• HYPOTHESIS
  • WORKFLOW
  • PLAN
  • HUMAN

How to scope MVP experiments with your AI

Connect your agent to your product documentation once. From there, it finds the tightest possible test hidden in your roadmap.

Ask AI about this page

Short answer

How can I use AI to scope an MVP experiment?

Your agent reads your documented user workflows to find the highest-leverage test for a new feature. It shrinks a massive roadmap into a single, one-week experiment. You get a clear hypothesis and a specific test plan.

The experiment outcomes.

What you get from the discovery process.

The agent processes your roadmap and workflows to produce these four results.

HYPOTHESIS

A single testable claim

The AI distills your feature idea into a clear statement. You get a specific prediction to prove or disprove.

WORKFLOW

Mapped user paths

It identifies where the new feature fits into existing user behavior. You see the specific friction points being targeted.

PLAN

One-week test scope

The agent strips away everything that isn't essential for the test. You receive a lean set of requirements for a seven-day sprint.

HUMAN

Final strategic review

The AI flags edge cases it can't resolve. You decide if the experiment aligns with your long-term product vision.

The workflow

What your AI does when the roadmap arrives.

The agent does the heavy lifting of parsing documentation so you can focus on the decision.

  1. Analyze workflows

    The agent reads your current user journey documentation to understand how people actually use the product.

    validate_product_discovery

  2. Identify friction

    It looks for gaps between your roadmap goals and current user workflows to find where a test is needed.

    validate_product_discovery

  3. Shrink the scope

    The agent removes any feature bloat that doesn't directly test the core hypothesis.

    validate_product_discovery

  4. Draft the experiment

    It produces a structured plan for a one-week test based on the validated discovery data.

    validate_product_discovery

Try it

Copy these to start.

Use these prompts to kick off the discovery process.

Starting points

Replace the bracketed text with your specific document names or feature ideas.

Product Discovery Prover Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_oRfntTCBhavUOPmcOZLkfPw8gtNLViGrf1SALzQt/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Product Discovery Prover capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "product-discovery-prover-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_oRfntTCBhavUOPmcOZLkfPw8gtNLViGrf1SALzQt/mcp"
    }
  }
}
Copy into chat04

  • Analyze the user workflows in my Notion doc and find a single experiment for the new checkout feature.

  • Look at the product roadmap in this Google Sheet and suggest a one-week test for the search improvement.

  • Based on the user journey map in my local folder, what is the smallest MVP we can build to test user retention?

  • Review the feature requests in this Slack thread and scope a single experiment to validate the most requested item.

  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Start here

Connect Product Discovery Prover once, then ask.

One click connects your agent to the MCP. Your credentials stay encrypted and secure, and you can start prompting immediately.

Connect Product Discovery Prover to your AI

FAQ

How this task behaves.

  • 01

    Can the AI write the actual code for the MVP?

    No. The AI scopes the experiment and defines the requirements, but you must write the code.

  • 02

    Does the AI change my original roadmap documents?

    No. The AI only reads your documentation to generate new experiment plans. It cannot edit your files.

  • 03

    How does it know which experiment is the best one?

    It uses the workflows you provide to find the path of least resistance for a quick test.

  • 04

    Can I use this with any AI client?

    Yes, as long as your client supports the Model Context Protocol.

  • 05

    Will it suggest features that aren't in my roadmap?

    It focuses on the data it reads, but it can suggest specific ways to test existing ideas more effectively.

  • More questions about Product Discovery Prover? The Connector page answers them. See everything the Product Discovery Prover Connector can do

Connect Product Discovery Prover to Claude, Cursor, ChatGPT & more