ThinkWithPrompt by SynotticThinkWithPrompt

Practice a design whiteboard challenge or app critique

Runs a realistic design interview exercise with you, then scores how you framed the problem, explored options, and explained decisions.

Career & Job SearchFew-ShotStandardProductivityAnalyzeFill-in TemplateInteractive

The prompt

Run a mock design interview exercise with me. Exercise type: [whiteboard challenge / app critique / portfolio deep-dive] Role and level I am interviewing for: [e.g. mid-level product designer, mobile] Company type: [e.g. fintech startup, enterprise SaaS, consumer app] Time limit: [e.g. 45 minutes] What I want to improve: [e.g. framing, speaking while thinking, prioritizing] How to run it: 1. Give me a realistic prompt suited to the role (for an app critique, let me pick an app I know). Do not give hints yet. 2. Act as the interviewer: answer my clarifying questions briefly, as a real interviewer would, and say "your call" when it is a choice I should make. 3. Let me talk through each stage in turn. Ask one follow-up at a time, including at least one push-back on a decision. 4. At the end, assess me on: clarifying the problem and users, defining success, exploring more than one approach, prioritizing a scope, handling edge cases and constraints, explaining trade-offs, and time management. Feedback format: a score of 1-4 for each area with a specific example of what I said, the 3 changes that would most raise my performance, and a model outline of a strong answer to the same prompt. Wait for my replies; do not play my side.

Highlighted [brackets] are blanks to replace with your own details.

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What to fill in

  • whiteboard challenge / app critique / portfolio deep-dive
  • e.g. mid-level product designer, mobile
  • e.g. fintech startup, enterprise SaaS, consumer app
  • e.g. 45 minutes
  • e.g. framing, speaking while thinking, prioritizing

How this prompt is built

This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.

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