Prompt

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Product Spec — Shippable v0.1

Write a spec that fits on one page and ships in one sprint.

  • Role-Based
  • Constraints
  • Output-Format
Download .mdOpen in Studio~228 words
**Role:** Senior PM who has shipped 40+ features. You've learned that 10-page specs become wallpaper while one-pagers ship.

**Context:** Feature: [name + 1-sentence purpose]. The user problem (in user's words): [the verbatim complaint or job-to-be-done]. The success metric: [the ONE number we'll measure]. Team capacity: [people-weeks available]. Hard deadline (if any): [date + why].

**Task:** Write the spec.

1. TL;DR (3 sentences): user problem + what we're shipping + how we'll know it worked.
2. User story: "As a [persona], I want [outcome], so that [reason]." Specific. Not "users want X."
3. Scope: what's IN (3-5 bullets), what's OUT (2-3 explicit bullets). Out-of-scope is a feature.
4. Success metric: ONE primary metric + how it's measured + the lift we'd need for the feature to "win."
5. Solution sketch: 3-5 bullets on the approach. Reference designs/Figma if they exist. NOT a feature list — the user journey.
6. Edge cases: 3-5 specific scenarios we need to handle. Include the empty state and the failure case.
7. Risks: 2-3 things that could go sideways + mitigation.

**Constraints:**
- ≤1 page (~500 words)
- ONE success metric — never tie-break later
- Out-of-scope is required, not optional
- Edge cases include empty state + failure case minimum
- No "we'll figure it out in build" placeholders

**Output format:** 7 sections · ≤500 words · ready for 30-min spec review meeting.

How to use it

  1. Read it, then replace anything in [BRACKETS] with your details — the more concrete the context, the sharper the answer. The Studio lists the blanks for you and can add your project's background.
  2. Copy it (or download the .md) and paste it into the AI you already use — it knows your work, so that is where the prompt does the most.
  3. Not sure what it produces? Give it a test run in the Studio first, then refine 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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Constraints

Sets the rules and boundaries — tone, length, what to avoid — that keep the output on-target.

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Output-Format

Specifies the exact shape of the result — sections, a table, JSON, a word count — so the output is predictable and ready to use.

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Works with

Any chat AI — ChatGPT, Claude, Gemini, Copilot, Grok, Mistral or a local model. The structure does the work, so you are not tied to one vendor or one model version.

New to structured prompts? Start with how to prompt AI, the RCTCO prompt framework this prompt is built on, and role prompting examples.

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