Your guide to mastering prompt patterns
Prompt patterns are reusable strategies for crafting effective prompts, ensuring consistent and high-quality AI responses.
Use prompt patterns when you need predictable outputs, such as generating summaries, answering questions, or creating content in a specific style.
Start with a simple 'Few-Shot' pattern: 'Here are two examples of summaries: [Summary 1], [Summary 2]. Summarize this text: [Text].'
Begin with basic patterns and gradually add complexity as you understand how the AI responds to different structures.
Dive DeeperCore prompt patterns like 'Few-Shot', 'Chain-of-Thought', and 'Role-Play' form the foundation of effective prompt engineering. 'Few-Shot' uses examples to set expectations, 'Chain-of-Thought' encourages step-by-step reasoning, and 'Role-Play' sets a persona for context.
The 'Few-Shot' pattern provides examples to guide the AI, ensuring it follows a specific format or style.
Ideal for tasks requiring a consistent output format, such as summarizing articles, generating lists, or writing in a specific tone.
Give two summaries as examples: 'Summary 1: [Example]', 'Summary 2: [Example]'. Then ask: 'Summarize this text in the same style: [Text].'
Use 2-3 examples for best results; too many can overwhelm the AI, while too few may not provide enough guidance.
The 'Chain-of-Thought' pattern prompts the AI to explain its reasoning step-by-step, improving transparency and accuracy.
Great for complex tasks like problem-solving, logical reasoning, or tasks requiring detailed explanations, such as math problems or decision-making.
Prompt the AI: 'Solve this problem and explain each step: 2x + 3 = 7.' The AI will break down the solution: 'First, subtract 3 from both sides...'
Encourage detailed steps by adding 'show all calculations' or 'explain your reasoning' to the prompt for clearer outputs.
The 'Role-Play' pattern sets a persona for the AI, tailoring its responses to a specific audience or perspective.
Useful for creating audience-specific content, such as explaining concepts to children, professionals, or beginners.
Set the persona: 'You are a teacher explaining photosynthesis to a 5th grader.' The AI will simplify its language: 'Plants use sunlight to make food...'
Be specific about the persona’s expertise and audience to get the most relevant and appropriately toned responses.
The 'Critique then Improve' pattern asks the AI to evaluate and enhance its own output, leading to better quality responses.
Perfect for iterative refinement, such as improving a draft, refining creative writing, or enhancing a generated idea.
Prompt the AI: 'Write a short story, then critique it and provide an improved version.' The AI will analyze its story and suggest improvements.
Ask the AI to focus on specific aspects (e.g., 'critique the plot') to get more targeted improvements.
The 'Zero-Shot' pattern asks the AI to perform a task without examples, relying on its pre-trained knowledge.
Useful for straightforward tasks where examples aren’t needed, such as translations, simple definitions, or basic questions.
Prompt the AI: 'Translate this text to French: [Text].' The AI will perform the task without needing prior examples.
Ensure the task is simple and well-defined, as 'Zero-Shot' may not work well for complex or ambiguous requests.
Prompt patterns can be applied to various tasks—creative writing, problem-solving, and more. Combine patterns for complex needs: use 'Few-Shot' with 'Chain-of-Thought' to guide the AI through a multi-step task with examples.
Use prompt patterns to guide the AI in generating creative content that matches your desired style and tone.
Ideal for writing stories, poems, or scripts where consistency in tone, style, or structure is important.
Use 'Few-Shot' for creative writing: 'Here are two story intros: [Intro 1], [Intro 2]. Write a story intro in the same style.' The AI will match the tone and style.
Combine 'Few-Shot' with 'Role-Play' (e.g., 'You are a novelist') to further refine the AI’s creative output.
Apply prompt patterns to solve complex problems by guiding the AI through logical, step-by-step reasoning.
Useful for tasks like solving math problems, logic puzzles, or decision-making scenarios where detailed reasoning is needed.
Use 'Chain-of-Thought': 'Solve this logic puzzle step-by-step: [Puzzle].' The AI will break down its reasoning: 'First, let’s identify the clues...'
If the AI skips steps, add 'explain each step in detail' to the prompt to ensure a thorough breakdown.
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