Derrick Lawter

Projects · Case study

ValidateNine

Synthetic focus groups for pressure-testing ideas and messaging early.

The ValidateNine homepage - AI-powered focus groups with four persona portraits
Status
Deployed product
Role
Designer and builder
Team
Solo

The problem

Real focus groups are slow and expensive, so most small teams skip them and guess. I wanted to find out how much useful signal you could get from a simulated version - and where that signal stops being trustworthy.

What I built

You submit a concept or a piece of messaging. ValidateNine generates a panel of distinct personas with different backgrounds and priorities, has each one react, and consolidates the responses into a structured report: what landed, what didn't, and where the panel disagreed.

Decisions that mattered

  • Keeping personas genuinely distinct, so the panel doesn't collapse into one voice with different names.
  • Structuring the output as a report a decision-maker can scan, instead of a wall of generated text.
  • Being explicit in the product about what a simulated panel is and isn't.

I designed and built all of it: the product, the React/Vite front end, the Supabase database, the prompt architecture, and the deployment.

My contribution

All of it. No team on this one.

What this doesn't prove

ValidateNine is a working, deployed application. It is not evidence that synthetic personas predict how real people respond, and it is not evidence of commercial traction. The more interesting question - which I'm still working through - is what evidence would justify using synthetic feedback for a particular decision.

Stack

  • React
  • Vite
  • Supabase
  • OpenAI API
  • Vercel
  • Cursor