WorkTop – Different desktops with different files. (Windows only)

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Obligatory clarification. This is not a virtual desktop app. Windows built-in feature "Multiple Desktops" is rather ambiguously named given the fact that it is just a virtual desktop implementation, you don't get multiple actual desktops with their own files, folders, and shortcuts. Something I have personally wanted for years, since my desktop always ends up accumulating files and I prefer spatial organization over deep folder structures anyway. WorkTop gives you separate desktops with different linked desktop folders. Meaning you can have different files on different desktops. Either because you too happen to get a messy desktop, or maybe you want a different desktop per work mode or project. Switching can be done via the tray, right clicking the desktop, or most easily via a hotkey (default is alt+w) just like you'd cycle apps with alt+tab. The app uses the built-in folder redirection functionality already present in Windows to swap out the active desktop and tracks individual desktop layouts, and makes sure the clipboard and open explorer windows stay current when switching. If you use the virtual desktop functionality in Windows, you can link WorkTop to switch files when you switch your virtual workspace. WorkTop is freemium software, the free version lets you have 3 managed desktops (OS default + 2), while the pro version ($14.99 one-time) lets you have unlimited desktops, per desktop wallpaper, and scheduled switching. https://worktop.dev I am working on Actions right now, which will let you run arbitrary commands on switch to trigger other apps (like Rainmeter for example, to switch layout). This should be ready for release soon. Happy to talk about the technical stuff (Its written in Rust so Windows API integration was interesting) or any questions about functionality.

Visit product View on Hacker NewsMay 24, 2026

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89%89% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

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

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: soon · Missing: plus, platform, intuitive

40%40% predicted probability of success on AppSumo, 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

29%29% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

14%14% 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.

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