C-A-R-E
Structure your AI prompts in 4 blocks: Context, Action, Expected Result, Example. Get precise answers on the first try.
Description
C-A-R-E structures your AI prompts into four blocks: Context (who you are, what situation you are in), Action (what you are asking for), Result (the expected format and level of detail), and Example (a concrete reference to calibrate the response). By filling in these four blocks before each request, you get responses aligned with your needs on the first try, with fewer iterations. This framework suits all use cases: writing specs, analyzing feedback, generating content, summarizing meetings. It requires no technical skills.
Objectives
- Improve team collaboration
- Structure AI prompts
How to apply C-A-R-E
- 1
Define the Context
Describe your role, industry, and situation in 2 to 4 lines. The more precise the context, the fewer assumptions the model makes.
- 2
Formulate the Action
Express your request with a clear action verb: write, analyze, compare, list. Avoid vague formulations like "help me with".
- 3
Specify the expected Result
Indicate the desired format (list, table, email, report), the length, and the level of detail.
- 4
Provide an Example
Add an example of a good response or a counter-example to avoid. This reference calibrates the model to your quality standard.
- 5
Assemble and test the prompt
Combine the four blocks into a single structured message and send it.
- 6
Iterate and capitalize
If the response is not satisfactory, identify the insufficient block and refine it. Save effective prompts for the team.