Disconnect – an iOS app blocker only a friend can unlock

Hacker News

Disconnect is an app blocker for iOS that lets you put a friend in control of granting you access to blocked apps. Like many, I've personally struggled a lot with phone and social media addiction over the years. I tried the usual tactics to get over this addiction -- deleting the apps (they make their way back in somehow), deactivating my accounts (they get reactivated again somehow), even tried some existing screen time blocking apps as well. Nothing worked. The final thing that worked for me was the following: 1- I changed my passwords to something random, on all the social media apps I wanted to get rid of. Didn't note down these passwords anywhere. 2- Changed the password recovery routes for these accounts to email and phone number of my partner's. Gave them the explicit instruction not to hand over the reset code when I ask, unless I've a compelling reason. 3- Signed out completely. The above worked surprisingly well. Knowing I can't access the apps myself and have to go through convincing my partner to let me back in, was a significant hurdle to get over. Disconnect embodies the same mechanism. It lets you pair up with a friend. When you put a hard block on apps, you can only get access to them if your buddy grants you access. You can send an access request from within the Disconnect app. The app uses system Screen Time APIs on iOS, and all your app usage analytics stays on your device. Your buddy doesn't get any analytics either, beyond the name of the block rule you choose at time of rule creation. App is free to download, with a pro tier for unlimited rules and unlimited buddies. Would love your feedback. A short demo here: https://youtu.be/zzybd_qYWcE More info: https://disconnectapp.co

Visit product View on Hacker NewsSep 15, 2026

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

85%85% 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: apps, email, code · Missing: mac, agents, macos

81%81% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

71%71% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

37%37% 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 · 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

27%27% 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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