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Prompt engineering examples

Here are practical examples of how to write prompts that get more reliable results from an AI. 1) Role + goal + constraints: “You are a customer-support agent. Draft a polite refund policy explanation for a customer who received the wrong item. Keep it under 120 words and avoid legal jargon.” 2) Step-by-step with fo

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  1. Prompt engineering examples (en-US)

    Here are practical examples of how to write prompts that get more reliable results from an AI. 1) Role + goal + constraints: “You are a customer-support agent. Draft a polite refund policy explanation for a customer who received the wrong item. Keep it under 120 words and avoid legal jargon.” 2) Step-by-step with format: “Create a study plan for learning Spanish in 4 weeks. Output as a table with columns: Week, Daily goal, Practice activity, Resources. Assume 30 minutes per day.” 3) Few-shot examples: “Classify the following emails as ‘Billing’, ‘Technical’, or ‘General’. Examples: ‘Invoice overdue’ → Billing; ‘App crashes on login’ → Technical. Now classify: ‘Need help resetting my password’.” 4) Ask for uncertainty + checks: “Summarize this article in 5 bullets. Then list 3 possible missing details or assumptions you made.” 5) Retrieval-style prompt: “Given these notes: [paste notes], answer: What are the key causes and effects described? If the notes don’t mention something, say ‘Not specified in the notes’.”

  2. Common prompt patterns you can reuse

    Use consistent patterns: - Specify the output format (bullets, JSON, table). - Add boundaries (length, tone, audience, what to avoid). - Provide context (background, definitions, data). - Include evaluation criteria (“prioritize accuracy over creativity”). - Request verification (“cite which sentence supports each claim” when sources are provided).

  3. FAQ

    Q1: What’s the fastest way to improve results? A: Add constraints (format, length, tone) and clarify the task goal. Q2: When should I use few-shot examples? A: When you need consistent classification, extraction, or style. Q3: How do I reduce hallucinations? A: Ask the model to state assumptions, and provide source text or data when possible.

FAQ

prompt engineering examples

Examples include role+goal+constraints prompts, step-by-step prompts with a required output format, few-shot classification prompts, and prompts that ask for uncertainty/assumptions and verification.

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