Muse

Understanding Personal AI Agents

In the evolving landscape of artificial intelligence, a personal AI agent represents a shift from simple conversational tools to active digital assistants. Unlike a standard chatbot that waits for a prompt to generate text, an agent is designed to take action. Think of it as a digital intern: you provide the goal, and the agent figures out the steps, navigates the necessary software, and completes the work for you. Muse is built to function as this type of persistent, autonomous helper, powered by Muse Spark, a model engineered for real-world agentic work—the ability to interact with the digital world to achieve specific outcomes.

The Secure VM Architecture

To manage the complexity of performing tasks across different apps, Muse operates within a Muse Secure VM. A virtual machine (VM) is essentially a computer within a computer; it is an isolated, software-based environment that mimics a physical machine. Think of the Secure VM like a secure, soundproofed office suite inside a large corporate building. The agent works inside this private office, using its own tools and browser, ensuring that its activities remain contained and do not spill over into your personal device’s main operating system.

The Sentinel Security Model

Security is a primary concern when an AI is granted the ability to perform actions like sending emails or making purchases. To address this, Muse utilizes a Sentinel agent. Sentinel acts as a gatekeeper, controlling all network egress—the data leaving the VM—and connector actions. Nothing the agent does reaches the internet unless Sentinel explicitly approves it. You can think of Sentinel as a strict security guard stationed at the only exit of the agent’s office. Even if the agent wants to send a document or access a website, it must present its request to the guard, who verifies the action against safety protocols before allowing it to pass through the door.

Furthermore, the system employs credential injection via a service called authd. The agent itself never handles actual passwords or payment tokens. Instead, it uses surrogate tokens minted by authd. When a task requires authentication, Sentinel performs just-in-time credential insertion at the network boundary, replacing the surrogate with the real credential only at the moment of egress. Additionally, eBPF kernel monitoring—a technology that allows for deep, low-level observation of operating system activity—tracks data flows to identify and revoke permissions if untrusted content is detected. To further protect user accounts, connectors are designed to automatically filter out sensitive items such as one-time tokens, password reset links, and login magic links from email.

Key Capabilities and Persistent Memory

Muse is designed to handle a wide range of autonomous tasks. It can send emails, book travel, fill out forms, browse the web, negotiate on a user’s behalf, make purchases with approval, schedule appointments, generate images, and create documents. Because it features background execution, the agent continues to work even after the user closes the application, returning only when a task is complete or when it requires human approval.

Perhaps most distinct is its persistent memory. Muse remembers details mentioned once, allowing it to make unprompted suggestions. Through cross-app integration, Muse uses connectors to interact with services like Gmail, Google Calendar, Instagram, Facebook, Ticketmaster, OpenTable, Spotify, Apple Health, Peloton, Plaid, and Function Health. If a service lacks a public API, Muse can even drive websites directly via browser automation.

Distinguishing Muse from Other AI

It is helpful to distinguish Muse from other familiar AI technologies:

• Vs. Chatbots: While chatbots are primarily conversational interfaces, Muse acts autonomously, works in the background, and executes multi-step tasks.
• Vs. Siri/Apple Intelligence: Siri is largely integrated at the system level on a user’s device. In contrast, Muse runs in a cloud-based VM, allowing for broader agentic capabilities that are not limited by the constraints of on-device processing.
• Vs. ChatGPT: While ChatGPT is centered on a conversational interface, Muse is designed as a persistent personal agent with deep OS and application integration via its connector ecosystem.

Availability and Pricing

At launch, Muse was made available across major mobile and web platforms, with access managed through standard social media authentication. The platform maintains a tiered service model, offering a free entry point alongside multiple paid subscription levels to accommodate different usage needs.

Privacy and Future Developments

Meta has stated that conversations and VM data are not shared with its advertising systems. Looking ahead, the company plans to introduce a Confidential VM. This will involve encrypting the entire VM with a user-held key inside a trusted execution environment, ensuring that even Meta cannot access the user’s data. To maintain high security standards, Meta also operates a bug bounty program, offering rewards of up to $300,000 for valid security reports, including those related to prompt injection.