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Feature Flag And Safe Rollout Designer

Designs a feature behind a flag with progressive rollout, kill switch, and clean flag retirement plan.

Role-BasedStep-by-StepStructured-Output

Prompt

ROLE: You are an engineer who ships risky changes safely behind feature flags with measured rollouts.

CONTEXT:
- Feature: [WHAT_IS_CHANGING and its risk]
- Blast radius: [WHO/WHAT_IS_AFFECTED_IF_IT_GOES_WRONG]
- Flagging system: [LAUNCHDARKLY / HOMEGROWN / CONFIG]
- Success & guardrail metrics: [WHAT_DEFINES_GOOD_AND_BAD]

TASK:
1. Define the flag: name, type (boolean/multivariate), default state, and where it is evaluated.
2. Design the code structure so the flag check is clean and removable — no scattered conditionals; isolate old vs. new paths.
3. Plan the progressive rollout: internal -> small % -> ramp, with the metrics watched at each gate and the abort criteria.
4. Specify the kill switch behavior and what happens to in-flight work when the flag flips.
5. Plan flag retirement: when and how to remove the dead code path so the flag does not become permanent debt.

OUTPUT FORMAT:
## Flag Definition
## Code Structure (how the branch is isolated; short snippet)
## Rollout Plan (table: stage | audience | watch metrics | abort if)
## Kill Switch Behavior
## Retirement Plan

CONSTRAINTS:
- The flag must be safely toggleable at runtime with a well-defined default if the flag service is unreachable.
- Avoid flag spaghetti — both code paths must be clearly separated and the flag removable in one change.
- Define explicit abort/rollback criteria tied to guardrail metrics, not gut feel.
- Include a concrete plan to delete the flag; an un-retired flag is a defect.

How to use this prompt

  1. 1

    Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.

  2. 2

    Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.

  3. 3

    Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.

Techniques in this prompt

Role-Based

Assigns the model an expert persona so it adopts the right vocabulary, depth, and standards for the task.

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Step-by-Step

Forces explicit intermediate reasoning instead of jumping to a conclusion, which improves accuracy on hard tasks.

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Structured Output

Pins the response to a defined structure so it drops straight into your workflow.

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Open it in the visual Studio to wire it into a full workflow with your own API key — or learn the craft behind prompts like this.

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