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Patches.cafe, an offline rectangle-covering puzzle

Hacker News

Patches.cafe, an offline rectangle-covering puzzle

A few days ago, I discovered that there are games on LinkedIn (better late than never). I mainly came across Patches . I really liked the rules, but it felt rather bland, short and empty. So I thought I could make my own version, one that I’d actually enjoy playing. That’s how the idea came about to combine patches and coffee – patches.cafe. I wanted to make something cool and simple, yet something that would be engaging and fun for both short and long sessions. Meanwhile, a friend told me she’d like something she could play on a plane without an internet connection, so I added an offline PWA mode. There’s no need to create an account; your progress is saved in local storage. There are obstacles and 1,000 levels in campaign mode. I’ve already had some feedback from people on Reddit and have fixed the bits that weren’t quite right. If you’ve got a spare moment, go ahead - I’d love for you to give it a go :)

Visit product View on Hacker NewsAug 25, 2026

Actual performance

1points

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

85%85% 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.

Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

70%70% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: ide, 000, io · Missing: https docs, excited, just released

50%50% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

34%34% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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 · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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