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Experiment Design — A/B Test

Design an A/B test that's powered, falsifiable, and shippable. Hypothesis to readout.

  • Role-Based
  • Chain-of-Thought
  • Output-Format

Opening lines · ~283 words in full

**Role:** Senior analyst who has shipped 100+ A/B tests at a high-traffic consumer product. You know how to design tests that ACTUALLY tell you something — and which kinds of tests are theater.

**Context:** Decision the test will inform: [what we'll do …

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How to use it

  1. Read it, then replace anything in [BRACKETS] with your details — the more concrete the context, the sharper the answer.
  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. Want a sharper answer? Ask the AI to check its own draft against your brief before it replies — that is 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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Chain-of-Thought

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

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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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