AI agents are moving from experiments for enthusiasts toward products aimed at everyday consumers and businesses. Meta’s Muse and OpenAI’s Dots promise to take on multi-step tasks with less supervision, but using them may mean sharing access to personal information. Their appeal depends on whether the time saved is worth the trust they ask users to place in them.
From experiments to personal assistants
Interest in agents has been building for years. In 2022, tech leaders described the period as a year of ideation. They called 2023 the year of deployment, when companies began trying systems and learning from failures. Agents remained disappointing through 2024 and 2025, according to The Verge’s discussion.
The newer pitch is more practical: an agent that can stay available and carry out a task without requiring a person to guide every step. A user might ask for a flight booking or a dinner reservation, then expect the agent to handle the process and return with the result. Other examples include buying gifts and sorting through an inbox.
That is a different promise from a tool that only answers a question or performs one isolated action. An agent is meant to manage a sequence of steps, using information it has about the user to make decisions along the way.
How the agent model works
The discussion describes an agent as an AI model paired with a system that lets it use a computer. That arrangement gives the model a way to act on tasks, rather than simply generate a response. OpenClaw helped bring attention to this approach, and both Muse and Dots are described as following its lineage.
For an agent to complete tasks with less back-and-forth, it needs context. Booking travel, for example, could involve preferences or account details that a person would otherwise provide each time. The selling point is that the agent can keep track of relevant information and carry a task through several stages.
The same access that makes the tool useful also raises the stakes. OpenClaw ran on a user’s own computer and network, often with a browser that had broad access to personal data. The article notes that this setup came with privacy and security problems. Consumer products may be easier to use, but the underlying question remains: what information and access should an agent have?
Muse and Dots take different paths
Meta and OpenAI are presenting their products as distinct, though the discussion describes them as broadly similar always-on assistants. Both use animated mascots to make the products approachable. Dots also reaches into work tasks, with specialist options for marketing, legal work, and accounting.
Muse is free, while Dots is not. That difference may matter for people deciding whether to try an agent, and Meta could benefit from its strength in making and distributing consumer products. The Verge discussion also points out that Meta does not yet have a frontier model of its own, suggesting that consumer reach may be an important part of its position.
Making an agent available is only one part of the challenge. People need to see that it can handle useful tasks, and they need a reason to trust it with the information those tasks require. The article describes this as a competitive question as well as a product question: companies are trying to show what agents can do today while users weigh the privacy and security costs.
The trust test for always-on AI
Agents could reduce the need to open separate apps or keep a phone in hand for each step. But the more they are expected to do independently, the more personal context they may need. That can include an email inbox, credit card information, or files stored on a computer.
Convenience alone may not persuade people to hand over that access. Users will have to judge whether an agent’s capabilities are dependable enough for the task and whether sharing the necessary data feels acceptable. The discussion leaves that question open: always-on assistants may be part of computing’s future, but it is not clear that most people want to provide the information needed to make them work.