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SERIES NO. 01 · EPISTEMIC INTEGRITY DISPATCHES
Critical Perspectives & Essays

What we think about.
And where we draw the line.

Honest intellectual positions on synthetic research — where it is genuinely transformative, where it breaks down, and the ethical boundaries we refuse to cross just to make marketing copy sound cleaner.

“If synthetic users always validate your thesis, you haven't built a research panel — you've built an expensive digital mirror.”
The Panelist Research Philosophy
10 Philosophical EssaysIntellectual Rigor
01
№ 01·Perspectives
5 min read

Synthetic panels are a gut-check, not a replacement

It would be easy to let the marketing copy drift toward 'skip user research entirely.' Here's exactly what a synthetic panel can and can't tell you, and why we keep saying so even when it costs us a cleaner pitch.

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02
№ 02·Perspectives
5 min read

AI market research: how accurate is it really?

Accuracy isn't one number. It's a set of separate, checkable claims — and most of what gets called 'accuracy' in AI research marketing is actually a claim about something else entirely.

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03
№ 03·Perspectives
5 min read

Why we said no to fake respondent counts

It would be easy to show '10,000 simulated respondents' on a panel result. We don't, because a panel of five distinct personas and a panel of ten thousand near-identical copies would look the same on that number.

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04
№ 04·Perspectives
5 min read

The honest limits of synthetic customer research

A running list of what synthetic research structurally can't do — not caveats buried in fine print, but the actual boundary of the method, stated plainly.

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05
№ 05·Perspectives
5 min read

When a founder should ignore the panel

A synthetic panel's answer isn't always the right input to weight heavily. Here are the specific situations where the honest move is to override it.

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06
№ 06·Perspectives
5 min read

Why every panel needs a real skeptic

A panel of five agreeable personas tells you less than a panel of four agreeable ones and one genuine skeptic. Here's why we build toward dissent on purpose.

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07
№ 07·Perspectives
5 min read

Synthetic research and the 'sounds great' problem

Language models are trained to be agreeable and helpful — which makes them structurally biased toward telling you your idea sounds great, whether or not it actually is.

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08
№ 08·Perspectives
5 min read

What research teams get right that AI personas can't

A real research team brings things to a study that no synthetic panel can replicate — not because the AI is bad, but because these are structurally human skills.

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09
№ 09·Perspectives
5 min read

The ethics of simulating a customer who doesn't exist

Generating a persona that talks like a real kind of person raises real questions about representation, stereotype, and what it means to speak 'for' a group that never consented to it.

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10
№ 10·Perspectives
5 min read

Why we publish our own methodology's limitations

Most vendors bury their limitations in a footnote, if they mention them at all. We put ours in the main navigation, because a limitation you can't see is a limitation you can't guard against.

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