10 Prompt Engineering Techniques Most People Don't Know

Most people use AI the same way they use a search engine: type a question, get an answer, move on. But that approach leaves 90% of AI's potential on the table.

The difference between a basic prompt and an expertly crafted one can mean the difference between a generic, unhelpful response and an answer that perfectly solves your problem. After working with thousands of prompts, we've identified 10 techniques that separate AI power users from everyone else.

Here are 10 prompt engineering techniques that will transform how you interact with AI.

1. Chain-of-Thought Prompting

This simple technique dramatically improves AI reasoning on complex problems. Instead of asking for a direct answer, you ask the AI to think through the problem step by step.

Before (Basic Prompt)

What's 17 x 24?

After (Chain-of-Thought)

What's 17 x 24? Let's work through this step by step.

The magic phrase "Let's think step by step" triggers the AI to break down its reasoning process. This is especially powerful for:

• Math problems
• Logic puzzles
• Complex analysis
• Decision-making scenarios

Why it works: AI models process tokens sequentially. When you force explicit reasoning steps, the model can build on each step rather than trying to jump to conclusions. Research shows this technique can improve accuracy on reasoning tasks by 40% or more.

Pro tip: You can make it even more explicit:

Solve this problem. Before giving your final answer, explain your
reasoning process in numbered steps.

2. Role Assignment

Assigning a specific role or persona to the AI dramatically changes the quality and style of responses. The AI draws on its training data about how that role would think and communicate.

Before (No Role)

Write an email asking for a raise.

After (Role Assignment)

You are an experienced HR consultant who has helped hundreds of
professionals negotiate salary increases. Write an email requesting
a raise that follows best practices for professional negotiation.

Powerful role combinations:

• "You are a senior software architect at Google..."
• "You are a patient, encouraging teacher explaining to a complete beginner..."
• "You are a skeptical scientist who questions assumptions..."
• "You are an experienced editor at The New York Times..."

Why it works: Role assignment provides context that shapes vocabulary, tone, depth of explanation, and the types of considerations the AI includes. A "doctor" will mention medical considerations a general response would miss.

Pro tip: Combine multiple expertise areas:

You are a startup founder with 10 years of experience who also
has a background in behavioral psychology. Explain why users
abandon shopping carts.

3. Few-Shot Examples

Instead of just describing what you want, show the AI with concrete examples. This technique, called few-shot learning, is one of the most powerful ways to get consistent, formatted outputs.

Before (Zero-Shot)

Convert these customer reviews into a positive/negative sentiment.

After (Few-Shot)

Classify the sentiment of customer reviews as Positive or Negative.

Example 1:
Review: "This product exceeded my expectations! Fast shipping too."
Sentiment: Positive

Example 2:
Review: "Broke after two days. Complete waste of money."
Sentiment: Negative

Example 3:
Review: "It's okay, nothing special but does the job."
Sentiment: Neutral

Now classify:
Review: "Absolutely love it, buying another one for my sister!"
Sentiment:

Why it works: Examples are worth a thousand words of instruction. They communicate format, tone, length, and edge cases implicitly. The AI pattern-matches from your examples.

Best practices:

• Use 2-5 diverse examples
• Include edge cases in your examples
• Make examples representative of the full range of inputs you expect

4. Negative Prompting

Sometimes the best way to get what you want is to specify what you don't want. Negative prompting sets boundaries and prevents common failure modes.

Before (Positive Only)

Explain quantum computing in simple terms.

After (With Negative Prompting)

Explain quantum computing in simple terms.

Do NOT:
- Use technical jargon or acronyms without explaining them
- Assume any prior physics knowledge
- Use analogies involving cats (too overused)
- Make it longer than 3 paragraphs

Common negatives to include:

• "Don't be vague or generic"
• "Don't include disclaimers or caveats"
• "Don't repeat information I already provided"
• "Don't use bullet points" (when you want prose)
• "Don't apologize or hedge"

Why it works: AI models have learned common response patterns that may not match your needs. Negative prompting overrides these defaults and narrows the output space to what you actually want.

5. Output Format Specification

AI can generate content in virtually any structured format—but only if you ask for it explicitly. Specifying output format eliminates the need for manual reformatting.

Request Specific Formats

JSON output:

Analyze this customer feedback and return a JSON object with the
following structure:
{
  "sentiment": "positive|negative|neutral",
  "main_topics": ["topic1", "topic2"],
  "action_items": ["action1", "action2"],
  "priority": 1-5
}

Markdown table:

Compare these 5 programming languages. Present your comparison as a
markdown table with columns for: Language, Best For, Learning Curve,
Job Market, and Key Strength.

Structured sections:

Write a product description with these exact sections:
## Headline (max 10 words)
## Key Benefits (3 bullet points)
## Technical Specs (table format)
## Call to Action (one sentence)

Why it works: Format specification removes ambiguity about what you expect. It also makes responses immediately usable—no copy-paste reformatting needed.

6. Temperature and Tone Control

While you can't directly set AI temperature through prompts (that's an API setting), you can control tone and creativity level through careful wording.

Control Creativity Level

For factual, consistent responses:

Give me the most accurate, widely-accepted answer. Stick to
established facts only.

For creative brainstorming:

Generate unconventional, creative ideas. Don't worry about being
practical—I want surprising, outside-the-box suggestions.

Control Tone

Formal:

Write in a formal, professional tone suitable for a board presentation.

Casual:

Write like you're texting a friend. Keep it casual and conversational.

Specific voice:

Write in a warm, encouraging tone like a supportive mentor giving
advice to someone just starting their career.

Why it works: Tone instructions tap into the AI's understanding of different communication styles from its training data. Being explicit prevents the AI from defaulting to its standard "helpful assistant" voice.

7. Iterative Refinement

Don't expect perfection on the first try. The best results come from building on previous outputs through conversation. Treat it as collaboration, not a one-shot query.

The Refinement Process

Step 1: Initial prompt

Write an introduction for a blog post about remote work productivity.

Step 2: Refine based on output

Good start, but make it more attention-grabbing. Start with a
surprising statistic or counterintuitive statement.

Step 3: Further refine

Better! Now make it shorter—cut it down to 2-3 sentences maximum.
Make every word count.

Step 4: Polish

Perfect length. Just change "remote workers" to "distributed teams"
for consistency with our brand voice.

Why it works: Iterative refinement lets you guide the AI toward your vision progressively. Each round gives you more information about what you want, and the AI can build on context from previous exchanges.

Pro tip: Save your best prompts. When you find a refinement pattern that works, incorporate it into your initial prompt next time.

8. Task Decomposition

Complex tasks often fail because they're too ambitious for a single prompt. Break large tasks into smaller, sequential steps that build on each other.

Before (Monolithic Task)

Write a complete marketing strategy for my new SaaS product.

After (Decomposed)

Let's create a marketing strategy step by step.

Step 1: First, help me identify my target audience. My product is a
project management tool for remote teams. What are the key customer
segments I should consider?

Then continue with:

Step 2: Based on the target audience we identified (remote startups
and distributed enterprise teams), what are the main pain points
each segment experiences?

Then:

Step 3: Now let's identify marketing channels. Given our audience
segments and their pain points, which 3-5 channels should we
prioritize and why?

Why it works: Decomposition keeps context focused, allows for course correction between steps, and produces higher-quality outputs because each step receives full attention. It also lets you review and approve before proceeding.

9. Self-Consistency Checking

For important decisions, ask the AI to approach the problem multiple ways and check if the answers converge. This reduces errors and reveals blind spots.

Example: Self-Consistency Prompt

I need to decide whether to build or buy a CRM system for my
50-person company.

Please analyze this decision from three different perspectives:

1. Financial perspective: Analyze costs over 3 years
2. Technical perspective: Consider integration, maintenance, and
   scalability
3. Strategic perspective: Think about competitive advantage and
   core competencies

After analyzing all three perspectives, note any contradictions
or tensions between them, then give your final recommendation.

Another Approach: Multiple Solutions

Generate three different solutions to this problem. For each solution,
explain the approach, list pros and cons, and rate it on feasibility
(1-10). Then explain which you'd recommend and why.

Why it works: Multiple perspectives reveal assumptions and trade-offs that a single analysis might miss. When different approaches reach the same conclusion, you can have higher confidence in the answer.

10. Meta-Prompting

The most advanced technique: using AI to improve your prompts. Meta-prompting leverages AI's understanding of effective communication to enhance your own prompts.

Generate Better Prompts

I want to use AI to help me write better product descriptions.
Here's my current prompt:

"Write a product description for [product]."

This prompt is too basic. Rewrite it as an expert prompt engineer
would, including specific instructions for format, tone, length,
and key elements to include.

Analyze and Improve

Here's a prompt I've been using:

[Your prompt]

Analyze this prompt and suggest 3 specific improvements that would
make it more effective. Explain why each improvement would help.

Create Prompt Templates

I frequently need to write prompts for [task type]. Create a
reusable prompt template I can fill in each time, with placeholders
for variable information and instructions for consistent results.

Why it works: AI has processed millions of examples of effective communication. It can identify what makes prompts clear, specific, and effective—and apply those patterns to improve your prompts.

Pro tip: Build a personal library of meta-improved prompts for tasks you do regularly.

Putting It All Together

These techniques compound. A well-crafted prompt might combine:

• Role assignment (who the AI is)
• Task decomposition (structured steps)
• Few-shot examples (showing the format)
• Negative prompting (what to avoid)
• Output format (how to structure the response)

Example: Combined Prompt

You are a senior content strategist with 15 years of experience
in B2B marketing.

I need you to analyze our latest blog post for SEO and engagement.
Here's how I want you to structure your analysis:

## SEO Analysis
- Keyword usage (list found and suggested)
- Title and meta description review
- Internal linking opportunities

## Engagement Analysis
- Hook effectiveness
- Readability score
- Call-to-action strength

## Recommendations
- Top 3 quick wins (can implement in <30 minutes)
- Top 3 strategic improvements (require more effort)

Format each recommendation as:
**Issue**: [What's wrong]
**Fix**: [How to fix it]
**Impact**: [High/Medium/Low]

Do NOT:
- Include generic advice that applies to any blog post
- Suggest changes that would require rewriting more than 20% of content
- Ignore the fact that our audience is technical decision-makers

Here's the blog post:
[paste post]

This single prompt incorporates six of the techniques we covered, resulting in a focused, actionable, and consistently formatted analysis.

Next Steps

These 10 techniques are just the beginning. Prompt engineering is a skill that improves with practice, and the best way to learn is by doing.

If you want to master these techniques with hands-on exercises and real-world projects, check out our comprehensive Prompt Engineering course. You'll learn:

• Advanced prompting strategies for different use cases
• How to build reusable prompt templates
• Techniques for specific applications (coding, writing, analysis)
• Common pitfalls and how to avoid them

For a broader introduction to using AI effectively in your daily life, our AI in Everyday Life course covers practical applications from productivity to creative projects.

The AI revolution isn't about having access to AI—everyone has that now. It's about knowing how to use it effectively. These 10 techniques are your first step toward becoming an AI power user.

Start experimenting with these techniques today. Pick one technique and apply it to your next AI interaction. Notice the difference. Then add another technique, and another. Before long, you'll be getting results that seem like magic to everyone else.

Ready to level up your prompting skills? Start with our free Prompt Engineering course today.