Haserupt – A different take on reducing phone usage

Hacker News

Instead of daily limits or scheduled focus sessions, Haserupt asks what you’re opening an app for before it opens. It then gives you just enough time to complete that task. Once the timer expires, the app stays unavailable for a short cool-off period. If you genuinely need more time, you can explain why and request an extension. I’m curious whether this approach feels more practical than traditional screen time apps. I’d really appreciate feedback on: 1. whether the concept makes sense, 2. whether there are obvious edge cases I haven’t considered, 3. and whether this is something you’d actually use. TestFlight: https://testflight.apple.com/join/WtPjYfFb

Visit product View on Hacker NewsJul 28, 2026

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

53%53% 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 · Missing: supports, reddit linkedin, podcasting

53%53% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

52%52% 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

28%28% 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.

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

17%17% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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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