Prompt Engineering: 7 Core Concepts Explained

Prompt engineering is the foundational skill for "using AI well." This article explains 7 core concepts in plain language, each with a reusable template.

1. Role
Have AI act as a specific identity to activate relevant knowledge domains.
Template: "You are a [senior lawyer/fitness coach/marketing director], please..."

2. Context
Tell AI the background so answers are accurate.
Template: "My situation is [background], my goal is [goal], and my constraints are [limitations]."

3. Few-shot
Give 1-3 input-output examples and AI will imitate the format.
Template: "Example 1: [Input] → [Output]. Now please process: [Input]"

4. Chain-of-Thought
Ask AI to reason step by step — complex problem accuracy improves dramatically.
Template: "Please reason step by step: 1) List conditions 2) Calculate progressively 3) Check results"

5. Output Format
Explicitly request JSON/tables/lists for directly usable results.
Template: "Please output in JSON with fields including [field list]"

6. Constraints
Limit scope, word count, and tone to prevent drifting.
Template: "Within 200 words, conversational tone, no technical jargon"

7. Iteration
If the first result isn't satisfactory, add conditions and follow up — don't start over.
Template: "Based on the previous version, [new requirement], output again"

Combine these 7 concepts and your prompt quality will jump to a new level. This site's prompt library provides many ready-to-use templates.