UseDesktop is an Infrastructure layer for training Deskop Agent. Desktop agent is a type of Computer use agent built to be more useful than the traditional Computer use agent by Anthropic, OpenAI and so on. It differs by combining the non-deterministic and deterministic features which then solves latency, accuracy, cost issues. At UseDesktop, you are able to train your own Desktop Agent, Create a model with your own data. It works just as expected creating real use cases unlike other agents.
Hey Seungju, that distinction between deterministic agents versus autonomous ones that are slower and less predictable is interesting. Was there a specific task you were trying to automate where an autonomous agent kept doing something slightly different each time and you thought I just need it to do exactly what I showed it, nothing more?
My name is Seungju from South Korea and I am the founder of UseDesktop.
UseDesktop is the infrastructure for training Desktop Agent.
Desktop Agent lives in your PC and acts based on what you showed them.
It is different compared to other autonomous pro active agents like OpenClaw in the sense that its action is more deterministic making the result more
Accurate
Faster(less latency)
Cheaper(in terms of token)
It is designed privacy-first and you can connect local models to use it.
At UseDesktop, you are able to
Create Desktop Agent that will automate all your works
Train actual finetuned model based on your own data
It was started with the motto of freeing Humans from labors. As We, humans, will gradually become managers managing hundreds of AI Agents that does the labor work for us.
Try it out! and If you need any help, you can reach out to me in the Discord or through my email
“An infrastructure layer for training deskop agents”
UseDesktop launched on Product Hunt on March 12th, 2026 and earned 86 upvotes and 1 comments, placing #43 on the daily leaderboard. UseDesktop is an Infrastructure layer for training Deskop Agent. Desktop agent is a type of Computer use agent built to be more useful than the traditional Computer use agent by Anthropic, OpenAI and so on. It differs by combining the non-deterministic and deterministic features which then solves latency, accuracy, cost issues. At UseDesktop, you are able to train your own Desktop Agent, Create a model with your own data. It works just as expected creating real use cases unlike other agents.
UseDesktop was featured in Productivity (650.3k followers), SaaS (41.6k followers), Artificial Intelligence (466.8k followers), Marketing automation (3.8k followers) and YC Application (31 followers) on Product Hunt. Together, these topics include over 260.1k products, making this a competitive space to launch in.
Who hunted UseDesktop?
UseDesktop was hunted by Seungju Chae. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
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Seungju Chae