Computer-use and desktop agents

A computer-use agent operates software the way a person does: it looks at screenshots of a screen, decides where to click or what to type, and repeats until the task is done. That lets it work with desktop apps and old internal systems that have no API, which is the main reason to consider one.

The same ability makes these agents the riskiest kind to run. An agent with control of a desktop can open any app, read any file and act under whatever accounts are signed in. Run it in a separate virtual machine or a dedicated user account with only the apps and data the task needs. Keep personal accounts, password managers and admin tools out of that environment.

They are also slower and less reliable than API-based automation. Each step needs a screenshot and a model decision, pop-ups and layout changes can throw them off, and they can misread small text. Expect to watch early runs closely and to retry. For a task that a proper integration could handle, the integration is usually the better choice.

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5 AI agent tools in computer-use and desktop agents

UI-TARS Desktop

by ByteDance

Open-source desktop app from ByteDance that controls a computer through a vision model reading screenshots.

  • Open source
  • Can run on your own servers

Open Interpreter

Open-source tool that lets a model run code on your own computer to complete tasks you describe in a terminal.

  • Open source
  • Can run on your own servers

UFO

by Microsoft

Open-source Microsoft research agent that completes tasks across Windows apps using the screen and app controls.

  • Open source
  • Can run on your own servers

Manus

General agent that works in its own cloud computer to browse, write code and produce files from a single request.

Simular

Desktop agent that operates apps on your computer by reading the screen and using the mouse and keyboard.

Watch out for prompt injection. Text on a web page, in a document or in an email can be written to give the agent new instructions. Limit what the agent can do without confirmation, especially sending messages, making purchases or changing settings, and review its action log.

Good first uses are repetitive data entry between two systems, testing your own app's interface, and one-off chores where a person checks the result. Open-source agents here are useful for learning how these systems behave in a sandbox before you trust any of them with real accounts.

Logging matters more here than for any other kind of agent. Keep screenshots or a screen recording of each run along with the list of actions taken, so you can see what the agent saw when it made a mistake. Set a time limit and a step limit for every run, since a confused agent can click in circles for a long time. Before any run that touches real accounts, decide who watches it, how they stop it, and how the changes it made would be undone. If an agent needs a password to finish a task, have a person sign in for it rather than storing the password where the agent can read it.

Questions about computer-use and desktop agents

When should I use a computer-use agent instead of an API?

Only when there is no usable API or integration for the app you need. APIs are faster, cheaper and more reliable. Screen-driven agents are a fallback for desktop software and legacy systems.

How do I run a desktop agent safely?

Give it its own virtual machine or user account with only the apps and data the task needs, keep personal and admin accounts signed out, and require confirmation before it sends, buys or deletes anything.

What is prompt injection, and why does it matter here?

It is text placed on a page or in a file that tries to give the agent new instructions. Because computer-use agents read everything on screen, they can be misled by it. Limits on unconfirmed actions are the main defense.

Do these agents work on Windows, macOS and Linux?

It varies by tool. Some target Windows apps, some run in Linux virtual machines and some work across systems. Each tool page notes what we could confirm; check the project's documentation for current support.

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