I Built an App to Reduce My Screen Time

Hacker News

It’s no secret that social media companies strive to maximize time spent in their apps — in other words, how much attention we give them. That's why I've created Atten - a screen time control app that helps safeguard your attention. Atten lets you schedule app blocking and set daily time limits for apps. I’ve always been curious about how people defend themselves against these attention-grabbing algorithms. Do you have systems in place to protect your time? Do you rely on self-discipline, or do you use screen-time control apps like Atten, AppBlock, Jomo, Opal, or something else? In a world where attention is commoditized, could having these apps enabled by default be as essential as locking your doors at night? If we all agree you shouldn’t go grocery shopping on an empty stomach, should using screen time control tools become a hard-and-fast rule for our devices? I’d love to hear your thoughts: - Do you find these apps genuinely helpful? - What strategies do you use to avoid falling prey to social media algorithms? Let me know what you think! Check out Atten here: https://apple.co/4dZIfKa https://www.atten.app (Free Lifetime Access Promo For This Month)

Visit product View on Hacker NewsNov 17, 2024

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

86%86% 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 · Strong signals: created, maximize · Missing: supports, reddit linkedin, podcasting

83%83% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

65%65% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

50%50% 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 · Strong signals: lifetime access · Missing: plus, platform, intuitive

47%47% 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

21%21% 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.

Incorrect prediction on native model

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