Let AI spend for you: how long can the personal Agent wave fueled by Meta Muse last

Wen | Baobian, Author | Zhang Jingwei, Editor | Xing Yun

Since its launch a month and a half ago, Meta's agent Muse has shown astonishing user growth. The latest data from Sensor Tower shows that since Muse launched in September, cumulative downloads have reached 10.9 million, of which 10.2 million were in the United States.

In Meta's just-released Q3 financial report, it said that about 25% of Muse users use it every day, more than 25% of users shop through Muse, and the average order value exceeds $200. Meta's stock closed higher on the day the financial report was released.

Muse's popularity has once again raised the market's attention to personal AI agents, and major domestic companies are also densely laying out their plans. According to media reports, ByteDance is developing a personal assistant called "Xiaodou"; the Tencent Cloud Lightweight Cloud team has launched a cloud-based Agent hosting product LightVela; Qwen also announced at the September Yunqi Conference its plan to build a Personal Agent.

In addition to major domestic and foreign companies, entrepreneurs are also eager to act. On October 21, Today AI, which focuses on AI personal assistants, completed a new round of financing worth $200 million, with investors including Tencent, Sequoia, IDG, Ant, Transsion and other institutions.

After chat, coding, and office work, the wind of personal Agents has risen again. How is it different from AI's previous functions, and what do manufacturers need to do to turn personal assistants into a good business?

1. What is different about personal AI assistants?

At Meta's Q3 earnings call recently, Muse became the absolute focus of attention. Zuckerberg mentioned Muse more than fifty times in his opening remarks, while Facebook and Instagram were mentioned fewer than 20 times in total.

Payment service provider Plaid told Meta that it had never seen such high activity in any other service before. In the first week of launch, Meta even had to ask online payment company Stripe to urgently raise its credit limit because transaction volume exceeded everyone's expectations.

Later, someone saved $1,250 on a car purchase with Muse, someone canceled a book subscription his wife had forgotten to cancel, and someone dug out a $200 gift card from deep within an account.

This kind of extra spending in daily life is essentially a "hassle tax": people get lost in complicated information, making it difficult to find the most valuable information and make the most efficient decisions. And in this, AI has room to create value, just as it does in enterprises. AI can reorganize your personal life and take charge of things you do not have the energy to manage or do not want to manage, giving you a more convenient and efficient life.

However, the value of personal agents goes far beyond this. It can also be a "personal growth coach" or "life recorder," and even become an important tool for personal entrepreneurship and creativity.

Today AI, released on the same day as Muse, is the same. Baobian registered for Today. After authorizing travel and email information to it, Today AI generated a relatively accurate personal summary and some daily management suggestions.

This way of using AI is very natural. In fact, when AI companion toys became popular, they carried this expectation from users. According to Baobian, at some domestic exhibitions previously, elderly people and enterprise managers asked manufacturers whether companion toys could take on the responsibilities of a personal assistant.

But companion toys do not have access to payments, calendars, and email. A real personal assistant needs to live in the digital world and operate real services on behalf of users. This is also why major companies moved first: they happen to hold real-world interfaces such as account systems, payment channels, and content ecosystems.

Muse's appearance is not the first time Meta has set its sights on agents. On December 29, 2025, Meta announced the acquisition of Manus, which develops agents. About four months later, after a foreign investment security review, the National Development and Reform Commission prohibited the acquisition and required the transaction to be revoked. In August 2026, Manus announced the resumption of independent operations. Meta subsequently launched its self-developed personal agent Muse in September.

From the OpenClaw craze at the beginning of the year to the autumn of 2026, agents have gradually penetrated from work scenarios into life scenarios. When acquired by Meta, Manus mainly met the needs of work scenarios. But now, from Meta and Tencent to Today AI and Manus, everyone has set their sights on personal life/work assistants.

Three weeks after Muse was released, OpenAI also released its own personal Agent Dots, focusing on all-weather task execution and integration into workflows.

In this exploration, on one hand, major companies develop personal assistants themselves; on the other hand, there is investment involving personal Agents. In addition to Today AI, another financing star is Manus, which completed more than $500 million in financing after becoming independent, also backed by Tencent.

2. OpenClaw fades, butlers enter: the threshold is lower, but the walls remain

The major companies' persistent layout in personal agents itself also reflects a certain current state of AI applications. Among the main battlegrounds for AI applications in 2026, coding was the first to be proven, with the strongest willingness of users to pay, but limited by usage scenarios, the user scale has a natural upper limit.

JetBrains' 2026 Developer Ecosystem Survey shows that 90% of professional developers already use AI coding Agents at work every week, and 68% use them every day. AI coding tools have become the daily working method of mainstream developers.

Office work is currently the most competitive, with Tencent WorkBuddy, Alibaba Qwen Office, ByteDance Doubao Work, and Kimi Work rushing in, and free quotas continuously increasing. AI applications need new usage scenarios to prove their value.

From the perspective of AI capabilities, the time is ripe for making personal assistants. The core features of personal assistants lie in proactive service and emphasis on user memory. The Agentic capabilities of mainstream models can meet the needs of various tool calls, and AI memory and context understanding are also sufficient for daily C-end interactions.

Beyond capability, the usage barrier is a problem that needs to be solved. Although today's Agents, compared with the early OpenClaw, no longer require a series of cumbersome configuration steps, Agents are mainly adapted to work scenarios such as programming and office work, and still involve a "problem-solving" interaction in which the user issues a task—the Agent completes the task—the user gives feedback—the Agent revises.

If an Agent is to intervene in the management of daily life, for earlier products one needed to find suitable Skills, build suitable programs/dashboards, and repeatedly converse with the AI to adjust. A personal Agent with stable programs and considerate features is much friendlier, and is plug-and-play.

Personal Agents also have to face an old problem, namely the many barriers of internet products.

Muse's growth stems to some extent from the high fragmentation and cumbersome procedures of US internet services. In China, where the mobile internet is controlled by big companies and is more convenient, third-party personal Agents may face the problem of being ill-adapted to local conditions.

Doubao Phone, which has functions similar to a personal Agent, ran into difficulties: 155 apps, including WeChat and Taobao, refused to allow it access. Even Muse stands before this same barrier: Amazon banned Muse from calling its shopping platform's permissions.

Domestically, various companies have already set out clear "ecosystem plays." Besides ByteDance's Xiaodou and Tencent's LightVela, which are backed by the Douyin/WeChat ecosystems, Ant's Lingguang also began in its October new version to support calling apps within ecosystems such as DingTalk, to handle tasks that require continuous follow-up.

It can be expected that domestic personal Agents will most likely form several walled cities centered on big companies.

For startups, wanting to build personal intelligent agents will probably require becoming part of a big company's ecosystem. While Today AI accepted investment from Ant and Tencent, it also turned WeChat and DingTalk into Agent entry points through the Channels feature.

3. Three unsolved problems: user stickiness, commercialization, and security

Besides long-term ecosystem building, the personal assistant business also needs to prove itself with short-term data, such as the retention problem.

Sensor Tower data shows that although Muse's next-day retention is as high as 73.3%, its 7th-day retention rate quickly drops to just over 30%, and by the 14th day Muse has only 22.5% left.

Even so, Muse is still higher than the average 14-day retention rate of similar apps, which is less than 20%. The overall low retention also shows that personal assistants have not yet cultivated high-frequency demand among users.

Another problem is the problem of making money.

Payment mainly provides more usage, among which the Power tier is $20 per month for 500 million Muse tokens per week, and the Maximum tier is $100 per month for 3 billion tokens per week.

Zuckerberg said at the earnings call that Meta will ultimately charge a "small fee" for transactions facilitated by Muse, and it is expected that this fee will be borne by the enterprise side.

He also said he plans to increase Muse's computing efficiency by 10 times within a year, so that it can achieve profitability after revenue scale expands.

Domestic products are still in the stage of free customer acquisition, and the business model is undetermined, but it is also very likely that transactions, usage, or advertising will be the main revenue models.

More importantly, Agents entering life may bring security risks. macOS security expert Patrick Wardle disclosed a zero-day vulnerability in the Meta Muse macOS app; attackers could exploit the AI's broad permissions to hijack users' devices and transcribe sensitive data to their own servers. He succeeded in taking photos through Muse and writing malicious files to disk, and in many cases users did not notice these operations.

Meta subsequently released a hotfix patch, but argued that this was a local privilege escalation vulnerability that required an attacker to already be running malicious code on the user's machine, so the actual risk was low.

At the same time, after Muse launched, some users would hand tasks such as calling to buy insurance/book tickets to the Agent, but because the other party heard it was AI and hung up directly, Meta once proposed a laughable "human concierge" plan, that is, the Agent would transfer the user's calling task to Meta's human customer service, which means the user's privacy would be known to a third person.

Personal Agents may be the closest AI has come to ordinary people's lives. Its uniqueness lies in the fact that we have to entrust our work and life to a steward with no physical form who learns while doing. How to let everyone entrust it with peace of mind tests all personal Agents.