Complete Guide

Master the Art of Prompting

Learn 7 powerful prompting strategies with interactive examples and real-world use cases. From beginners to experts, discover techniques that will transform how you work with AI.

Zero-shot

Beginner

"Clear instructions, instant results"

What is Zero-shot?

Zero-shot prompting means giving the AI clear, direct instructions without providing any examples. It's the simplest and most straightforward approach - you tell the AI exactly what you want, and it delivers based purely on its training.

How it works

InstructionOutput

When to use Zero-shot?

Quick Answers

Get immediate responses to straightforward questions or simple tasks.

Content Generation

Create emails, summaries, or basic content with clear specifications.

Simple Commands

Execute direct tasks like translations, formatting, or basic coding.

Creative Writing

Generate stories, poems, or creative content with specific guidelines.

See the Difference

Before
Basic Prompt
Write an email to a customer
After
Enhanced with Strategy
Write a professional email to a customer with the following requirements:
- Tone: Friendly yet professional
- Purpose: Apologize for delayed shipment
- Include: Estimated delivery date (May 15th), discount code for next purchase (SAVE20)
- Length: 3-4 paragraphs
- Signature: Use company name "TechStore"
Expected Results
Basic Response:

Basic email without clear direction or structure...

Enhanced Response:

Well-structured, professional email with all required elements, appropriate tone, and proper formatting.

Example Prompts

Email WritingBusiness
Write a professional email to schedule a meeting with a client. Include:
- Greeting with client's name (John)
- Purpose: Discuss Q2 product roadmap
- Suggest 3 time slots next week
- Keep it under 150 words
- Professional but friendly tone
Content SummarizationContent
Summarize this article in 3 bullet points, focusing on:
- Main findings
- Key statistics
- Actionable takeaways
Keep each bullet point under 20 words.

Try it Yourself

Pro Tips

  • Be specific about tone, length, and format requirements
  • Include concrete details instead of vague descriptions
  • Specify the output structure (bullet points, paragraphs, etc.)
  • Define your audience to help the AI adjust appropriately

Common Mistakes to Avoid

  • Being too vague (e.g., 'write something good')
  • Assuming the AI knows your context without explaining
  • Not specifying format or length, leading to inconsistent results

When NOT to Use

Avoid zero-shot for complex tasks requiring specific patterns, formats that need examples to understand, or when you need the AI to follow a very particular style.

📚

Few-shot

Beginner

"Learn by example"

What is Few-shot?

Few-shot prompting provides the AI with 2-3 example input-output pairs before asking it to complete your task. The AI learns the pattern from your examples and applies it to new inputs. It's like showing someone how to do something a few times before asking them to do it themselves.

How it works

Example 1Example 2Example 3PatternOutput

When to use Few-shot?

Formatting Tasks

Transform data into specific formats by showing examples of desired output.

Style Matching

Replicate a particular writing style, tone, or voice consistently.

Pattern Recognition

Classify or categorize items based on demonstrated patterns.

Code Generation

Generate code following specific conventions shown in examples.

See the Difference

Before
Basic Prompt
Convert product descriptions to bullet points
After
Enhanced with Strategy
Convert product descriptions to bullet points following this format:

Example 1:
Input: "This comfortable cotton t-shirt is perfect for everyday wear. Features a classic crew neck and comes in 5 colors."
Output:
• Material: 100% cotton
• Style: Classic crew neck
• Use: Everyday wear
• Colors: 5 options available

Example 2:
Input: "Premium leather wallet with RFID protection, multiple card slots, and coin compartment. Dimensions: 4.5 x 3.5 inches."
Output:
• Material: Premium leather
• Feature: RFID protection
• Storage: Multiple card slots, coin compartment
• Size: 4.5 x 3.5 inches

Now convert this:
"Wireless noise-cancelling headphones with 30-hour battery life, comfortable over-ear design, and included carrying case."

Example Prompts

Customer Service ResponsesSupport
Respond to customer inquiries using this template:

Example 1:
Customer: "Where is my order?"
Response: "Thank you for reaching out! I've checked your order #12345, and it's currently in transit. Expected delivery is May 15th. You'll receive a tracking link via email shortly. Is there anything else I can help with?"

Example 2:
Customer: "Can I return this item?"
Response: "Absolutely! We accept returns within 30 days of purchase. Please visit our returns portal at returns.com and use order #12345. You'll receive a prepaid shipping label. Let me know if you need any assistance!"

Now respond to:
Customer: "Do you ship internationally?"

Try it Yourself

Pro Tips

  • Use 2-3 examples - more than that rarely improves results
  • Make sure your examples are diverse but follow the same pattern
  • Keep examples consistent in format and structure
  • Choose examples that cover edge cases or variations

Common Mistakes to Avoid

  • Providing inconsistent examples that confuse the pattern
  • Using too many examples (diminishing returns after 3-4)
  • Choosing examples that are too similar to each other

When NOT to Use

Skip few-shot when the task is simple enough for zero-shot, or when you can't provide good representative examples. Also avoid if examples would take up too much token space.

🔗

Chain-of-Thought

Intermediate

"Think step by step"

What is Chain-of-Thought?

Chain-of-Thought (CoT) prompting encourages the AI to break down complex problems into logical steps and show its reasoning process. Instead of jumping to an answer, the AI "thinks out loud" through each step, leading to more accurate and explainable results.

How it works

ProblemStep 1Step 2Step 3Solution

When to use Chain-of-Thought?

Math & Logic

Solve mathematical problems or logical puzzles requiring multi-step reasoning.

Analysis Tasks

Analyze complex situations that require breaking down into components.

Decision Making

Evaluate options and make informed decisions with clear reasoning.

Debugging

Trace through code or processes to identify and fix issues.

See the Difference

Before
Basic Prompt
Calculate 15% tip on $47.50
After
Enhanced with Strategy
Calculate 15% tip on $47.50. Let's think step by step:

1. First, convert the percentage to decimal
2. Multiply the bill amount by the decimal
3. Round to 2 decimal places
4. Show the total with tip included

Please show your work for each step.
Expected Results
Basic Response:

The tip is $7.13

Enhanced Response:

Step 1: 15% = 0.15\nStep 2: $47.50 × 0.15 = $7.125\nStep 3: Rounded to $7.13\nStep 4: Total = $47.50 + $7.13 = $54.63\n\nThe tip is $7.13 and your total is $54.63

Example Prompts

Problem SolvingLogic
A train leaves Station A at 2:00 PM traveling at 60 mph. Another train leaves Station B (180 miles away) at 2:30 PM traveling at 80 mph toward Station A.

Let's solve this step by step:
1. Calculate how far the first train travels before the second starts
2. Determine the combined speed of both trains approaching each other
3. Calculate the remaining distance to cover
4. Find the time until they meet
5. Determine the exact meeting time

Please show all calculations clearly.

Try it Yourself

Pro Tips

  • Use phrases like 'Let\'s think step by step' or 'Let\'s break this down'
  • Ask the AI to explain its reasoning at each stage
  • Request numbered steps for clarity
  • Encourage showing calculations or intermediate results

Common Mistakes to Avoid

  • Skipping the step-by-step instruction - AI might still jump to conclusion
  • Not allowing enough space for reasoning (token limits)
  • Using CoT for simple tasks that don't need it

When NOT to Use

Avoid for simple, straightforward tasks where step-by-step reasoning adds unnecessary complexity. Also skip if you need very quick, concise responses.

🎯

ReAct

Advanced

"Think, then act"

What is ReAct?

ReAct (Reasoning + Acting) combines reasoning traces with task-specific actions. The AI alternates between thinking about what to do (Thought), taking an action (Action), and observing the result (Observation). This creates a feedback loop that allows for adaptive problem-solving.

How it works

ThoughtActionObservationRepeat

When to use ReAct?

Research Tasks

Gather information through multiple steps with intermediate decisions.

Iterative Problem Solving

Tackle problems that require trying different approaches and learning.

Planning & Strategy

Develop plans that adapt based on intermediate outcomes.

Complex Workflows

Execute multi-step processes with decision points along the way.

See the Difference

Before
Basic Prompt
Find information about electric cars and their environmental impact
After
Enhanced with Strategy
Research electric cars and their environmental impact using the Thought-Action-Observation framework:

Thought: I need to understand both the benefits and drawbacks of electric cars environmentally.
Action: List key environmental factors to research (battery production, energy sources, lifetime emissions).
Observation: [What did we learn from this step?]

Thought: Now I need to compare these factors to traditional vehicles.
Action: Identify comparison points.
Observation: [What insights did we gain?]

Continue this pattern to build a comprehensive understanding.

Example Prompts

Market ResearchBusiness
Analyze the market opportunity for a new fitness app using ReAct:

Thought: I need to understand the current market size and trends.
Action: Identify key market metrics to analyze.
Observation: [Record findings]

Thought: Now I should analyze the competition.
Action: List main competitors and their strengths/weaknesses.
Observation: [Record findings]

Thought: Based on the above, where are the gaps?
Action: Identify underserved segments or unmet needs.
Observation: [Record findings]

Thought: Finally, what's the recommended strategy?
Action: Synthesize findings into actionable recommendations.

Try it Yourself

Pro Tips

  • Explicitly structure prompts with 'Thought', 'Action', 'Observation' labels
  • Allow the AI to iterate and adjust based on observations
  • Use this for tasks that benefit from adaptive decision-making
  • Encourage the AI to learn from each observation

Common Mistakes to Avoid

  • Not clearly separating thought from action
  • Skipping the observation step - loses the feedback loop
  • Using for simple linear tasks that don't need iteration

When NOT to Use

Avoid for straightforward tasks without decision points, or when you need a single direct answer without intermediate steps.

🔄

Reflexion

Advanced

"Learn from mistakes"

What is Reflexion?

Reflexion adds a self-evaluation and improvement layer to problem-solving. The AI tries an approach, evaluates its own output, reflects on what could be better, and then refines the solution. It's like having built-in quality control and continuous improvement.

How it works

TryEvaluateReflectImproveRetry with improvements

When to use Reflexion?

Quality Improvement

Refine outputs iteratively until they meet high-quality standards.

Error Correction

Identify and fix mistakes or issues through self-evaluation.

Content Editing

Polish writing, code, or creative work through multiple refinement cycles.

Strategy Refinement

Develop and improve strategies based on evaluation feedback.

See the Difference

Before
Basic Prompt
Write a compelling product description
After
Enhanced with Strategy
Write a compelling product description, then refine it:

Step 1 - Initial Draft:
Write the first version of the product description.

Step 2 - Self-Evaluate:
Analyze the draft for:
- Clarity of benefits
- Emotional appeal
- Call to action strength
- Readability

Step 3 - Reflect:
Identify specific weaknesses and opportunities for improvement.

Step 4 - Refine:
Rewrite the description addressing the identified issues.

Step 5 - Final Check:
Confirm all improvements have been made.

Example Prompts

Email ImprovementCommunication
Compose and refine a sales email using Reflexion:

1. DRAFT: Write initial sales email for our new software product.

2. EVALUATE: Score the draft on:
   - Subject line effectiveness (1-10)
   - Opening hook strength (1-10)
   - Value proposition clarity (1-10)
   - Call to action power (1-10)

3. REFLECT: For any score below 8, explain what's missing or weak.

4. REFINE: Rewrite the email addressing each weakness.

5. VERIFY: Confirm all scores are now 8+ or explain remaining tradeoffs.

Try it Yourself

Pro Tips

  • Build in explicit evaluation criteria
  • Ask for specific scores or assessments
  • Request the AI explain what to improve and why
  • Allow multiple refinement cycles for best results

Common Mistakes to Avoid

  • Not providing clear evaluation criteria - leads to vague feedback
  • Stopping after first evaluation without refinement
  • Using for tasks where the first output is usually good enough

When NOT to Use

Skip Reflexion for time-sensitive tasks requiring quick responses, or simple tasks where quality is already high in first attempt.

🌳

Tree of Thoughts

Advanced

"Explore multiple paths"

What is Tree of Thoughts?

Tree of Thoughts (ToT) explores multiple reasoning paths simultaneously, like branches on a tree. Instead of following one line of thinking, the AI generates several different approaches, evaluates each one, and then selects or combines the best elements. It's perfect for complex problems with multiple viable solutions.

How it works

ProblemPath APath BPath CBest Solution

When to use Tree of Thoughts?

Creative Brainstorming

Generate and evaluate multiple creative ideas before selecting the best.

Strategic Planning

Explore different strategies and compare their potential outcomes.

Architecture Design

Consider multiple design approaches before committing to one.

Decision Analysis

Evaluate pros and cons of different options systematically.

See the Difference

Before
Basic Prompt
Design a customer retention strategy
After
Enhanced with Strategy
Design a customer retention strategy by exploring multiple approaches:

Step 1 - Generate 3 Different Approaches:
Path A: Loyalty rewards program approach
Path B: Personalization and engagement approach
Path C: Community building approach

Step 2 - Develop Each Path:
For each approach, outline:
- Key features
- Implementation requirements
- Expected costs
- Potential ROI

Step 3 - Evaluate Each Path:
Score each on:
- Ease of implementation (1-10)
- Cost effectiveness (1-10)
- Customer impact (1-10)
- Scalability (1-10)

Step 4 - Select or Combine:
Choose the best approach or combine strengths from multiple paths.

Example Prompts

Product Feature PlanningProduct
Explore different approaches for our app's next major feature:

Branch 1: AI-Powered Recommendations
- Core functionality
- Technical requirements
- User benefits
- Development timeline

Branch 2: Social Collaboration Features
- Core functionality
- Technical requirements
- User benefits
- Development timeline

Branch 3: Advanced Analytics Dashboard
- Core functionality
- Technical requirements
- User benefits
- Development timeline

Evaluation Matrix:
Compare all three on: User demand, Development effort, Revenue potential, Strategic fit

Recommendation:
Based on the evaluation, which path should we pursue? Or should we combine elements?

Try it Yourself

Pro Tips

  • Generate 3-5 distinct approaches, not minor variations
  • Use consistent evaluation criteria across all paths
  • Consider combining strengths from multiple approaches
  • Be explicit about what makes each path unique

Common Mistakes to Avoid

  • Creating paths that are too similar to each other
  • Not fully developing each path before evaluation
  • Bias toward the first generated path

When NOT to Use

Avoid for simple problems with obvious solutions, or when you need quick decisions without exploring alternatives. Also skip if token limits prevent exploring multiple paths fully.

🎭

Meta Prompting

Intermediate

"Assign the perfect role"

What is Meta Prompting?

Meta prompting assigns the AI a specific expert role or persona tailored to your task. By defining who the AI should "be" (e.g., a marketing strategist, senior developer, or financial advisor), you help it access the most relevant knowledge and adopt the appropriate perspective and communication style.

How it works

RoleTaskFormatOutput

When to use Meta Prompting?

Domain Expertise

Access specialized knowledge by assigning expert roles in specific fields.

Specific Output Formats

Get results in professional formats by defining the role and standards.

Tone & Style

Match a specific writing style or communication approach through role-play.

Perspective Shifts

View problems from different professional angles by changing roles.

See the Difference

Before
Basic Prompt
Help me improve my website's conversion rate
After
Enhanced with Strategy
You are a senior conversion rate optimization (CRO) specialist with 10+ years of experience in e-commerce. You've helped over 100 companies increase their conversion rates by an average of 40%.

Your approach:
- Data-driven analysis
- Evidence-based recommendations
- Clear prioritization of changes by impact
- Specific, actionable next steps

Task: Analyze my website and provide a CRO improvement plan.

Input Format: I'll describe my website and current metrics
Output Format:
1. Executive Summary
2. Key Issues (prioritized)
3. Recommended Changes (with expected impact)
4. Implementation Roadmap

Please analyze in your expert capacity.

Example Prompts

Code ReviewDevelopment
You are a Staff Software Engineer at a FAANG company, specializing in Python and system design. You have:
- 15+ years of experience
- Led architecture reviews for high-scale systems
- Mentored 50+ junior developers
- Strong focus on performance, security, and maintainability

Your code review approach:
1. Correctness and logic
2. Security vulnerabilities
3. Performance implications
4. Code maintainability
5. Best practices adherence

Review Style: Constructive, specific, with examples

Please review this Python code: [code here]

Provide feedback in this format:
- Critical Issues (must fix)
- Improvements (should fix)
- Suggestions (nice to have)
- What's done well
Marketing StrategyMarketing
You are a Chief Marketing Officer with expertise in SaaS B2B marketing. Your background:
- Built marketing teams at 3 successful startups
- Expert in growth marketing, content strategy, and demand generation
- Data-driven approach with focus on CAC, LTV, and conversion metrics

Your framework:
1. Understand business goals and current metrics
2. Identify target audience and positioning
3. Recommend multi-channel strategy
4. Define success metrics and timeline
5. Provide implementation roadmap

Task: Develop a go-to-market strategy for our new product.

Please provide strategy in format:
- Situation Analysis
- Strategy Recommendations
- Channel Plan
- Budget Allocation
- Success Metrics
- 90-Day Action Plan

Try it Yourself

Pro Tips

  • Be specific about the role - include experience level and specialties
  • Define the expert's approach or framework
  • Specify desired output format and structure
  • Include relevant context about the expert's background

Common Mistakes to Avoid

  • Vague roles like 'expert' without specifics
  • Not defining what makes this expert qualified
  • Skipping output format specifications

When NOT to Use

Skip meta prompting for general tasks that don't benefit from specialized expertise, or when you want a neutral, objective perspective without role bias.