I am refining the core promise of Menso after a useful conversation with Marc Lou at yesterday's Indie Hacker meetup in Shanghai.
Menso gives an AI user a persona and a task, lets it use a live product in the browser, and returns the replay, screenshots, decisions, and a prioritized friction report.
My original positioning emphasized the report: analyze the full path and explain the UX friction.
The sharper version may be:
Menso verifies whether the task actually succeeded. If it did not, it shows the first point where success became impossible and the evidence behind it.
The deeper UX analysis still matters, but it comes after the outcome and interruption point.
I would value blunt feedback from founders and product teams:
I am currently testing the service at $29 for one core flow, delivered within 24 hours with the replay, screenshots, and prioritized findings.
If you want, leave one real task from your product in the comments. I will tell you what I would treat as the observable success state before running it.
The interruption point is closer to a buying decision because it connects friction to observed behavior. A UX report becomes more valuable when it explains why that interruption happened, how often it occurs, and which change is most likely to improve completion.