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Strophae, multi personas chat interface

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Strophae, multi personas chat interface

Recently I built an ensemble of synthetic persona agents for a client in advertising. It turned out to be a much better brainstorming tool than a single chat, because the differences between the personas are the useful part. So I wrote an open-source desktop version. You compose a council of agents with name, model and system prompt. Every message you send is broadcast to all of them in parallel, each answers in its own column. It use your OpenRouter key, one request per agent. The obvious cost is that N personas means N× the tokens, so I suggest you to keep the councils small and use cheap models if possible. Electron + Bun + React, MIT license. Happy to hear what you think.

Visit productView on Hacker NewsJul 31, 2026
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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, model · Missing: mac, macos, cursor
92%92% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersIH features products with proven revenue · Strong signals: para · Missing: supports, reddit linkedin, podcasting
48%48% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: interface · Missing: plus, platform, intuitive
46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: answers, para · Missing: mobile apps, ios, personal
43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
39%39% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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