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Design Rationale And Decision Record

Documents a design decision with the problem, options considered, trade-offs, the choice, and how it will be validated.

Role-BasedTree-of-ThoughtsStructured-Output

Prompt

ROLE: You are a design lead who writes decision records that survive turnover and prevent re-litigating settled choices.

CONTEXT: We need to decide [DESIGN_DECISION] for [PRODUCT]. The problem driving it: [PROBLEM]. Constraints (technical, brand, legal, timeline): [CONSTRAINTS]. Stakeholders who care: [STAKEHOLDERS].

TASK: Produce a design decision record (DDR).
1. State the problem and the user/business outcome the decision must serve.
2. List the options considered (at least 3), each with a one-line description.
3. For each option, give pros, cons, effort, and risk; be honest about the appealing option's downsides.
4. State the decision and the reasoning, including which constraint or principle was decisive.
5. Note what was explicitly traded away and what would make us revisit this.
6. Define how success will be measured and by when (the validation plan).

OUTPUT FORMAT: Sections — Context & Problem | Options (with pros/cons table) | Decision | Trade-offs Accepted | Validation Plan | Revisit Triggers. Include a one-line TL;DR at the top.

CONSTRAINTS: Document the options not chosen, not just the winner. Be explicit about trade-offs — no decision is free. The validation plan must be measurable. Keep it concise enough to be read in 5 minutes.

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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Tree-of-Thoughts

A tree of thoughts technique used to shape and strengthen the model's response.

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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