How to Write AI Prompts That Actually Work
Master the skill of communicating with AI. Learn our proven PCRF framework, see real examples, and start getting better results from ChatGPT, Claude, and Gemini.
Last updated: January 19, 2026
What is an AI prompt?
An AI prompt is a text instruction you give to an AI system like ChatGPT, Claude, or Gemini that tells it what you want it to do. The quality of your prompt directly determines the quality of the AI's response. Effective prompts are specific, provide context, and clearly define the expected output format.
The PCRF Framework for Better Prompts
After analyzing thousands of prompts, we developed the PCRF framework—a simple structure that dramatically improves AI outputs. Every effective prompt includes these four elements:
PCRF: The 4 Elements of Effective Prompts
Not every prompt needs all four elements—simple tasks can work with just Request and Format. But complex tasks benefit significantly from the full framework.
Example 1: Content Creation
Let's see the PCRF framework in action. Compare these two prompts for writing a blog post:
The weak prompt is vague and will produce generic content. The strong prompt specifies the persona (B2B marketing strategist), context (SaaS companies), request (500-word blog post with 3 tactics), and format (headers and bullet points).
12 Tips for Writing Better AI Prompts
These techniques work across ChatGPT, Claude, Gemini, and other AI platforms. Bookmark this list and reference it when crafting prompts.
Be Specific, Not Vague
Replace "Write something about marketing" with "Write a 500-word guide to email subject lines for B2B software companies." Specificity eliminates ambiguity.
Assign a Relevant Role
Start with "You are an experienced [role]..." This primes the AI to respond from that perspective, improving accuracy and relevance.
Provide Context
Include background information: who is the audience, what is the situation, what constraints exist. The more context, the better the output.
Specify Output Format
Tell the AI exactly how to structure the response: "Format as a numbered list," "Use headers and bullet points," "Write as a table with columns for X, Y, Z."
Set Length Constraints
Be explicit about length: "in 100 words," "in 3 paragraphs," "as a one-page summary." Without constraints, AI often over-produces.
Give Examples
Show the AI what good output looks like. "Here's an example of the tone I want: [example]." This technique (few-shot prompting) dramatically improves consistency.
Ask for Multiple Options
Instead of "Write a headline," try "Write 10 headline options." This gives you choices and reveals the AI's range of ideas.
Use "Step by Step"
For complex reasoning, add "Think through this step by step." This chain-of-thought technique improves accuracy on analytical tasks.
Specify What to Avoid
Include negative instructions: "Do not use jargon," "Avoid clichés like 'game-changer,'" "Don't include a conclusion section."
Define the Tone
Be explicit about voice: "professional but conversational," "formal and authoritative," "friendly and approachable." Tone shapes the entire output.
Break Complex Tasks into Steps
Instead of one massive prompt, use sequential prompts: first outline, then expand each section. This maintains quality throughout.
Iterate and Refine
Your first prompt rarely produces perfect output. Review, identify what's missing, and refine. Prompt engineering is an iterative process.
Example 2: Email Writing
Emails are one of the most common AI use cases. Here's how specificity transforms results:
The strong prompt includes context about the recipient, the situation, their specific interests, and the desired tone. This level of detail produces emails that feel personalized rather than generic.
Common Prompting Mistakes to Avoid
- Vague requests without specifics
- Missing context or background
- No format specification
- Asking for too much at once
- Accepting first output without iteration
- Using AI jargon the model doesn't need
- Be specific about what you want
- Provide all relevant background
- Specify exact output format
- Break complex tasks into steps
- Refine prompts based on output
- Write naturally, as if to a colleague
Example 3: Document Summarization
Summarizing long documents is another common use case. Compare these approaches:
The strong prompt specifies the audience (CEO), what to focus on (four specific areas), the format (one-page brief with bullets), and the style (plain language). This produces an immediately useful summary rather than a generic overview.
The Key Insight: Practice Beats Theory
Reading about prompting is not the same as doing it. Like any skill, prompt engineering improves through practice and feedback. Research shows that employees with formal training achieve 2.7x higher proficiency than self-taught users.
The most effective way to improve is through structured practice where you:
- Write prompts for real work tasks (not hypothetical exercises)
- Receive feedback on what could be improved
- Iterate based on that feedback
- Build a library of prompts that work for your role
Frequently Asked Questions
Master Prompt Engineering with Hands-On Practice
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