1. Prompt Analysis Basics

Lesson 1: Understanding Prompt Structure

1.1 What is a Prompt?

A prompt is a set of instructions or input that guides a model, like GPT, to generate a response. It can vary in complexity, from a simple question to a detailed scenario.

1.2 Key Components of a Prompt

• Context: Provides necessary background information.
• Objective: The specific task or question that the model should answer.
• Constraints/Guidelines: Any specific rules or boundaries for the response.
• Format: The preferred structure or tone for the answer (e.g., narrative, technical, concise).

Example Prompt Breakdown

Write a short story about a robot discovering emotions.

Component	Example
Context	Robot exists in a futuristic world
Objective	Write a short story
Constraints	Focus on the robot's emotional journey
Format	Narrative form, creative tone

1.3 Flow of Prompt Creation

A structured process for prompt creation ensures that important details are not overlooked.

graph TD;
    A[Define Context] --> B[State Objective];
    B --> C[Add Constraints];
    C --> D[Choose Format];
    D --> E[Test Prompt];

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Lesson 2: Critical Analysis of Prompts

2.1 Evaluating Prompt Clarity

A prompt should be easy to understand, with minimal ambiguity. Use the following checklist:

• Does the prompt provide enough background?
• Is the task clearly stated?
• Are there any potential misinterpretations?

Example

Describe the features of a smart device.

• Ambiguity: What kind of smart device? Phone, watch, speaker?
• Refinement: "Describe the key features of a smart speaker."

2.2 Analyzing Prompt Scope

Scope refers to the breadth of the task:

• Too Broad: “Tell me about technology.”
• Too Narrow: “Describe the weight of the iPhone 12.”
• Balanced: “Explain the impact of AI on modern technology in 200-300 words.”

2.3 Evaluating Output

Analyze how well the generated response meets expectations:

• Relevance: Does the response answer the prompt?
• Detail: Is it too vague or too specific?
• Structure: Is the response in the desired format?

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Lesson 3: Why Some Prompts Work

3.1 Examples of Successful Prompts

Prompt 1:

Write a persuasive email to your boss explaining why you deserve a promotion.

• Why it works:
  • Clear objective (write an email).
  • Defined task (persuade for a promotion).
  • Sets a scenario that’s easy to visualize.

Prompt 2:

Generate a list of 5 healthy breakfast ideas that can be made in under 10 minutes.

• Why it works:
  • Specific task (generate 5 ideas).
  • Constraints (healthy, quick to prepare).

3.2 Key Factors of Effective Prompts

• Clarity: The model can easily understand the task.
• Specificity: Narrow focus leads to relevant and concise responses.
• Context: Provides enough background for a well-informed answer.

3.3 Flow Diagram for Successful Prompts

graph TD;
    A[Clear Objective] --> B[Provide Context];
    B --> C[Specify Constraints];
    C --> D[Test and Iterate];

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Lesson 4: Practical Example: Writing a Good Prompt

4.1 Example Task

You want to generate an informative blog post about AI applications in healthcare.

Prompt:

Write a blog post discussing 3 major applications of AI in healthcare. Focus on how these technologies are improving patient outcomes.

4.2 Key Components

Component	Example
Context	AI is being used in healthcare
Objective	Write a blog post
Constraints	Focus on 3 major applications, emphasize patient outcomes
Format	Informative, professional tone

4.3 Code Example

If you're automating prompt generation for various tasks, here’s a Python snippet using GPT-like models:

import openai

def generate_blog_post(prompt):
    response = openai.Completion.create(
        engine="text-davinci-003",  # Model
        prompt=prompt,
        max_tokens=500,  # Length of response
        n=1,
        stop=None,
        temperature=0.7  # Creativity control
    )
    return response.choices[0].text.strip()

# Example prompt
prompt_text = "Write a blog post discussing 3 major applications of AI in healthcare."
print(generate_blog_post(prompt_text))

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References

1. OpenAI Documentation: Prompt Design Guide
2. "Designing Prompts for Maximum Impact" - Jane Smith, AI Journal, 2022.
3. Python's openai library for text generation.