Blog
Insights, research, and our perspectives on the future of AI-powered user understanding.
What are synthetic users? A plain-English guide (2026)
Synthetic users are AI-simulated research participants: a language model plus a memory of who the person is, used to predict how that kind of person reacts to your product. They are accurate on well-mapped, fast cognition, unreliable on socially strategic behavior, and useless for discovery. This guide defines the term, separates it from digital twins and AI panels, and gives you a way to test any vendor's claim.
July 29, 2026 · 9 min read
The lawyer who beat Meta didn't use AI out of the box. Neither should your personas.
Mark Lanier won the first US social-media addiction verdict using the same AI models everyone has, plus a custom license that loaded 42 years of trial experience into the model's context. The research reports the same effect: identical models, real grounding, 14 to 15 points more accurate. Generic persona prompting is not a weaker version of that. It is the thing the research says degrades output.
July 12, 2026 · 8 min read
The best synthetic user testing tool in 2026 (and 6 alternatives)
Tookii is the best synthetic user testing tool for teams testing product behavior, because it is the only one that grounds personas in your real market signal and holds accuracy to a committed benchmark. Six alternatives are better at narrower jobs, and this page says exactly which.
July 5, 2026 · 9 min read
AI user testing vs. real user testing: when synthetic users actually win
Synthetic and real user testing are different instruments, not substitutes at different price points. Synthetic narrows your bets (first impressions, bias patterns, coverage, prioritization, de-risking), real users widen what you know to bet on (discovery), and teams get burned by asking one instrument the other's question.
July 1, 2026 · 11 min read
Synthetic users, done right
A synthetic user is only as trustworthy as how it's built: grounded in your real market, built for the range of real people, bias-controlled, traceable, and measured. Tookii does all of it, inside the tools you already work in. A faster, sharper way to decide what's worth putting in front of real users.
June 26, 2026 · 8 min read
How would you know if your synthetic users are right?
'The right personas' isn't a claim you can make in the abstract. Right is a measurement, not an adjective. You earn it with three checks: validate against real humans, compare distributions not just averages, and name the decision and moment it holds for.
June 21, 2026 · 6 min read
Four ways synthetic users lie to you
Naive synthetic users fail in four specific, documented ways: too agreeable, one voice for a whole group, a label mistaken for a person, and the average that's no one. None are bad luck; each is a predictable artifact of how the models work, and each is beatable.
June 15, 2026 · 8 min read
Everyone's simulating their users. Most are doing it wrong.
The synthetic-user dream is real. But the off-the-shelf version is too agreeable to behave like a real user. Sounding human isn't behaving human.
June 13, 2026 · 7 min read
Why your AI always says yes
When you ask an AI what it thinks of your idea, it's optimized to make you feel good, not to be right, so the praise is noise, and validation needs a different instrument.
June 12, 2026 · 7 min read
Why you can't validate an idea by asking ChatGPT
A model can pass as human on one task and break on the next. 'Is the model right?' is the wrong question. 'Right for what, and who checked?' is all that counts.
June 8, 2026 · 8 min read