A 7-language PWA built solo under a 100-hour deadline

Hacker News

I read Benjamin Hardy's "The Science of Scaling," which argues for setting yourself impossible goals and timelines. So I gave myself one: build an app for our community orchestra in 100 hours. Together with the website and translated into 7 languages, it took 155 hours over less than 3 months. There are some apps like this, but none in Slovenian, and most drown you in options. Groopa does one thing: plan an event, notify members, see who's coming and stay informed. Website: https://groopa.app/en/info App: https://groopa.app I'd love your feedback, especially on how to approach distribution.

Visit product View on Hacker NewsJun 28, 2026

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

51%51% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

TrustMRRFits verified-revenue profile · Strong signals: apps, month · Missing: mobile apps, ios, personal

51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Product HuntUnlikely to reach the leaderboard · Strong signals: apps · Missing: mac, agents, macos

48%48% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

45%45% predicted probability of success on AppSumo, 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

33%33% 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

27%27% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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