Why This Page Exists
A replica is only as good as the question you ask it. As in a real moderated interview, the quality of your results depends on how the questions are written. There is one added wrinkle for AI.How Replicas Fail Differently From Humans
Understanding the failure modes makes the anti-patterns below make sense.They can tell you what you want to hear
A leading or loaded question invites agreement. Replicas, like people, drift toward the framing
you hand them.
They can converge to the majority
On divisive topics, weak questions flatten the real spread. Use larger cohorts and neutral
framing to preserve genuine variance.
They anchor on numbers you show
Reveal a price or a friction point in the question and it contaminates every downstream answer.
They over-explain
If the question presumes a behavior, replicas will rationalize it rather than tell you it is
wrong.
Anti-Patterns to Avoid
Rules of Thumb
Keep prices and friction out of the question text
Never state a price you want to test, and never name the weakness you suspect. Let the replica
reveal it.
Get their first reaction before showing options
Get the honest first reaction before you show options side-by-side. Comparison changes how
people think.
Put the concept you care about in the middle
AI pays extra attention to whatever comes first, so do not list your favored option at the top.
Keep outcomes symmetric
Offer balanced go and no-go choices, not a menu tilted toward the answer you want.
Asking the Same Thing More Than Once
Yes, you can, and there are two deliberate ways to do it.1. The rephrase (fragility) check
Rewrite one or two of your most important questions in slightly different words and run them. If a replica gives a noticeably different answer to a reworded version that means the same thing, the original question was fragile: the framing, not the substance, was driving the result. Robust findings survive rewording.2. The split by intent
Run the same concept against the same cohort with two different mindset framings (for example, two different jobs-to-be-done). Comparing the results shows how the concept lands for different motivations, which is useful signal rather than a contradiction.Screening First
If a study is only meaningful for a subset of people (for example, people who personally pay for the subscription), screen for it. Screening keeps you from surveying a fantasy population, which is the most common way a result ends up looking impressive but wrong. You add up to three pre-screen questions when you build a cohort; each replica is then marked Qualified or Rejected, with the confidence, the reasoning, and a supporting quote shown.We Take a First Pass, but Review Before You Run
When you set up a Rehearsal in the intake chat, Rehearsals takes a first pass at your questions and runs them through our system to reduce leading, loaded, or anchored framing. That first pass is a starting point, not a guarantee, so always read the questions yourself before you launch.Next: Interpreting Results
What to do when a simulation does not match your expectations.