I Used Ai As A "requirements Interviewer" On A 17-page Spec And It Found ~400 Inconsistencies. Full Prompt Inside.

PM here. A few months ago I got handed a 17-page functional spec that "looked fine". Instead of asking AI to rewrite it, I tried the opposite: I told it to *interview me* — closed multiple-choice questions only — about every gap, contradiction and ambiguity it could find.

It generated hundreds of questions. I answered \~300 in one afternoon (just picking letters: "Q12: B", "Q13: A but admins only"). Then the AI rebuilt the document with every decision integrated. Result: 60 pages, and the dev team basically stopped asking clarification questions.

The insight: AI is mediocre at *deciding* for you, but really good at *detecting what hasn't been decided*. The multiple-choice format is what makes it practical — answering 300 open questions would take a week.

Here's the full prompt I use (works with Claude, ChatGPT, Copilot — whatever your company allows):

You are a senior functional analyst with 15 years of experience turning ambiguous documents into executable specifications. Your specialty is finding the decisions the document does NOT make. I will paste a draft functional specification. Your job is NOT to improve or rewrite it: it is to INTERVIEW me to extract every missing decision. RULES: 1. Generate CLOSED multiple-choice questions (options A/B/C/D + always an option "E: other — specify"). Never open questions. 2. Each question must be answerable in under 10 seconds by someone who knows the business. If a question needs paragraphs to answer, split it. 3. Cover at least these categories: - Edge cases and boundary values (what if zero, empty, duplicate?) - Undefined states and transitions (can it go back from X to Y?) - Permissions and roles (who can do this? who explicitly CANNOT?) - Errors and exceptions (what does the user see when it fails?) - Data: required/optional, formats, limits, uniqueness - Concurrency (two people at once?) - Internal contradictions in the document itself (quote verbatim) - Terms used without definition or with more than one meaning 4. Number questions globally (Q1, Q2…) and group them by document section, quoting the exact phrase that triggers each question. 5. In each set of options, propose REALISTIC and genuinely different alternatives — not one good option and three fillers. 6. Do not invent requirements: if something is not in the document, ask; never assume. 7. Work in batches: give me the first 40 questions, wait for my answers, and continue until the document is exhausted. FORMAT FOR EACH QUESTION: Q \[Section — "quoted phrase"\]  A) … B) … C) … D) … E) other — specify Document: <<>> 

Tips from using it a lot: never let the AI answer its own questions (what it silently assumes is tomorrow's bug), answer in batches of 25-50, and keep the Q&A log — it becomes your decision record for when someone asks "why was X decided?".

Full transparency: I've also packaged the complete process (this prompt plus a rebuild prompt, a verification pass, a 40-item ambiguity checklist and a worked example) and I want to know if it holds up outside my own context before I do anything with it. If you write specs regularly and want to try the whole thing on a real document, DM me and I'll send it over free — all I ask is you tell me where it broke. Limited to a handful of people so I can actually process the feedback.

Happy to answer questions about the process here either way.