I

I brought the best Pebble watch feature to iOS and Apple Watch

Hacker News

I brought the best Pebble watch feature to iOS and Apple Watch

Hi HN, I wanted to share something exciting that I've been working on. Remember the classic word clock feature from Pebble watches? It was my default on my pebble steel (Still working like a charm to this day!). I've always loved how unique and visually appealing it was, so I decided to bring that experience to iOS and Apple Watch. Introducing Custom Word Clock - TextTime: a fully customizable word clock widget for iOS. You can personalize it to fit your style and preferences. It started as a widget for the home screen, and I'm thrilled to announce that it's now available as a lock screen widget and a complication on the Apple Watch. Here's what you can expect: Customization: Choose unique greetings, fonts, colors, and backgrounds to create a word clock that suits your taste. Widgets: Add the word clock to your iPhone's home screen and lock screen for quick access. Customization in the app applies directly to the widget. Apple Watch Complication: Get the word clock experience right on your wrist with our new complication. Numbers are so last year—why not add words to your watch? I'm really proud of how it turned out and would love to hear your thoughts and feedback! App Link: https://apps.apple.com/us/app/custom-word-clock-texttime/id6...

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Indie HackersFits the IH revenue-focused audience · Strong signals: started, ios · Missing: supports, reddit linkedin, podcasting
91%91% 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
75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: ios, personal, apps · Missing: mobile apps, entrepreneurs, video
59%59% 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, io · Missing: https docs, excited, just released
43%43% 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
41%41% 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
15%15% 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.

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