FuseCells a new type of logic-neighbor puzzle for iOS (free, no ads)

Hacker News

Hi! I’ve been building a new type of logic-neighbor puzzle for iOS. Each cell shows how many matching neighbors it needs, and the goal is to make the entire grid consistent. It’s clean, minimal, no ads, no tracking. Made by a single indie developer. App Store: https://apps.apple.com/app/id6754704139 If anyone tries it, I’d love feedback, especially on difficulty curve and level design. Happy to answer any technical questions!

Visit product View on Hacker NewsNov 28, 2025

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Actual performance

1points

Did not reach leaderboard

Launch Intel predictions

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

80%80% 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 · Strong signals: apple, apps, new · Missing: mac, agents, macos

68%68% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

64%64% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

33%33% 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

23%23% 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

22%22% 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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