Poor vs Improved Prompts

A well-designed prompt tends to minimize ambiguity while guiding the model towards the desired response. Here are some key contrasts:

  1. “Tell me about climate change” vs “Write a 3-paragraph summary explaining the causes and effects of climate change.”
    The improved prompt specifies the length and scope of the response.
  2. “Give feedback on this resume.” vs “Act as a hiring manager. Give 3 strengths and 2 weaknesses in this resume.”
    The latter clearly defines the perspective and the number of points expected.
  3. “Summarize this article.” vs “Summarize this article in 5 bullet points using clear, concise language.”
    Clarity and formatting expectations are provided here.

The principle underlying these examples is simple: the better the input (prompt), the better the output (response) from the model. Therefore, applying the prompt design principles discussed in earlier sections—such as clarity, specificity, and structure—results in more effective interaction with AI.

Audio Book

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Understanding Poor Prompts

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❌ Poor Prompt
“Tell me about climate change.”

Detailed Explanation

The poor prompt presented here lacks specificity and clarity. Simply asking, 'Tell me about climate change' is too vague. There are numerous aspects of climate change, from its causes and effects to statistics, and it's unclear what kind of information the AI should focus on. Without a clear directive, the AI's response may be unfocused or too general, leading to an output that doesn’t effectively meet the user's needs.

Examples & Analogies

Imagine asking a friend at a party to 'Tell me about history.' Your friend might feel overwhelmed and not know where to start — should they tell you about ancient civilizations, the World Wars, or a specific historical figure? A clearer question helps your friend give you a detailed and relevant answer.

Improvement through Clarity

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✅ Improved Prompt
“Write a 3-paragraph summary explaining the causes and effects of climate change.”

Detailed Explanation

The improved prompt is significantly more effective because it specifies the desired output. It requests a 3-paragraph summary and explicitly states that the focus should be on both causes and effects of climate change. This structure guides the AI toward generating a more organized and relevant answer that meets the user’s expectations.

Examples & Analogies

Think of this like giving a chef a recipe. If you just say, 'Make something with chicken,' you might get something completely different each time. But if you specify, 'I want a roasted chicken with herbs and vegetables,' the chef has a clear roadmap to follow, resulting in a consistent and desired dish.

Issues with General Feedback Requests

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❌ Poor Prompt
“Give feedback on this resume.”

Detailed Explanation

This poor prompt is problematic because it does not provide any context or criteria for the feedback. Without specified strengths, weaknesses, or specific focus areas (e.g., formatting, content relevance), the AI may struggle to focus its feedback, resulting in vague or irrelevant advice.

Examples & Analogies

Imagine asking a teacher to 'give feedback' on an essay without saying what specific aspects to focus on. The teacher might comment on grammar or ideas but may miss important points you were concerned about, like clarity or argument effectiveness.

Constructive Context for Feedback

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✅ Improved Prompt
“Act as a hiring manager. Give 3 strengths and 2 weaknesses in this resume.”

Detailed Explanation

Here, the prompt clearly defines the role of the AI ('hiring manager') and specifies the structure of the output (3 strengths, 2 weaknesses). This approach minimizes ambiguity, leading the AI to provide targeted and relevant feedback that is more useful to the user.

Examples & Analogies

This is similar to hiring a consultant to improve your resume. If you tell them specifically to look for leadership qualities and project experiences, they will offer insightful and tailored feedback, rather than general comments that may not be helpful.

The Need for Summarization Guidance

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❌ Poor Prompt
“Summarize this article.”

Detailed Explanation

The prompt 'Summarize this article' is too broad and does not provide any framework. Without specific guidance on the type or length of summary, the response can vary widely and lack focus, which may not fulfill the user's expectations.

Examples & Analogies

It’s like asking someone to 'tell you about a movie.' They might highlight different scenes or themes, leading to a summary that doesn’t touch on what you were interested in knowing, like the main plot or characters.

Focused Summarization Request

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✅ Improved Prompt
“Summarize this article in 5 bullet points using clear, concise language.”

Detailed Explanation

This improved prompt is effective because it provides precise instructions. By asking for a summary in ‘5 bullet points’ and specifying the use of ‘clear, concise language,’ the prompt leads the AI to produce a structured and digestible response that meets user expectations.

Examples & Analogies

Think of this like organizing your grocery list. If you simply think of what you need, you might forget an essential item. However, if you write your list with specific categories like dairy, produce, and meat, you ensure you gather everything efficiently and don’t miss anything important.

Definitions & Key Concepts

Learn essential terms and foundational ideas that form the basis of the topic.

Key Concepts

  • Clarity: Clear prompts result in better understanding and responses.

  • Specificity: Specific prompts guide AI to precise outputs.

  • Structure: Well-structured prompts reduce errors and enhance clarity.

Examples & Real-Life Applications

See how the concepts apply in real-world scenarios to understand their practical implications.

Examples

  • A poor prompt: 'Summarize this book.' A good prompt: 'Summarize the main themes of this book in three sentences.'

  • A poor prompt: 'Tell me a story.' A good prompt: 'Write a short story about a dog who finds a hidden treasure.'

Memory Aids

Use mnemonics, acronyms, or visual cues to help remember key information more easily.

🎵 Rhymes Time

  • To get the best from the AI's quest, make your prompts clear, specific, and structured; that’s the test!

📖 Fascinating Stories

  • Think of a chef in a kitchen; only with the right recipe can they create the perfect dish.

🧠 Other Memory Gems

  • Remember CSS: Clarity, Specificity, Structure for great AI interactions!

🎯 Super Acronyms

PACE

  • Prompts Are Clear and Effective.

Flash Cards

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Glossary of Terms

Review the Definitions for terms.

  • Term: Prompt

    Definition:

    An input given to an AI model that specifies the task to be performed.

  • Term: Clarity

    Definition:

    The quality of being clear and understandable in language or instruction.

  • Term: Specificity

    Definition:

    The quality of being specific, precise, and not vague or ambiguous.

  • Term: Structure

    Definition:

    The arrangement of ideas or instructions in a coherent and logical format.