[ Trusted by builders from ]NetflixServiceNowCiscoAdobePayPalAmazonDatadogJPMorgan ChaseDell
[ Trusted by builders from ]NetflixServiceNowCiscoAdobePayPalAmazonDatadogJPMorgan ChaseDell
Prior.Runprior.run

FIG · 01— Field notes from the lab

From the lab.

Research notes, methodology deep-dives, and the thinking behind our engine. Written by the people doing the work, not the marketing team.


FIG · 02

Recent dispatches.

01

Featured

Why Synthetic Users Give Better Design Feedback Than Real Ones

The counterintuitive case for simulated audience reactions.

02

LLM bias

How We Built a Skeptical Audience (On Purpose)

LLMs are polite by default. That's a disaster for design feedback.

03

synthetic users

Our Audience Gets Smarter With Every Analysis

What happens when synthetic users develop pattern recognition.

04

synthetic users

Why Context Changes Everything in Design Feedback

Two identical people. The same pricing page. Opposite reactions. Both right.

05

SaaS

SaaS Pricing Page Patterns: What Actually Works

What happens when skeptical, trusting, and anxious users see the same pricing page.

06

experimentation

Kill Your Losing Experiments Before You Build Them

Most A/B tests fail. What if you could predict which ones before writing a line of code?

07

A/B testing

No Traffic? No Problem. How to Validate Designs Before Launch

You don't need a million users to know if your design works. You need the right question.

08

fintech

The Fintech Design Playbook: Conversion Without Compliance Violations

The line between persuasion and deception is thinner than your legal team thinks.

09

compliance

The Hidden Compliance Risks in Your Design

What your design team isn't catching before launch.

10

design review

Why Design Reviews Fail

And what to do instead of another meeting.

11

design validation

Design Validation Without User Research

A practical guide to making better design decisions faster.

12

design comparison

How to Compare Designs When Your Team Can't Agree

A framework for moving from preferences to decisions.

13

AI design review

What AI Design Tools Get Wrong

And how to use them without getting burned.