Hi HN, We’re Mahmoud and Alan, building Cyberdesk ( https://www.cyberdesk.io/ ), a deterministic computer use agent for automating Windows desktop applications. Developers use us to automate repetitive tasks in legacy software in healthcare, accounting, construction, and more, by executing clicks and keystrokes directly into the desktop.
Here’s a couple demos of Cyberdesk’s computer use agent:
Completing a lightning fast file import automation into a legacy desktop app: https://youtu.be/H_lRzrCCN0E
Working on a monster of a Windows monolith called OpenDental (showcases agent learning process as well): https://youtu.be/nXiJDebOJD0.
Filing a W-2 tax form: https://youtu.be/6VNEzHdc8mc
Many industries are stuck with legacy Windows desktop applications, with staff plagued by repetitive tasks that are incredibly time consuming. Vendors offering automations for these end up writing brittle Robotic Process Automation (RPA) scripts or hiring off-shore teams for manual task execution. RPA often breaks due to inevitable UI changes or unexpected popups like a Windows update or a random in-app notification. Off-shore teams are often unreliable and costlier than software, plus they’re not always an option for regulated industries.
I previously built RPA scripts impacting 20K+ employees at a Fortune 100 company where I experienced first hand RPA’s brittleness and inflexibility. It was obvious to me that this was a bandaid solution to an unsolved problem. Alan was building a computer use agent for his previous startup and realized its huge potential to automate a ton of manual computer tasks across many industries, so we started working on Cyberdesk.
Computer use models can struggle with abstract, long-horizon tasks, but they excel at making context-aware decisions on a screen-by-screen basis, so they’re a good fit for automating these desktop apps.
The key to reliability is crafting prompts that are highly specific and well thought out. Much like with ChatGPT, vague or ambiguous prompts won’t get you the results you want. This is especially true in computer use because the model is processing nearly an entire desktop screen’s worth of extra visual information; without precise instructions, it doesn’t know which details to focus on or how to act.
Unlike RPA, Cyberdesk’s agents don’t blindly replay clicks. They read the screen state before every action and self-correct when flows drift (pop-ups, latency, UI changes). Unlike off-the-shelf computer use AIs, Cyberdesk runs deterministically in production: the agent primarily follows the steps it has learned and only falls back to reasoning when anomalies occur. Cyberdesk learns workflows from natural-language instructions, capturing nuance and handling dynamic tasks - far beyond what a simple screen recording of a few runs can encode.
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