I built a grouped app switcher for macOS

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Hey HN, I just released GroupTab after getting some feedback from the TestFlight beta. The idea came from my own frustration with the default macOS app switcher when I have 10+ apps open. You know that feeling when you're cycling through a massive list just to get to Notes or Messages, then back to your terminal, then to Xcode? GroupTab lets you organize apps into rows so you can jump between "work stuff" and "personal stuff" quicker without the endless carousel. You use Option+Tab instead of Cmd+Tab, then navigate with arrow keys (or hjkl if you're into that, or just the typical tab/shift-tab). Apps stay in their groups, so your browser windows stay with other browsers, dev tools stay together, etc. You can drag apps between groups or use keyboard shortcuts to move them around. I've been using it for a few weeks now and I'm quite happy with how it works. A few beta testers said similar things, which was encouraging. The app is $1.99 but I'm making it free until September 26th so people can try it out and see if it clicks for them. No point charging for something if it doesn't actually improve your workflow. Mac App Store: https://apps.apple.com/app/grouptab/id6751125313 More screenshots and details: https://beshr.com/grouptab/ Would love to hear any feedback if you get a chance to try it. Thanks!

Visit product View on Hacker NewsSep 23, 2025

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

93%93% 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

87%87% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

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

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: personal, apps · Missing: mobile apps, ios, entrepreneurs

43%43% 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

32%32% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit

16%16% 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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