Always remember why you unlocked your phone

Hacker News

A little something I have been working on and wanted to share it here to see if it’s useful Have You ever picked up your phone to do one thing and suddenly you’re , scrolling through social media, watching videos, or browsing random stuff. Two hours later, you can't even remember why you picked up your phone in the first place! I tired to solve this problem by creating a lock screen widget that you see every time on your Lock Screen before picking up your phone, you can quickly tap the widget and enter the reason why you unlocked your phone. This way you can choose to keep browsing your phone and be sure that you will not forget. You also get a reminder 10 minutes later to ask you if you are done with the intended task. Only on iOS https://apps.apple.com/de/app/unlock-mate-reminders/id673663...

Visit product View on Hacker NewsOct 16, 2024

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

77%77% 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 · Missing: mac, agents, macos

73%73% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

56%56% 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

37%37% predicted probability of success on AppSumo, 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

29%29% 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

20%20% 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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