Prompt Evolution: CARE (Context – Action – Result – Example)

AI CARE structure examples guide context prompt design

📌 PROMPT EVOLUTION: Exploring AI Frameworks
🎯 Today’s focus — CARE (Context – Action – Result – Example)

🔹 What is CARE and why use it?

The CARE framework helps improve prompt clarity and precision by adding context, action, desired output format, and an example.
It’s especially effective for instructional, educational, or explanatory prompts.

📌 How does it work?

1️⃣ Context → What is the topic? What background info matters?
2️⃣ Action → What exactly should AI do?
3️⃣ Result → What kind of output is expected? (format, structure)
4️⃣ Example → (optional) a model or reference for AI to follow

🔍 Example (before):

Explain how SQL works.

💡 The problem:

❌ Too vague
❌ No audience specified
❌ No structure — AI chooses whatever format it wants

🔥 Improved version with CARE

✅ Updated prompt:

Explain the basics of SQL for beginner programmers.
Use examples with simple queries and clear table structures.
Format the answer as a list with brief explanations.
Sample structure:
1️⃣ What is SQL?
2️⃣ How to create tables? (Example: CREATE TABLE)
3️⃣ How to use SELECT queries? (Example)

📌 What’s better now?

✔ Context → AI knows the audience is beginners
✔ Result format → a list with practical explanations
✔ Example structure → AI understands what the output should look like

💡 Bottom line:

Old prompt → Random, unstructured response
CARE prompt → Clear, structured, and highly usable explanation

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