Claude Duet: Anthropic's AI Agent for Professionals Takes On Its Rivals

Anthropic has announced its AI agent Claude Duet as a "research preview." The product targets professionals and small business owners. It is positioned as a direct rival to Meta's Muse and OpenAI's Dots. That three major companies are releasing similar products at the same time shows that the shift from the chatbot era to the era of always-on assistants is now a tangible market.

What happened?

Claude Duet is offered as a standalone app on iOS and Android. It can also be accessed on the web from within Claude. Anthropic has released the product not as a full version but as a preview. That label generally means features and limits may change and bugs are to be expected.

Why does it matter?

The first large language model products were built on a single pattern: the user types, the model replies, the conversation ends. In this setup, AI existed only when it was called upon. The agent approach flips that. An agent can keep watching emails, the calendar and documents even after the user closes the app, and it can prepare drafts and send reminders when needed. The experience Anthropic previously gained with agent tools for developers, especially agents that write code, seems to have laid the groundwork for bringing this idea to consumers and the business world.

The three companies entering the arena at the same time may not be a coincidence. Each arrives with a different advantage. Meta has a very broad social distribution network. OpenAI has the largest consumer chat user base. Anthropic, historically, is strong among enterprise customers and developers. Duet's focus on "professionals and small businesses" looks like a natural extension of that background. Rather than fighting for the general consumer, it goes after a segment that wants to get its work in order and is more willing to pay.

The real sticking point is trust. An agent running in the background has access to your email and calendar even when the app is not open. That is a very different risk profile from asking a question in a chat window. A reply sent to the wrong person, a meeting accepted by mistake, or a malicious instruction buried in a message in the inbox (prompt injection) can all have consequences. The industry has not yet fully solved this type of attack.

Who is affected, and how?

For a small business owner, the appeal is clear: someone who cannot afford an executive assistant can hand off recurring tasks such as appointment coordination, invoice tracking and customer correspondence. But that same person has no team to fix things when a mistake is made. That is why approval mechanisms, meaning which tasks the agent can perform without asking, will determine the real quality of the product.

Details of the rival products in the table are limited to the information in the source. The columns therefore reflect general positioning and do not offer an exact feature comparison.

On the enterprise side, data governance comes to the fore. Before opening their employees' email and calendar data to a third-party agent, companies will ask questions such as retention periods, whether the data is used for training, and audit logs. Anthropic's emphasis on safety could be a plus in enterprise sales. But that is not a promise; it is a claim that has yet to be proven.

What's next?

Three things are worth watching. First, the move from preview to general availability: which permissions will be the default, and which actions will the agent take without approval? Second, pricing. An always-on agent means constant processing costs, which could strain subscription models. Third, third-party integrations: the more tools an agent connects to, the more useful it becomes, but the larger its attack surface grows too.

Here is my assessment: Duet's real test will be reliability, not model intelligence. The race becomes decisive when users are ready to hand their email over to their agent. Anthropic's choice of a narrow, clearly defined audience looks like the most defensible strategy among the three rivals. Still, the promise of a product in preview remains just a promise until it is proven under real workloads. For more context, see Anthropic's official website.