Tester library

Testers with traits that matter.

Tech literacy, patience, device, accessibility, language. Identical testers tell you nothing.

Describe, don’t configure
One sentence in, and every trait and the background are drafted for you to check.
Nothing saved unreviewed
You review every line before a tester exists, and a lint pass flags a person who could not exist.
Traits, not a script
Patience, tech confidence and goals change how a tester behaves rather than what they say.
Kept for the next study
A tester you save can attempt any study in the workspace.
Core capabilities

What a tester is made of

Pick a capability to see it drawn from the sample study.

  1. Three testers ship with every workspace. The rest are yours, and each says how often it has run.

Common use cases

Who to send at a prototype first

The testers teams reach for.

choosing AI testers · sample study
Accessibility

Test with the people the room forgets

Low vision, a screen reader, large text, a right-to-left language, a slow connection. Pick them from the library and run.

“The label reads as cancel to me. I would not press it.”

AI tester · think-aloud · sample run
creating an AI tester
Your actual audience

Describe the user you already know

The cautious first-timer, the power user who compares three competitors, the professional in a hurry. One sentence each.

AI tester journeys · sample run
Before a human round

Find out which traits are worth recruiting for

Run the spread first. Where two testers diverge is where a human session is worth the scheduling.

Benefits

A spread, not copies of you

  • 6traits, all of them behavioural

    Traits, not costumes

    Every field on the form changes what happens in the session, or it would not be on the form.

  • No contradictions found

    Linted before it runs

    A tester who is both a screen-reader user and a speed-reader is flagged rather than quietly simulated.

  • Patience: lowPatience: high

    Duplicate and adjust

    Change one trait, run again, and the difference in the results is attributable to that trait.

The traits

Six fields, and every one shows up in the transcript

This is the whole form.

Tech literacy

How comfortable they are with software — the single trait that changes a session most.

Domain familiarity

How much they already know about your field, which decides whether your words help or hide.

Patience

How long they will keep trying before they give up and leave.

Primary device

Phone, tablet or desktop — what they are actually holding while they use it.

Accessibility needs

Low vision, a screen reader, large text, limited movement or a cognitive difference — the testers a team rarely gets to recruit.

Language and connectivity

Primary language, English comfort, right-to-left, slow connection.

FAQ

About the testers themselves

Can I write my own AI testers?

Yes. Pick the traits, add a background, or describe the person in a sentence and let AI draft it. No raw instruction scripts.

How do I know the traits do anything?

Compare two sessions from one run. The spread is produced by the traits, not by chance.

What stops an AI tester contradicting itself?

A lint pass flags it before it runs.

The tester app

Test from your pocket

The uTestMe tester app runs a study on a phone. Taps and screens recorded, consent first, results in the same view.

Coming soon onApp StoreGet it onGoogle Play
Scan to install
  • Tap tracking
  • Screen recording
  • Consent first
Test code · K7F2-9QA