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How Litmus works

From your problem statement to a structured report — in plain language.

1

You tell us what you’re testing

A problem statement, an idea (or design images), and a target audience. The problem statement is the highest-signal input — people post about problems on Reddit and X, not about solutions, so this is what drives our search later.
2

We figure out who your users are

A model parses your audience description into structured axes — geography, age range, profession, life stage. These become the diversity constraints for the personas we generate.
3

We scan Reddit and X for real voices

Using your problem statement, idea, and audience axes, we find ~6–12 relevant subreddits and ~6–10 X search queries. We pull the last 30 days of posts, drop noise (low-engagement, deleted, off-topic), and keep ~30–50 genuine snippets that match your problem space.

This is the “real voices” part. Every quote we pull keeps its source URL so you can verify the provenance later.
4

We generate the synthetic personas

A model creates 10 diverse personas spanning your audience axes. Critically, each persona gets 2–3 verbatim quotes from real Reddit and X postsbaked in as their authentic voice samples. We also force a 33/33/33 split across sympathetic / neutral / contrarian stances so the test doesn’t skew positive.
5

We interview each persona in character

All 10 personas run in parallel. Each is given their full profile (including the grounded voice samples) and the interview script. They answer in character — speaking with the voice of the real people they’re grounded in, not generic AI-speak.
6

We synthesize the report

A model aggregates all 10 interview transcripts into a structured report: headline finding, executive summary, where it works, where it fails, themes with verbatim quotes, sentiment distribution, stance breakdown, and concrete next steps.

Two things to know

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