AI assistants are moving beyond answering questions.
Instead of simply generating text, code, or summaries, a new generation of AI agents is being designed to take actions, use websites, work with connected apps, remember context, and continue tasks without requiring constant instructions.
Muse AI is Meta's entry into this category.
Launched in September 2026, Muse is designed as a personal AI agent that can work toward goals, browse the web, use a dedicated computer environment, create documents and interactive outputs, connect with apps, and continue certain tasks in the background. Meta says Muse can even ask for approval before sensitive actions such as sending an email or making a purchase.
But Muse is also raising an important question:
How much access should you give an AI agent to your digital life?
Independent hands-on reviews have highlighted both the convenience of Muse and concerns about how much personal information an agent can potentially access when users connect services such as email, Instagram, and other accounts.
In this Muse AI review, we'll explain what Muse is, how it works, its most useful features, pricing and availability, real-world use cases, security architecture, privacy concerns, and what makes it different from a traditional AI chatbot.
Editor's note: Muse is a new product launched in September 2026. Availability, pricing, connectors, and features are still changing, so check Meta's official Muse Help Center before relying on a specific feature or subscription detail.
What Is Muse AI?
Muse AI is Meta's personal AI agent designed to take action on a user's behalf.
The fundamental difference between Muse and a traditional chatbot is agency.
A chatbot might answer:
"Find some good laptops under $1,000."
An AI agent can potentially go further by researching products, comparing options, opening websites, organizing the results, and—when supported and approved—helping complete the purchase.
Meta describes Muse as an agent that doesn't simply answer questions but actually works toward tasks and long-term goals. Users can give Muse a goal, and it can create a personalized plan and continue advancing the work.
Muse runs inside a dedicated cloud environment called Muse Secure VM. It has its own browser, file system, terminal, and computing environment, allowing it to perform tasks rather than simply generate responses.
How Does Muse AI Work?
Muse is built around a simple idea:
Tell it what you want accomplished, then let the agent handle the work.
For example, instead of sending five separate prompts, you could give Muse a broader goal such as:
"Research a topic, organize the important information, create a report, and remind me to review it tomorrow."
Muse can break a goal into steps, work on those steps, and continue working when appropriate.
Meta says Muse can:
- Browse the web
- Navigate websites
- Fill out forms
- Work with files
- Use a terminal
- Create documents
- Create PDFs
- Build web pages
- Create dashboards and trackers
- Connect with supported services
- Continue certain tasks in the background
- Ask for approval before sensitive actions
This makes Muse fundamentally different from a purely conversational AI.
Muse Secure VM: The Computer Behind the Agent
One of the most important technical parts of Muse is its Secure VM.
Meta says every Muse runs on its own dedicated computer in the cloud. The VM contains the agent and the user's data and credentials for connected services.
Muse also uses a separate security layer called Sentinel.
The idea is that Muse doesn't get unrestricted internet access. According to Meta, Sentinel evaluates outbound actions and can require permission before an action is allowed to proceed.
This architecture matters because an AI agent is fundamentally different from a normal chatbot.
A chatbot may produce a bad answer.
An agent with browser and account access could potentially perform the wrong action.
That's why permissions, approvals, auditing, and isolation become much more important.
WIRED reported that Meta's approval prompts are designed to reach the user directly rather than simply being interpreted by the AI model, partly to reduce risks such as prompt-injection attacks.
Muse AI's Most Important Features
1. Background Tasks
One of Muse's defining features is its ability to continue working after you stop actively interacting with it.
Meta says that for longer tasks, Muse can keep working after you close the app and return when something changes or when it needs your approval.
This changes the normal AI workflow.
Instead of:
Prompt → Answer → Finished
Muse is designed more like:
Goal → Plan → Work → Monitor → Follow up → Ask for approval → Complete
For example, a user could create a longer-running goal and allow Muse to monitor relevant information.
The Muse design team says the agent can work on a schedule and respond to relevant events while also handling new tasks in the main conversation.
2. Goals
Muse has a dedicated Goals concept for long-running objectives.
Rather than treating every prompt as an isolated request, Muse can maintain an ongoing goal and continue working toward it.
Examples might include:
- Planning a trip
- Organizing a project
- Tracking a recurring task
- Researching a topic
- Managing a personal routine
- Monitoring something online
The goal system is especially relevant to the broader shift from AI assistants to AI agents.
3. Activity Feed and Task History
One useful feature highlighted by hands-on testing is Muse's activity feed.
Lenny's Newsletter review specifically highlighted the activity feed and its task lineage, allowing the user to see what the agent was doing and follow its work.
This is valuable because autonomous agents can otherwise feel like black boxes.
When an agent performs multiple actions, users need a way to understand:
- What task is running
- What the agent has done
- Which tools it used
- What remains
- Where it needs approval
That transparency can make an agent easier to supervise.
4. Ideas
Muse also provides an Ideas feature that can suggest ways to use the agent.
During testing, The Verge noted examples such as product comparisons, finding forgotten subscriptions, and tracking future product releases.
This is useful for beginners because many people don't initially know what an AI agent can actually do.
Instead of starting with:
"What should I ask Muse?"
Users can get suggestions for possible workflows.
5. Persistent Memory
Muse can remember information across conversations.
Meta says Muse remembers what matters to the user and can use details mentioned previously to make suggestions or take relevant actions. Users can also tell Muse to forget information.
For example, you could tell Muse:
"Remember that I prefer budget-friendly hotels."
Later, that preference can become part of a travel-planning task.
Persistent memory can make an AI agent much more useful, but it also increases the importance of privacy controls because the agent can build a more detailed picture of the user over time.
6. Muse Artifacts
Muse isn't limited to text responses.
It can create Artifacts such as:
- Documents
- PDFs
- Web pages
- Trackers
- Interactive study guides
- Dashboards
- Other structured outputs
The Muse design team provides examples including spending trackers, interactive study guides, and dashboards.
This is especially useful for professionals.
For example:
"Analyze these expenses and create an interactive spending tracker."
Instead of returning a paragraph, Muse can create something designed to be used.
Lenny's Newsletter also highlighted Muse's ability to generate a personalized family PDF during hands-on testing.
7. Browser Automation
Muse has access to a full web browser.
Meta says the agent can:
- Search websites
- Navigate pages
- Fill forms
- Complete transactions
- Research products
- Book travel
- Shop online
This is where the distinction between an AI assistant and an AI agent becomes very clear.
Instead of telling you how to complete a task, Muse can potentially complete some of the browser-based work itself.
However, browser automation isn't perfect.
Lenny's hands-on testing found that Muse performed differently across shopping tasks: one shopping test did not go particularly well, while another transaction worked better.
That is a useful reminder that agentic capability doesn't mean guaranteed execution.
8. Shopping and Payments
Muse is designed to assist with online shopping.
Meta says Muse can use Link by Stripe for checkout, with a one-time-use card designed to keep the user's real card details hidden from the merchant interaction. Meta also announced Shop Pay and additional payment integrations as part of its broader Muse ecosystem.
Muse can potentially:
- Research products
- Compare options
- Find deals
- Ask for confirmation
- Proceed with supported checkout workflows
The human approval step is particularly important here.
You don't want an autonomous agent spending money without knowing exactly what it is buying.
9. Connectors and App Integrations
Muse becomes considerably more useful when it can work with services users already use.
Meta launched Muse with multiple partners and later announced additional connectors at Connect 2026.
These include services such as:
- Walmart
- Best Buy
- Sephora
- Ulta
- Wayfair
- Expedia
- Instacart
- Notion
- Granola
- GitHub
- Box
Meta also announced additional payment options and other integrations.
For developers, the GitHub connector could make Muse more relevant for software-related workflows.
For professionals, Notion and Box could help with information and document management.
For shoppers and travelers, commerce and travel connectors expand the number of real-world tasks Muse can potentially handle.
The available connectors are still evolving, so users should check the current Muse Help Center for what is actually supported in their region.
10. Muse on AI Glasses
Meta is also taking Muse beyond the phone and browser.
At Connect 2026, Meta announced that Muse is coming to its AI glasses.
The planned experience allows users to interact with Muse hands-free and potentially have the agent act based on what they're looking at.
For example, Meta demonstrated use cases involving:
- Products on shelves
- Flyers
- Lists
- Objects in the user's environment
This could eventually make AI agents more contextual.
Instead of explaining:
"I'm looking at this product. What is it?"
A user could simply ask Muse about what they are seeing.
Meta also announced a voice mode designed for longer conversations while Muse continues working in the background.
Muse AI for Developers
Muse isn't positioned specifically as a coding agent, but developers may still find its computer environment interesting.
The Muse design team says the agent has:
- A file system
- A terminal
- A web browser
- The ability to write code
- The ability to build tools required for tasks
That means Muse can potentially help with broader technical workflows such as:
- Researching documentation
- Working with project files
- Analyzing information
- Building small utilities
- Creating dashboards
- Performing browser-based development tasks
- Working with GitHub through supported integrations
However, this doesn't mean Muse automatically replaces specialized coding agents.
Tools such as Claude Code, Codex, Cursor, and other developer-focused agents are designed specifically around software development.
Muse's broader focus is general personal agency.
Muse AI for Freelancers and Content Creators
Muse can also fit workflows outside software development.
For freelancers and content creators, possible use cases include:
Content research
Ask Muse to research a topic, organize sources, and create a research document.
Competitor research
Give Muse a competitor-research goal and let it browse websites and organize findings.
Email assistance
Muse can read connected email and help draft responses where permissions allow.
Project organization
Use Goals, reminders, documents, and connected services to keep track of ongoing work.
Research reports
Ask Muse to collect information and turn it into a PDF or structured report.
The important difference is that Muse can potentially handle the workflow, not just generate the words.
Muse AI Privacy: What Should You Know?
This is probably the most important part of any Muse AI review.
The more useful an AI agent becomes, the more access it may need.
Muse can potentially work with:
- Calendars
- Files
- Connected apps
- Web services
- Shopping accounts
- Personal preferences
- Social-media-related information
Meta says users choose which apps Muse connects to and how much access it receives. For example, email permissions can determine whether Muse can only read messages or also send messages on the user's behalf.
Users can also disconnect services and manage access.
But independent testing has shown why these permissions deserve careful attention.
The Verge reported that when Instagram and Facebook were connected, Muse was able to provide detailed interests that the tester said were not presented at the same level of detail in the normal Instagram interface. Meta said Muse can pull and infer interests from Instagram activity when connected, and users who don't want this can disconnect Instagram from Muse through Accounts Center.
TechRadar similarly described a trade-off: Muse was useful for handling tasks such as shopping and email, but the amount of personal access required made the reviewer uncomfortable.
So the practical lesson is:
Don't connect everything immediately.
Start with low-risk tasks and only add permissions when you understand what the agent can access and do.
Muse AI Security: Secure VM, Sentinel and Reported Vulnerabilities
Meta has built several security controls into Muse.
According to Meta:
- Muse runs inside a dedicated cloud computer.
- A separate Sentinel system controls external access.
- Credentials are stored securely.
- Muse does not directly see passwords or payment details.
- Sensitive actions can require approval.
- Users receive an audit trail.
- Users control connected-app permissions.
- Users can disconnect services.
- Users can opt out of interactions being used to train Meta's AI models.
Meta also announced Confidential VM, designed to encrypt the entire VM using a key controlled by the user. Meta says the goal is that even Meta itself would not be able to access the contents of that VM.
However, security research has also identified concerns.
Ars Technica reported a serious vulnerability affecting Muse's macOS implementation and described a possible attack involving ClickFix-style social engineering. The report also noted that Amazon blocked Muse from shopping on its platform, citing its conditions of use. These are reported findings and platform decisions, not evidence that every Muse user is compromised.
WIRED also reported that Meta had added Muse to its public bug bounty program, with payouts of up to $300,000 for qualifying vulnerabilities, including up to $130,000 for certain successful prompt-injection attacks.
For users, the takeaway is simple:
AI agents need a much higher security standard than ordinary chatbots because they can act on your behalf.
Is Muse AI Safe to Use?
There isn't a simple yes-or-no answer.
Muse includes significant security protections, including Secure VM isolation, Sentinel controls, permission management, approval workflows, credential protection, and auditing.
At the same time, independent researchers and reviewers have raised concerns about privacy, account access, social engineering, and vulnerabilities.
Therefore, users should treat Muse like a powerful digital assistant—not like a harmless chatbot.
A sensible approach is:
- Start with low-risk tasks.
- Don't connect every account immediately.
- Review permissions carefully.
- Keep approval requirements enabled for sensitive actions.
- Check the activity history.
- Review purchases before confirming them.
- Disconnect services you no longer need.
- Keep the application and operating system updated.
- Avoid giving an AI agent unnecessary access to sensitive information.
Muse AI Pricing
Meta says Muse is free for most basic needs and offers subscription plans for users who want more.
Current third-party reporting has described paid tiers for heavier users, including a $20/month Power plan and $100/month Maximum plan, but pricing and availability can change as Meta continues rolling out the product.
For that reason, users should verify the price shown in their own Muse account before subscribing.
Muse AI Availability
Muse is not globally available yet.
Meta initially announced the rollout in the United States across iOS, Android, and the Muse website.
Meta's current Help Center states that the Muse app and website are not available everywhere, and that some features may not yet be available in certain areas.
TechCrunch reported on September 25 that Muse was then available in the United States and Canada, while Meta was continuing to expand the product and its integrations.
Therefore, availability should be checked directly through Meta rather than assumed based on another user's location.
Muse AI vs ChatGPT
Muse and traditional AI assistants overlap, but their product philosophy is different.
| Feature | Muse AI | Traditional AI Chatbot |
|---|---|---|
| Conversational AI | Yes | Yes |
| Web research | Yes | Often |
| Browser actions | Yes | Depends on product/mode |
| Background work | Yes | Varies |
| Persistent memory | Yes | Varies |
| Long-running goals | Yes | Varies |
| Connected apps | Expanding | Depends on integrations |
| Artifacts | Yes | Depends on tool |
| Human approval | Yes for sensitive actions | Depends on task |
| Personal-agent focus | Core design | Varies |
The key difference isn't simply intelligence.
It's what the system is designed to do after you give it a goal.
A chatbot generally helps you generate or understand information.
Muse is designed to take that information and continue into the execution stage.
What Are the Best Muse AI Use Cases?
Here are practical ways users can experiment with Muse.
1. Product Research
Ask Muse to compare products, prices, features, and availability.
2. Travel Planning
Give Muse a destination and preferences and ask it to research options and build an itinerary.
3. Email Organization
Allow limited email access and ask Muse to identify important messages or prepare drafts for review.
4. Content Research
Ask Muse to research a topic and create a structured report.
5. Personal Projects
Use Goals and reminders to manage ongoing projects.
6. Shopping
Let Muse research products and bring you options before you approve a purchase.
7. Document Creation
Ask Muse to turn research into a PDF, webpage, dashboard, or other Artifact.
8. Developer Research
Use the browser, terminal, files, and supported GitHub integration for broader technical workflows.
What Are the Limitations of Muse AI?
Muse is powerful, but it isn't perfect.
It's still new
Muse launched in September 2026, so the ecosystem is still developing.
Availability varies
Not every country or user has access to every feature.
Connectors are evolving
Meta continues adding new services, so today's integrations may not represent the final product.
Agents can make mistakes
A more autonomous system can make a wrong decision or misunderstand a task.
Browser automation isn't perfect
Hands-on testing has shown mixed results across different browser-based tasks.
Privacy requires attention
The more personal services you connect, the more information the agent can potentially use.
Security is still an active area
The reported macOS vulnerability demonstrates why AI-agent security remains an evolving field.
What Makes Muse Different From Other AI Agents?
Muse's biggest differentiator is its attempt to combine agent capability with consumer-friendly design.
Lenny's Newsletter's hands-on review highlighted the product's onboarding, activity feed, goals, ideas, library, artifacts, permissions, and overall consumer UX.
The Muse design team also says the product intentionally avoids a strict turn-by-turn interaction model.
Users can send multiple tasks, interrupt the agent, maintain side chats, and continue a persistent main conversation.
That makes Muse feel less like:
"Ask → Wait → Answer"
and more like:
"Tell → Delegate → Supervise."
That distinction is important when evaluating personal AI agents.
Final Verdict
Muse AI is an important example of the transition from AI chatbots to AI agents.
Its core capabilities go beyond text generation. Muse can browse websites, use a dedicated computer, work with files and a terminal, create artifacts, remember information, manage goals, connect with external services, and continue certain work in the background.
Its ecosystem is also expanding quickly, with connectors for services such as GitHub, Notion, Box, shopping platforms, travel services, and other tools. Meta is also bringing Muse to AI glasses, where the agent will eventually be able to work with what users are looking at.
But the same capabilities that make Muse useful create new risks.
Giving an AI agent access to your email, accounts, files, shopping, and personal information is fundamentally different from asking a chatbot to write an article.
That means permissions, approval controls, activity history, privacy settings, and security updates matter just as much as the AI's capabilities.
For someone interested in AI automation, productivity, research, content creation, software development, or personal agents, Muse is a product worth understanding and testing carefully.
The future of AI may not simply be about asking:
"What can AI tell me?"
Increasingly, the question is:
"What can AI actually do for me?"
Muse is Meta's attempt to answer that question.
Frequently Asked Questions
What is Muse AI?
Muse AI is Meta's personal AI agent designed to perform tasks, manage goals, browse the web, use connected services, create artifacts, and continue certain work in the background.
Is Muse AI free?
Meta says Muse is free for most basic needs, with paid subscription options for users who need more capacity.
Can Muse AI browse the internet?
Yes. Muse has its own browser and can search, navigate websites, fill forms, and perform supported transactions.
Can Muse AI work in the background?
Yes. Background task execution is one of Muse's core capabilities. Muse can continue working on longer tasks and return when something changes or approval is needed.
Does Muse AI have memory?
Yes. Muse can remember information that matters to the user and use it in future conversations and tasks. Users can also ask Muse to forget information.
Can Muse AI send emails?
Muse can work with connected email services and can prepare or send messages depending on the permissions granted by the user. Meta says sensitive actions such as sending an email can require user approval.
Can Muse AI make purchases?
Muse can assist with supported purchases and checkout workflows. Meta says Muse supports Link by Stripe and has announced additional payment and commerce integrations.
Is Muse AI available worldwide?
No. Meta's Help Center says Muse is not yet available everywhere and some features can vary by region.
Can Muse AI work with GitHub?
GitHub was among the integrations Meta announced for Muse at Connect 2026. Availability can depend on the user's region and current connector rollout.
Is Muse AI coming to smart glasses?
Yes. Meta announced that Muse is coming to its AI glasses, with planned capabilities that allow Muse to understand and act on what the user is looking at.
Is Muse AI safe?
Muse includes security features such as Secure VM isolation, Sentinel controls, permission management, approval workflows, credential protection, and activity auditing. However, independent researchers have also reported privacy concerns and security vulnerabilities, so users should carefully manage permissions and keep the software updated.
Who should try Muse AI?
Muse is particularly relevant to people interested in AI agents, automation, research, productivity, content workflows, online tasks, personal organization, and broader agentic AI.