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AI agent for product designers

Product Specification Example Agent

Specifications whose rules are tested by concrete examples.

Quality controlCreatingProduct developmentIT and development
See how it worksGet access
Product Specification Example Agent: what goes in, what the agent does and what you get

What it does

Product specifications hide ambiguities that only show up during building. When a spec draft is ready, this agent generates concrete examples, starting with boundary cases such as exact thresholds, empty values and limits, then normal cases. It runs each example against the explicit rules in the spec. If an example rests on an invalid assumption, it revises the example. If rules give conflicting or unclear outcomes, it writes a precise question for the stakeholder. It keeps a versioned set of examples that becomes part of the spec. The product designer approves spec changes, and the agent never invents business rules. Edge case: two rules give different discounts for an order exactly at the threshold.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueApprovedNo 1 STARTS WHEN Spec draft ready 2 DOES Generate boundary examples 3 USES A TOOL Execute explicit rules 4 CHECKS THE RESULT Do rules give one clear outcome for each example? If not: write a precise stakeholder question. Back tostep 3. 5 DOES Version the example suite 6 YOU APPROVE Product designer approves spec changes 7 RESULT Tested specification example pack
Read the steps as a list
  1. Spec draft ready
  2. Generate boundary examples
  3. Execute explicit rules
  4. Do rules give one clear outcome for each example?If not: write a precise stakeholder question. Back to step 3.
  5. Version the example suite
  6. Product designer approves spec changesThe agent waits here for your OK.
  7. Tested specification example pack

How it decides

It chooses examples most likely to expose ambiguity.

  • Test boundary cases first.
  • Every conflict becomes a precise question, never a guess.
  • Examples with invalid assumptions are revised before running.

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Example types to generate (boundary, normal, invalid input)
  • Number of examples per rule (default 3)
  • Who answers stakeholder questions
  • Where the example set is stored

What keeps you in control

It always asks you first

  • Unstated business rules
  • Spec changes

Hard limits

  • No business rule invention.

It stops when

  • Done: suite complete.

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensA loyalty discount spec is drafted on 13 January. The agent generates 24 examples. The rule check fails for an order of exactly $500: one rule gives 10% for orders 'over $500', another gives 10% for '$500 and above'. It asks the product owner which rule wins. The answer is '$500 and above'. The rerun passes all 24. The product designer approves the spec update.

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