Pebbles – recurring reminders for stuff you forget

Hacker News

Hi HN, I made an Android (iOS coming soon) app called Pebbles for the recurring chores of being an adult: car registration, filters, smoke alarms, dentist, appliance servicing, pet meds... the list of tiny obligations that somehow become emergency situations. Idea: turn “boulders” into “pebbles” by reminding you early, consistently, and on a schedule that doesn’t make you hate your phone. Highlights • Offline-first (no account required) • Granular recurring reminders + notification windows • Built for the “I’ll definitely remember” crowd (that's me) Link: https://play.google.com/store/apps/details?id=com.pebbles.ap... If you try it: tell me what’s missing, what’s annoying, and what you’d pay for (if anything) once sync exists.

Visit product View on Hacker NewsFeb 27, 2026

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

68%68% 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: google, apps, tiny · Missing: mac, agents, macos

57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

55%55% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

40%40% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

34%34% 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 · Strong signals: recurring · Missing: arr, mrr, revenue

31%31% 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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