A 3D Mac window switcher with browser tab support and search

Hacker News

Hey HN. I made this little app, because I missed Compiz but also because I wanted a way to switch between tabs as well as my windows. Around 2008 a Linux desktop could spin your windows around a cube and flip through them like cards, and so far I have not seen anything like that on Mac. I also tried a bunch of different Command-Tab alternatives like AltTab, but so far they always lacked the following things: a live visual preview of windows and some kind of way to switch and search between individual browser tabs. So I built a simple prototype and refined it over the last two months. It goes like this: press a shortcut and every open window shows up as a 3D card, in one of seven arrangements. Browser tabs get their own cards as well and you can flick through each one. Hitting space makes the search come up so you can type a few letters and it finds the window or tab. Fuzzy searching is implemented as well. I also added a quick Option + ` (key above tab) to instantly switch to the last window without any UI coming up, because I do this a lot. For the curious: Swift and Metal, window pictures come from ScreenCaptureKit and it only captures while the switcher is open, nothing runs in the background. Browser tab support is done through the accesibility strip. Apple Silicon, macOS 14+ for now. It has a seven day trial with all features, no account, no telemtry, no subscription or marketing bs. One time purchase, $12.99 during launch, $19.99 after. 14-day money back guarantee. Very curios what you guys think :)

Visit product View on Hacker NewsSep 20, 2026

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

96%96% 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: ios · Missing: supports, reddit linkedin, podcasting

77%77% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

45%45% 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

40%40% 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, subscription · Missing: mrr, revenue, profit

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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