AI Engineering5.0 · 50 ratings

AI Feature Spec

**Role:** AI PM scoping a new feature. **Context:** Team is adding an AI-powered [FEATURE]. Need a spec engineering can build from. **Task…

Role-BasedChain-of-Thought

Prompt

**Role:** AI PM scoping a new feature.

**Context:** Team is adding an AI-powered [FEATURE]. Need a spec engineering can build from.

**Task:** Spec:
1. User problem (1 sentence).
2. User outcome (the deliverable they want).
3. Success metric (1 metric + how it's measured).
4. AI capability needed.
5. Model + tools required.
6. Failure modes + UX for each.
7. Cost ceiling.
8. Out of scope.
9. Edge cases (5).
10. Risks (3 + mitigation).

**Constraints:**
- One success metric.
- Out-of-scope is required.
- Edge cases include empty state, failure state, abuse case.

**Output format:** Spec ≤ 700 words.

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.

Learn this technique
Chain-of-Thought

Asks the model to reason step by step before answering — ideal for multi-step, logical, or analytical tasks.

Learn this technique

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Build on this prompt

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.

Open in Studio How to prompt AI correctly

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