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Prostir – A calm productivity app to plan without burnout

Hacker News

Prostir – A calm productivity app to plan without burnout

Hi HN, I’ve been working on Prostir, a simple productivity app that helps you plan your day, capture thoughts, and build habits — without feeling overwhelmed. The idea came from personal frustration: most tools either try to do everything or feel too rigid. I wanted something calmer — a space to think, not just check things off. So I built Prostir using Swift + SwiftUI, with focus on speed, minimalism, and offline support. I’ve been building Prostir, a mindful productivity app that helps you organize your day, jot down thoughts, and build healthy habits — without getting overwhelmed. It’s already available on the App Store and has gone through a few iterations based on early feedback. The goal has always been the same: to create a calm and simple space for planning, especially for people who find traditional task managers too rigid or stressful. Prostir is free to try, and if anyone here wants to explore the premium features, I made a promo code specifically for the HN community: Use promo code in appstore: "HACKERNEWS" Prostir: https://apps.apple.com/us/app/daily-planner-prostir/id653569... Would really appreciate your thoughts or impressions. Always learning from how others approach building focused, human-friendly apps. Would love your feedback or ideas — especially if you’ve built something similar or tried calming productivity tools before. Thanks for checking it out!

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3points
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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
90%90% 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
62%62% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: personal, apps, way · Missing: mobile apps, ios, entrepreneurs
54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: friendly · Missing: plus, platform, intuitive
45%45% 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
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 · 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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