Manus has introduced a new capability called “My Computer,” allowing AI agents to operate directly on users’ local computers—bringing AI beyond isolated cloud environments into everyday workflows.

This matters because it extends AI from executing tasks in controlled cloud environments to operating directly on personal machines—forcing a key question for businesses: which workflows should now be automated, and who controls that execution?

Until now, Manus operated inside a secure cloud environment, limiting its ability to access local files, development tools, and applications. With the introduction of “My Computer,” Manus enables a hybrid model where cloud intelligence coordinates actions while local machines handle execution.

This directly impacts developers, small businesses, and everyday users who manage workflows across local files, applications, and cloud services—and can now begin automating those environments with AI agents.

In short: AI agents are moving from answering questions to executing real work directly on your computer.

AI agents with local execution capabilities are evolving into operating layers that can control files, applications, and workflows across personal computing environments.

Meta’s Manus Desktop enables AI agents to operate directly on local computers, allowing automation across files, applications, and development environments.

The introduction of Manus’s “My Computer” capability comes after Meta’s December 2025 acquisition of Manus, an AI startup known for building autonomous agents that can execute complex tasks across software environments.

According to TechCrunch, Meta acquired Manus to move beyond traditional AI assistants and invest in systems that perform multi-step actions rather than just generate responses.

Manus has consistently positioned itself less as an assistant and more as an execution engine—designed to plan tasks, use tools, iterate on results, and deliver completed work.

VentureBeat notes that the acquisition reflects an enterprise focus on controlling how AI systems execute real work—moving beyond generating outputs to completing tasks across cloud and local environments.

Meta has also indicated it plans to keep Manus operating independently while integrating its agent capabilities across platforms like Facebook, Instagram, and WhatsApp, where Meta AI is already available. This points to a dual strategy: expanding distribution through consumer platforms while advancing execution capabilities across devices and workflows.

By enabling Manus to operate directly on local machines through the “My Computer” capability, Meta is extending AI execution beyond the cloud and into the environments where everyday work actually happens.

Until now, Manus operated entirely inside a secure cloud sandbox—an isolated environment with access to tools like a command line, file system, browser, and network. While this allowed Manus to execute tasks autonomously, it was limited to that environment and could not directly interact with the files, applications, and workflows on a user’s personal computer.

The introduction of “My Computer”—delivered through the new Manus desktop application—removes that limitation by allowing Manus to operate directly on local machines.

Manus interacts with a user’s computer through a command line interface (CLI), a text-based control system that enables it to:

The key point: AI agents are becoming execution layers for operating systems, using tools like the command line to translate user intent into real actions across software environments.

This approach enables a wide range of practical use cases:

For example, a small business owner could ask Manus to organize thousands of product photos into categories, while an accountant could standardize hundreds of invoice filenames in minutes—tasks that would otherwise take hours to complete manually.

What previously required repetitive, time-intensive work can now be completed in minutes through natural language instructions.

When Manus can access the full set of development tools on a user’s machine—from Python and Node.js to Swift and Xcode—the scope of what it can build expands significantly.

Because Manus operates through command line execution, it can:

In one internal example, Manus was tasked with building a real-time meeting translation and subtitle application in Swift on macOS. The entire process—from project setup and coding to debugging and packaging—was handled through terminal commands.

Within about 20 minutes, the result was a fully functioning Mac application, built without manually writing code or opening traditional development tools like Xcode.

This illustrates what becomes possible when an AI agent gains direct access to a local machine: it can move beyond assisting with coding tasks to handling complete development workflows across tools and environments.

Manus also introduces a new way to use local hardware resources—turning personal machines into active AI workers instead of idle devices.

Many users already have powerful compute resources sitting unused, such as GPUs in their computers or secondary machines like a Mac mini running in the background. With the “My Computer” capability, those resources can now be used to run AI tasks locally.

Users can assign tasks to Manus, which can then use:

For example, a user could send a request from their phone while away from home, and Manus would execute the task on their computer—without needing direct access to the machine.

This creates a hybrid model where:

As long as a device is powered on and connected, it can function as a persistent AI worker, quietly handling tasks in the background from anywhere.

Manus already integrates with services like Google Calendar and Gmail, and the “My Computer” capability extends those workflows to include local machines.

For example, a user who is away from their computer might need a contract stored on their home device. Instead of manually accessing their computer, they can simply ask Manus to retrieve it.

Manus can then:

In this scenario, the file remains on the local computer, while the delivery happens through the cloud—allowing Manus to coordinate across both environments.

This creates a unified workflow across:

The result is an AI agent that operates across systems, connecting tools and environments rather than being limited to a single interface.

Allowing an AI system to operate directly on a user’s local computer introduces new trust, security, and control considerations.

Because of this, Manus is designed to keep control firmly with the user.

Every action Manus executes on a local machine requires explicit user approval before execution. Users can choose to:

This allows users to balance automation with oversight, depending on the task and level of trust.

Manus also integrates with Projects, Agents, and Scheduled Tasks, enabling recurring workflows such as:

This approach allows users to automate routine work while retaining control over execution—keeping the human in the decision loop even as tasks become more autonomous.

The Manus Desktop application is available today for both macOS and Windows users.

To begin using the “My Computer” capability, users install the Manus Desktop app, connect it to their account, and grant access to selected local folders and permissions for execution.

Setup involves:

Once configured, Manus can operate across both cloud and local environments—bringing AI execution directly into real-world workflows.

Q: What has been announced with Manus and Meta?
A: Following Meta’s acquisition of Manus, the company has introduced a new capability called “My Computer,” delivered through its desktop application, which allows AI agents to operate directly on local computers.

Q: What’s new compared to previous AI assistants?
A: Unlike cloud-only AI tools, Manus’s “My Computer” capability allows agents to access local files, run applications, and execute tasks directly on a user’s machine.

Q: How does Manus interact with a computer?
A: Manus uses a command line interface (CLI), a text-based control system, to read, modify, and organize files, control applications, and run workflows across the system.

Q: Why does local execution matter for AI?
A: Most real work happens on personal machines. Local execution enables AI to automate tasks that cloud-based systems cannot access or control directly.

Q: Who benefits most from this capability?
A: Developers, small businesses, and knowledge workers who manage workflows across local files, applications, and cloud tools.

Q: Is it safe to let AI access your computer?
A: Manus requires explicit user approval for each action, allowing users to maintain control over AI execution on their machine.

AI systems are moving beyond interfaces and into execution environments, where they can directly control software, files, and workflows across a user’s digital workspace.

The key point: AI is no longer just assisting with tasks—it is performing them across real systems, reducing the need for manual interaction with software.

Who should care: Developers, small businesses, and knowledge workers—because they rely on fragmented tools, repetitive workflows, and manual processes that AI agents can now automate directly on their machines.

Why it matters now: This capability removes one of the biggest limitations of AI adoption—the inability to access and act on local environments where critical work happens. As AI gains the ability to operate across files, applications, and systems, it becomes more useful, more actionable, and harder for businesses to ignore.

What decision this affects: How quickly to integrate AI agents into core workflows—and which tasks should shift from manual execution to automated system-level operations to improve productivity.

In short: The real value of AI now lies in action, not just insight—and in systems that can operate seamlessly across cloud and local environments.

The future of AI won’t be defined by what it can say—it will be defined by what it can do, directly inside the systems you rely on every day.

Editor’s Note: This article was created by Alicia Shapiro, CMO of AiNews.com, with writing, image, and idea-generation support from ChatGPT, an AI assistant. However, the final perspective and editorial choices are solely Alicia Shapiro’s. Special thanks to ChatGPT for assistance with research and editorial support in crafting this article.