Meta enters productivity assistant territory with Muse, an AI-powered agent designed to carry out online tasks on the user's behalf. The stated ambition is to lighten the load of chores that fill the digital day: sorting through email, planning a trip, searching for products, and making online purchases. A hands-on test published by The Verge suggests the system is already capable of completing some concrete tasks. At the same time, it clearly shows the price of this delegation: Muse must be granted access to accounts that hold a very large part of its users' daily lives.
Its defining feature is not a simple chat interface offering instructions. Muse operates via a virtual computer in the cloud, allowing it to navigate external services and perform actions directly within website interfaces once granted the necessary permissions. It is the difference between asking an assistant how to clean up a Gmail inbox and entrusting it with the task of reading messages, sorting through them, and deleting them. It is also what makes these tools more compelling than standard generative features, yet far more sensitive in terms of security, control, and privacy.
When the agent enters the inbox
In the test, one of the first tasks assigned to Muse was an instruction to scan a Gmail inbox and delete unnecessary messages. To do so, it was necessary to connect a Google account and authorize the assistant to access, read, and delete emails. The connection process was not seamless on a smartphone: the Google sign-in screen repeatedly looped back to the Muse website instead of completing the step in the app. The issue was bypassed by switching to a laptop.
Once connected, the agent deleted thousands of promotional emails and updates. It is a significant result because it goes beyond flashy demos or text generation: inbox cleaning is a tedious, frequent task with an easily verifiable outcome. In this case, Muse saved real time. Yet the very effectiveness of the operation highlights the breadth of permission required. A system capable of discerning what to delete must be able to see the email; a system authorized to delete messages can also make an error with non-trivial consequences.
For Meta, the issue is inevitably more sensitive than for other software vendors. The company claims to have designed Muse so that it exchanges with third-party applications only the data necessary to make them work for the user, and maintains that it does not share information with advertisers. These are significant commitments, but they do not eliminate the need to understand precisely what data passes through the service's infrastructure, how long it is retained, and what options exist for revoking or managing permissions. For a product that requests access to emails, purchases, and personal preferences, operational transparency matters just as much as the quality of its responses.
From ordering on Amazon to autonomous initiatives
The second step of the test involved Amazon. After linking the account, Muse received a specific request: choose workout tank tops matching the specified size, style, and colors. Here, an agentic behavior emerged that was more interesting than mere literal execution. Before completing the order, the system detected the presence of other items in the cart and asked whether they should be removed. Once purchase confirmation was received, it bought only the requested garments.
That intervention signals a clear direction: Muse does not merely fill in fields, but attempts to interpret the context of the session and pause when facing ambiguity that could alter the outcome. It is a best practice in a scenario where the difference between a helpful automated action and a blunder can be very slim. The agent did not unilaterally decide to clear the cart, nor did it add products; it asked for guidance before proceeding.
Yet a structural tension remains. The more an assistant is capable of acting without manual steps, the more it knows about the user's habits and details: pending purchases, history, sizes, implicit budgets, received messages, and connected services. In the case of Muse, the sense of invasiveness described in the test also stems from the system's ability to infer specific interests associated with the Instagram account. For some, this personalization may seem convenient; for others, it will be reason enough not to link their profiles.
A product broader than email and shopping
Muse is not limited to tasks on external services. Meta also presents it as a tool capable of creating AI podcasts, images, and videos, as well as web pages or interactive documents dubbed “artifacts”. This combination brings the product closer to the category of AI-assisted workspaces, where content creation, research, and automation coexist within the same interface.
During testing, however, the boundaries of its creative capabilities also emerged. Muse refused requests for images depicting characters easily traceable to well-known intellectual property, such as a cartoon mouse with red shorts or a character with a red cap and blue overalls. The refusal points to the enforcement of content safeguards, although the reported experience does not allow for broad conclusions about the scope or consistency of its generation policies.
The decision to bundle disparate features into Muse is significant for Meta. The company built much of its relationship with users on social networks, entertainment, and communication; an agent that manages email, shopping carts, and documents attempts instead to shift that relationship toward utilitarian, high-value daily tasks. Offering a chatbot is not enough: users must be convinced to grant it access and trust its steps before they become irreversible.
The decisive test will be user control
The Gmail and Amazon use cases paint a picture far less abstract than many presentations on agentic AI. Muse can work, at least for well-defined tasks and with specific instructions. It can also run into mundane yet crucial friction, such as a malfunctioning mobile login. Above all, it confronts the user with a choice that goes beyond model accuracy: how much control are they willing to surrender in exchange for saved minutes?
For Meta, the game will not be decided by the ability to delete newsletters or select a tank top. Those are features that other assistants will increasingly offer. What will make the difference are the mechanisms through which Muse bounds actions, signals what it is about to do, manages permissions, and allows users to interrupt or correct a task. The most useful agent is the one that reduces effort without turning every connected account into an opaque zone.
The test reported by The Verge therefore leaves two realities that are simultaneously true: Muse is capable of completing online tasks with immediate utility, and this very capability makes the product harder to adopt lightly. Meta will have to prove that its data processing guarantees are not merely statements of principle, but understandable and verifiable tools for those who decide to entrust their digital lives to its assistant.
