Dialed – A Radial Calendar App for iOS

Hacker News

Hey HN! I just launched Dialed – a calendar app where your day is visualized as a clock instead of a grid. I've always found traditional calendar UIs frustrating. Lists feel like todo apps. Grids feel like spreadsheets. But we experience time circularly, like a clock face. A few months ago I saw a radial planning concept and couldn't stop thinking about it. Started building that week. Key features: Day visualized as 24-hour clock Tasks/events as colored arcs Apple Calendar sync Time analytics (planned vs actual) Custom themes Built in Swift/SwiftUI. The radial layout was harder than expected – lots of edge cases around midnight wrapping and overlapping events. This is my first iOS launch. Would love feedback on whether the radial metaphor works for you guys!

Visit product View on Hacker NewsNov 28, 2025

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: apple, apps, visual · Missing: mac, agents, macos

85%85% 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 HackersFits the IH revenue-focused audience · Strong signals: started, ios · Missing: supports, reddit linkedin, podcasting

84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

60%60% 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

45%45% 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

27%27% 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

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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