Context, Action, Result, Example — A result-oriented structure that keeps the AI focused on the outcome you actually need.
CARE is useful whenever the deliverable matters more than the process — reports, summaries, business writing, and any task where you want the AI to work backward from a defined result instead of just following instructions step by step.
The situation the AI is operating in — what's happening and why this task exists.
What you need the AI to do to move from the current situation toward the result.
The specific outcome that defines a successful answer — what "done" looks like.
A model of the format, tone, or level of detail the result should have.
Bad prompt:
“Summarize this quarter's sales data.”
Structured with CARE:
Context: Our Q3 sales data shows growth in two regions and a decline in one, and leadership has 10 minutes before a board meeting. Action: Summarize the data into the key takeaways leadership needs to know. Result: A summary that lets a non-analyst understand what changed and why, without needing to read the underlying spreadsheet. Example: Similar structure to a three-bullet executive summary — headline number, driver, one recommended action.
A short executive summary with a headline figure, the main driver behind the regional decline, and one recommended next step — formatted for someone reading it in the elevator before a meeting, not an analyst.
CARE is a strong fit for both ChatGPT and Claude when the task is business or analytical writing, since naming the Result up front keeps longer-context models from wandering into unnecessary detail.