synthetic reactor
show it a product launch and it tells you how reddit would react.
2026-02-01 | hack
launching something and waiting to see how people react is slow, and it's expensive when you get it wrong. i wanted a preview.
synthetic reactor is a small next.js app i built in two days. it asks llama 3.1 8b, running locally on ollama, to invent a handful of reddit users. then it shows them launch posts across five subreddits, and each one comments on every post with a sentiment, a few concerns and an interest score from 0 to 100. at the end it counts everything up per subreddit and saves the run so you can replay it.
the tech is basic: one prompt per persona that returns json, a few regexes that tag the posts by theme, and some counting. small models break json a lot, so there's a fallback parser and one retry.
the first run
i pointed it at noxsoft's launch: 5 personas, 10 posts, 50 comments.
| subreddit | positive | neutral | negative | mixed | avg interest |
|---|---|---|---|---|---|
| r/technology | 0 | 0 | 10 | 0 | 91.5 |
| r/singularity | 0 | 4 | 3 | 3 | 89.6 |
| r/futurology | 5 | 4 | 1 | 0 | 84.5 |
| r/machinelearning | 0 | 7 | 3 | 0 | 79 |
| r/entrepreneur | 2 | 3 | 2 | 3 | 73.5 |
on paper that's a clear signal: r/technology hated it and cared the most. the sharpest line came from a persona called david kim:
building a tool that displaces workers while selling the safety net feels like a business model, not a solution.
why i don't trust it
here's the rest of that thread:
four of the five wrote nearly the same sentence. on r/machinelearning, two of them wrote the exact same comment, word for word:
i'm intrigued by the rag-powered intelligence, but i'd love to see some technical details on how it works.
the personas were too alike before they even commented. two separate runs both invented an emily chen who likes hiking, cooking and reading, is introverted and analytical, and is scared of public speaking and failure. only her job changed. each subreddit also has a written profile of its culture, but i never passed it into the comment prompt, so the model only knew the subreddit's name. that table is closer to one model's opinion said five times than to five people's.
if i picked it back up, i'd build the personas from real profiles instead of letting the model invent them, put each subreddit's profile in the prompt, and throw out any comment that's too close to one already written.