aiDex for Product Managers: Run Your PRD Through a Critique Panel
Use a panel of AI models to pressure-test a product spec, then force a decision.
TL;DR
Product managers can pressure-test a PRD by running it past several AI models at once in aiDex, not just one. Drop the spec into the chat, use Compare to read independent critiques side by side, then use Judge to rank the real blockers and decide what to fix first.
How can a product manager review a PRD with AI?
Paste the product requirements document into aiDex, open Compare, and ask three models the same question: "What is missing, risky, or contradictory in this PRD?" Each model answers in its own column, so you read three independent critiques side by side instead of one model's best guess. A single assistant tends to agree with the framing it was handed. A panel does not, because the models were trained differently and tend to catch different gaps.
aiDex is a multi-model panel chat. You can sit up to five models around one conversation (Claude Opus 4.8, GPT-5.4, Gemini 3.1 Pro, DeepSeek V3.2, plus local Ollama), and every model reads the same document you drop into the chat. Use your own provider keys or the ones we manage, and pick the models you want.
Which mode critiques a PRD best?
Compare is the workhorse for a first read. It runs the same prompt across the models you picked and lays the answers out in parallel, which is exactly what you want when you are hunting for blind spots. One model flags a missing success metric, another questions the rollout sequence, a third points at an edge case in the permissions model. You keep what is real and discard the noise.
When the critiques disagree, switch to Judge. Judge takes the panel's answers and has a model weigh them against each other, then name the single most important issue to fix first. That matters for a PRD, because a list of twenty concerns is not actionable, but "the auth flow has no error state and that blocks the whole feature" is.
For a rewrite, run a Pipeline. The PRD moves through staged roles (Draft, Critique, Revise, Polish), each handled by the model best suited to it. You hand in a rough spec and get back a tightened one with the critique already folded in.
What does a critique panel catch that one model misses?
Three things show up consistently. First, framing bias: a single model usually accepts your premise, while a second or third model questions whether the feature should exist at all. Second, scope gaps: different models flag different missing sections (analytics, error states, migration, accessibility), and the union of their flags is wider than any one list. Third, internal contradictions, where section 2 promises something section 6 quietly removes. Reading the answers in columns makes those contradictions obvious.
None of this requires fabricated scores. You are not asking which model is smartest. You are using disagreement as a signal: where the panel splits is usually where your spec is underspecified.
How do I run the critique in aiDex, step by step?
Drop the PRD (DOCX, PDF, MD, or txt) into the chat so every model reads the full text. Open Compare and pick two or three models with different strengths. Ask one precise question, for example "List the assumptions this PRD makes that are not stated, and the top three risks to the launch." Read the columns, then send the disagreements to Judge to get a ranked, decide-first answer. If you want a clean rewrite, move the whole thread into a Pipeline. Costs are visible per message in the Dex, and you can set a spending limit before you start.
For a recurring review ritual, open a Team chat with the same model lineup and treat it as a standing critique panel your whole product group can reuse.
When should a PM use Judge instead of Compare?
Use Compare when you want breadth: every angle, every flagged gap, nothing collapsed yet. Use Judge when you have the angles and need a decision: which risk is the real blocker, which of two rollout plans to back, which critique to act on this sprint. Most PRD reviews use both in sequence, Compare to open the problem up and Judge to close it down. The pillar guide on multi-model AI workflows walks through chaining the modes in more detail.
The aiDex Team · Multi-model AI platform
aiDex is a multi-model AI platform that lets you query several AI models at once, compare their answers, run consensus picks, and chain models in pipelines or open team chats. Use your own provider keys or the ones we manage, and pick the models you want.
Frequently asked questions
Which aiDex mode should a product manager start with for a PRD?
Start with Compare. It runs the same critique prompt across the models you pick and lays the answers out in parallel, so you see gaps that any single model would miss. Move to Judge once you need to rank the issues.
Can the AI models read my full PRD?
Yes. Drop the PRD as DOCX, PDF, MD, or txt into the chat and every model in the conversation reads the same full document before answering.
Why use multiple models instead of one for a spec review?
Different models catch different gaps. One flags a missing metric, another questions the rollout, a third spots an edge case. The union of their critiques is wider than any single model's list.
How do I turn the critique into a decision?
Send the panel's answers to Judge. It weighs the critiques against each other and names the single most important issue to fix first, which turns a long list of concerns into one clear next step.
Does this cost extra for the bigger models?
Per-message costs are visible in the chat and you can set a spending limit before you start. Use your own provider keys or the ones we manage, and pick the models you want.
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