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How to Go from Product Idea to Prototype in 20 Minutes with an AI-Enhanced PM Workflow

Move a product idea through evidence gathering, a structured opposing-view debate, a decision-ready PRD, a clickable prototype, and a short vision asset without confusing generated output for validated demand.

How to Go from Product Idea to Prototype in 20 Minutes with an AI-Enhanced PM Workflow

Source episode · 04:00

How I AI: Marily Nika’s AI Native PM Workflow (Perplexity, Veo, v0, Notebook LM)

with Claire Vo

Marily researches smart-fridge sentiment in Perplexity, has opposing agents debate the idea, turns the resulting feature hypothesis into a PRD, builds a v0 prototype, and generates a product vision video.

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Before you start

What you need

  • A specific user, problem, and product hypothesis
  • Approved public research sources and search terms
  • A PRD template with decision and evidence fields
  • A prototyping tool such as v0
  • A vision-video tool and brand-safe assets

What you’ll make

A product-review package containing source-linked research, explicit assumptions, a scoped PRD, a clickable prototype, and a clearly labeled concept video.

Tools used

Step by step

The workflow

Follow the sequence once, then adapt the prompts, checks, and handoffs to your own setup.

4 steps

Step01

Conduct Instant User Research with Perplexity

Research the user problem in Perplexity’s discussion sources. Collect representative positive and negative evidence, then ask opposing agents to debate the hypothesis and identify the minimum claims that still need validation.

Example prompt
Research whether [target user] experiences [problem] and would value [idea]. Use public discussion sources from [date range]. Return recurring needs, objections, alternatives, counterexamples, and representative links. Then have a pro and skeptical analyst debate the evidence. End with the smallest feature hypothesis, riskiest assumptions, and direct research questions. Do not present the debate as customer validation.

This technique helps avoid confirmation bias and forces the AI to surface genuine user concerns and critical feature requirements.

Step02

Generate a Product Requirements Document (PRD) with a Custom GPT

Feed the evidence and feature hypothesis into a configured PRD assistant. Require source links, problem and user definition, success measures, non-goals, constraints, decisions, assumptions, and open questions.

Example prompt
Draft a PRD from this evidence packet. Preserve source links. Separate observed evidence from hypotheses. Include target user, problem, user narrative, goals and measurable success, critical path, requirements, non-goals, privacy and technical constraints, decisions, open questions, and a validation plan. Do not invent market size or customer claims.

Creating a custom GPT for your common documents (PRDs, creative briefs, etc.) can save hours of formatting and boilerplate writing.

Step03

Create a Clickable UI Prototype with v0.dev

Give the PRD to v0 or another prototyping tool and build the smallest clickable critical path. Use realistic synthetic data, inspect generated additions, and test the flow with stakeholders or target users.

Example prompt
Create a clickable prototype for the critical path in this PRD. Use realistic synthetic data, make assumptions visible, preserve the stated privacy constraints, and do not add unrelated features. Include the states needed to test [risky interaction] in a product review.

A visual prototype is far more effective for stakeholder reviews than a document alone. It helps everyone see, touch, and feel the product vision.

Step04

Sell the Vision with an AI-Generated Video

Turn the user narrative into a short concept-video brief. Generate several candidates, reject visual inconsistencies or unsupported behavior, and present the selected video beside the PRD and prototype as a vision aid.

Example prompt
Create a [duration]-second concept video from this user narrative: [narrative]. Show the user problem, the critical interaction, and the outcome. Keep product behavior consistent with the PRD, avoid unsupported claims, and label the result as a concept visualization.

AI video generation is still new, so be prepared to iterate and refine your prompts to get the desired result. Combining the video with your PRD and prototype creates a powerful pitch package.

What good looks like

  • Research claims link to representative source discussions and note sample limits.
  • The PRD separates observed needs, hypotheses, decisions, and open questions.
  • The prototype demonstrates the critical user path rather than decorative screens.
  • The vision video illustrates the intended experience without becoming proof of feasibility or demand.

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After the steps

Runbook notes

How to recover when the loop fails and where human judgment helps.

Recover

If it goes sideways

A synthetic debate is presented as user validation
Retain source links, label debate output as analysis, and schedule direct research for the highest-risk assumption.
Information changes meaning as it moves between tools
Use a structured handoff with evidence, assumptions, decisions, and open questions, and compare each output with the prior artifact.
The prototype invents features or architecture beyond the PRD
Mark generated additions, remove distracting scope, and center the review on one critical user journey.
The generated video depicts impossible or misleading behavior
Use a written user narrative, label the video as a concept, and call out feasibility questions beside it.

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