Most market research is a lie. People say they’ll buy a product in a survey, but then they abandon their cart in real life.

Yesterday, I launched Sediman to bridge that gap. Instead of asking humans what they think, I built a behavioral engine that spawns AI Agents with rich, census-weighted personas—diverse incomes, ages, and psychological biases—and lets them "live" through a market simulation.

The Experiment:
I ran 100 agents through a "2026 Cola War" simulation.

The result? A 56.8% to 43.2% split for Coke vs. Pepsi.

The logic? My agents weren't just picking names. High-income personas clustered at Costco; lower-income personas prioritized value at Aldi. They behaved like real people under financial stress.

The Tech Stack:

Persona Layer: Deep psychographic prompting to ensure "Avery, 28n, $135k" doesn't think the same way as a retiree in Ohio.

Decision Engine: Separating the "Identity" from the "Evaluator" to prevent LLM brand bias.

Web Mode (WIP): Moving from surveys to actual site navigation audits.

Why I’m building this:
In 2026, we shouldn't wait 6 weeks for a focus group. We should be able to "unit test" our marketing strategy.

I'm currently building out the Web Agent to let these personas browse real D2C sites to find conversion leaks.

Check out the full Day 1 results here: https://sediman.com/