Muse AI: What it is, how to use it, and what it can do16 min read

Muse AI is Meta’s personal AI agent, designed to do tasks for you rather than just answer questions. You can ask it to research a topic, organize a project, manage reminders, draft documents, interact with websites, or work across connected apps. For longer tasks, Muse can continue working in the background and return when it has an update or needs your approval.

Meta launched Muse in September 2026. It runs on a dedicated cloud computer, called Muse Secure VM, with a browser and a Linux environment. That gives it tools to take action on the web, not just generate text.

If you’re wondering what Muse can actually do, how to get started, and whether you can trust it with real work, this guide covers the essentials. We’ll also show how to share documents and apps created with Muse, and how to hand off work between AI agents using AgentGrid.io.

What is Muse AI?

​Muse is a personal AI agent from Meta. Its main purpose is to turn a request or goal into completed actions.

For example, a chatbot might explain how to plan a product launch. Muse can help research competitors, create a draft launch plan, check your calendar, and prepare follow-up tasks using the apps you’ve authorized it to access.

Three things distinguish Muse from a conventional AI chat experience:

• It can take actions. Muse uses a browser and connected services to complete tasks such as filling forms, creating documents, or managing bookings.
• It can keep working. Supported tasks and monitoring can continue after you close the app; Muse can return with results, reminders, or requests for approval.
• It can use context over time. Muse is designed to remember goals and relevant details you share, so it can help with ongoing projects rather than treating every conversation as a fresh start.

You communicate with it naturally, much like messaging someone. You describe what you want to achieve and give it permission to use the tools it needs.

This is why Meta calls Muse a personal AI agent, not simply a chatbot. Meta’s introduction to Muse explains the distinction.

What can Muse AI do? Practical examples

Muse is built for both everyday tasks and more involved work. Here are some examples of what to try.

1. Research and summarize information

Ask Muse to compare products, investigate a market, collect sources, or turn a broad question into a structured report.

Prompt to try:

Research five AI tools that help product teams build prototypes. Compare their core features, pricing, and limitations. Create a report with source links and recommend which types of teams each tool suits.

Muse can gather information and draft the report. You should still check important facts and figures before using them in a decision.

2. Manage schedules, reminders, and routine tasks

Muse can work with compatible calendars, email services, and other connected apps, subject to the access you approve. It can help identify scheduling conflicts, prepare reminders, or monitor a recurring task.

Prompt to try:

Look at my calendar for next week. Identify scheduling conflicts and deadlines, and suggest a realistic priority list. Don’t change any events without asking.

3. Browse websites and complete actions

Muse’s browser is more than a source of search results. The agent can interact with pages, fill out forms, and help complete web workflows.

For example, you might ask it to compare travel options, gather information from multiple sites, or prepare an online form for review. Purchases and other sensitive actions may require your explicit approval.

4. Create documents and other content

Muse can draft reports, proposals, project briefs, content calendars, and other structured material. Meta also lists image generation among its capabilities.

Prompt to try:

Create a product requirements document for a simple customer feedback dashboard. Include the user problem, requirements, user stories, and an acceptance checklist. Use clear Markdown headings.

A useful document is often just the beginning. It may need review, changes, or a handoff to another agent. We’ll cover that workflow below.

5. Help run a small business

Meta also offers Muse for Small Business, with capabilities and connectors aimed at business workflows: marketing plans, campaign analysis, customer replies, sales follow-ups, and product pages.

A particularly useful feature for marketers is its connection to Facebook Pages, Instagram professional account analytics, and Meta ad accounts. Meta says Muse can use this context to learn your brand voice, understand what customers ask about, identify what’s working in your ads and content, and draft improvements. It also connects to tools such as Canva, Klaviyo, Shopify, Notion, and Figma. Exact access depends on your account permissions.

See Meta’s Muse for Small Business announcement and the official product page.

How does Muse AI work?

Muse combines an AI model with a persistent virtual computer and access to approved tools.

The computer is called Muse Secure VM. According to Meta, it includes a browser, files, processing resources, and an isolated Linux environment where Muse can run tools and develop custom skills. This helps it carry out multi-step tasks that a text-only chatbot cannot complete by itself.

Muse can also work with connectors: integrations that let it read information or perform permitted actions in other services.

When you give Muse a task, it can plan steps, use the relevant tools, and report back. Some actions happen automatically within the access you’ve granted; others trigger a permission request.

Meta describes a separate security component called Sentinel that checks external actions and network requests. This is a safeguard, not a guarantee that Muse will never make a mistake.

For a technical explanation, see How Meta built safety into Muse.

How to use Muse AI: Step by step

You don’t need to be a developer to get started.

Step 1: Open Muse

Visit muse.ai and follow the sign-in or download instructions. Meta supports Muse through its app and web experiences, and also describes using it through WhatsApp.

Availability matters: Meta’s current Muse for Small Business information lists access for adults aged 18 and over in the United States and Canada. Supported regions and platforms can change, so check the official site for your account.

Step 2: Start with one clear task

Choose a task with an observable result. Rather than asking, “Help me with marketing,” try:

Analyze the positioning of these three competitors. Create a one-page brief with their target audiences, differentiators, and key messages. Include source links.

A useful Muse prompt usually defines the goal, the input or context, the expected output, and anything the agent must not do.

Step 3: Connect apps when needed

If the task requires email, files, calendars, or another service, open Muse’s connector settings and authorize the relevant integration.

Start with the smallest amount of access that will accomplish the task. Reading a calendar is different from permission to edit it; drafting an email is different from sending it.

Step 4: Review progress and approvals

Muse may ask for approval before sending information, making a purchase, or taking another sensitive action. Review exactly what it proposes.

For research and documents, check sources, calculations, and conclusions. For web tasks, confirm the action really happened rather than relying on a plan or an unfinished attempt.

Step 5: Decide what should happen to the result

Some outputs are one-time answers. Others become work that a colleague or another agent needs to review, edit, or reuse.

For those, saving the work as a document or app with a stable link is often more useful than leaving it inside the original AI conversation.

Five Muse prompts worth trying

These examples help you experience different parts of Muse’s workflow. Adapt them to your own data and the services you’ve connected.

Competitive research

Compare four competitors in [category]. Use recent primary sources where possible. Produce a Markdown table of positioning, pricing, target customer, and notable differentiators. Flag anything you couldn’t verify.

Meeting preparation

Review my upcoming meeting with [company]. Summarize the relevant emails and documents I have access to, suggest five questions, and draft a short agenda. Don’t send it yet.

Personal task automation

Track the price of [product] and tell me if it falls below [budget]. Include the retailer and total price when you notify me.

A reusable business document

Create a customer onboarding checklist based on these notes. Organize it into stages, include owners and completion criteria, and format it as Markdown so the team can edit it later.

A small app idea

Design a lightweight dashboard for tracking weekly marketing experiments. Define the data fields, main screens, and user interactions. If your current tools support generating a working app, create the project files; otherwise produce an implementation-ready specification.

The last example intentionally distinguishes writing a specification from successfully generating a running application.

Muse AI for marketing: Facebook, Instagram, and Meta Ads use cases

Muse for Small Business connects to your Instagram professional account analytics, Facebook Pages, and Meta ad accounts. This is an important difference from asking a general chatbot for marketing ideas: Muse can use authorized information about your brand and campaigns. Meta explicitly highlights analyzing ad performance, improving content, and drafting upcoming campaigns as example tasks.

Muse also has a web browser, so you can ask it to research publicly accessible content. But the business integrations do not automatically give Muse access to private Facebook Groups, restricted Instagram comments, or competitors’ private performance data.

1. Find the language customers actually use

Customer research is more persuasive when it starts with real posts and comments rather than AI-invented personas. Give Muse specific public or authorized Facebook Groups, Instagram accounts, and discussion topics to investigate.

Prompt to try:

I sell [product] to [target customer], solving [problem]. Review these publicly accessible or authorized Facebook Groups and Instagram accounts: [links]. Find up to 30 real quotes about the problem, with a source URL for each quote. Organize the language into frustrations, desired outcomes, objections, and things people have already tried. Suggest ten hooks that reflect their wording. If you can’t access a source, tell me—don’t invent quotes or claim you saw private content.

Can Muse read any Facebook Group? No such blanket access has been confirmed. Whether this works depends on what the specific group and account allow Muse to view. Check the returned URLs and use quotes responsibly.

2. Create a weekly competitor ad brief

The Meta Ad Library lets people search publicly available ad information. You can ask Muse to inspect competitors’ visible ads where its browser can access them, then compare those creative patterns with your own connected ad account data.

Prompt to try:

Look for active ads from [competitor names] in Meta Ad Library. For each visible ad, record the headline, offer, format, start date, and source URL. Separately analyze my connected Meta ad account to identify which messages and formats perform best. Suggest five experiments for our next campaign. Do not infer competitor ROAS from ad visibility, and do not change budgets or publish ads.

A competitor’s ad appearing in the library is not proof that the ad converts. And Muse’s ability to inspect listings may vary with access controls.

3. Monitor changes and turn research into action

Muse can work on ongoing tasks. Ask it to revisit accessible sources and return a marketing brief that highlights what changed rather than repeating the same research.

Prompt to try:

Every Monday, revisit the accessible public competitor ads and social accounts in this list: [links]. Note newly visible ads, messaging shifts, and recurring customer questions from the previous week. Include evidence links and flag anything you couldn’t access. Prepare a short report with three experiments to consider. Don’t publish content or spend money without approval.

Where AgentGrid fits: Once Muse has produced a messaging bank or weekly competitor brief, save it as a shared AgentGrid document. Your marketing team can review the same artifact, and another authorized agent can turn the insights into a landing page, content plan, or app. The research becomes shared work rather than remaining inside one conversation.

Is Muse AI safe? Privacy and limitations

Giving an AI agent access to apps and accounts is a bigger decision than using it to answer a question.

Meta says Muse runs in an isolated virtual machine, separates stored credentials from the agent, allows users to manage connectors, and uses approval checks for sensitive actions. Meta also says Muse conversations aren’t shared with its advertising systems and offers controls over whether interactions are used to train its AI models.

These safeguards are useful, but they don’t remove every risk. Muse may misunderstand instructions, encounter incorrect information, or make mistakes in complex workflows. A connected app may also contain sensitive data you didn’t intend to use for the task.

A sensible starting point is to connect only what’s necessary, review permissions, ask Muse to prepare drafts before sending or publishing, and verify important outcomes. For confidential or high-stakes work, follow your organization’s data-handling rules.

Read Meta’s security explanation and the permissions shown in your own Muse account.

Can Muse AI write code or use a terminal?

Muse has access to a Linux-based environment with shell and command-line capabilities. Meta’s technical documentation says it can compile code and build custom tools or connectors for services that expose APIs or CLIs.

That doesn’t mean every coding workflow will work without setup. A particular tool may need to be installed, network access may require approval, and some actions may be restricted by Muse’s security controls.

It’s also useful to distinguish Muse, Meta’s personal AI agent, from Muse Code, Meta’s separate coding-focused product.

For projects that involve generated code, you can ask Muse to create files, run available commands, or prepare a project that another coding agent can continue.

Muse+Agent Grid: How to share documents and apps created with Muse

A report, Markdown document, or small application might start in Muse, but the next person who needs it may not use Muse at all.

Imagine this workflow: Muse researches a new market and writes a report. A teammate needs to review it. Later, a coding agent needs the same findings to build a dashboard.

Sending the chat transcript isn’t ideal: the useful content is mixed with instructions and conversation history. Copying files between tools can also create multiple versions.

​AgentGrid.io, built by Anima, is a shared workspace for documents, apps, and other artifacts created by people and AI agents.

Each artifact has a stable link and version history. People and authorized agents can work with the same artifact instead of passing copies between conversations.

It’s especially useful when you want to:

• Share a Muse-generated document with someone who doesn’t use Muse.
• Give teammates access to an app or report without making it public.
• Let another AI agent read and update the same work.
• Keep related documents and apps in a workspace that authorized agents can access.

You can keep artifacts private. Depending on the collaboration you need, you can invite a guest to a specific artifact, grant someone access to its workspace, or add them to your team. Publishing a public website is a separate, explicit action.

How to connect Muse to AgentGrid using Anima’s CLI

Muse’s command-line capabilities provide a path to connect directly to AgentGrid, without starting with a manual copy-and-paste workflow.

AgentGrid provides the Anima CLI, which supports login, workspace discovery, artifact creation or import, and updates.

The commands below are documented by AgentGrid. However, we have not independently verified the complete flow inside a live Muse session. Muse may need Node.js or npm installed, and its network and permission controls must allow the setup.

Step 1: Ask Muse to connect

Paste this into Muse:

I want to use AgentGrid to save and share the documents and apps we create. Check whether Node.js and npx are available in your environment. If they are, run npx @animaapp/cli@latest login. Give me the verification URL and code so I can approve access. Don’t publish anything publicly.

If npx is not available, ask Muse to report what’s missing and request approval before installing anything.

Step 2: Approve its identity and access

The CLI should return a verification URL and short code. Open the URL and approve the connection.

AgentGrid gives each connected agent its own identity and the workspace access and capabilities you authorize. You don’t need to give Muse your password.

Step 3: Verify the connection

Ask Muse to run:

bash
npx @animaapp/cli@latest workspaces

This lists the AgentGrid workspaces it can access. Verify that the intended workspace appears and that Muse has permission to create or update artifacts there.

Step 4: Create an artifact

For a Muse-generated Markdown report, save the report in a local folder with a .md file. Then ask Muse to import that folder into your chosen workspace.

The documented CLI command is:

bash
npx @animaapp/cli@latest create -t import --from ./report --artifact-type markdown --workspace <workspace-id>

Replace <workspace-id> with the ID returned by the workspaces command.

For a supported web-app project, the CLI can import a project folder as an app artifact instead, provided the project has the expected entry point.

After successful creation, Muse should return the AgentGrid artifact URL. Open it to verify the result.

See the AgentGrid connection guide and Anima CLI documentation for the current commands.

If you can’t use the CLI

You can still create a document or app artifact in AgentGrid and bring in supported Muse output yourself. This is a fallback, not the only workflow.

An official Muse directory connector is a separate distribution path; do not assume one is installed merely because Muse supports the CLI.

How to work with Muse and multiple AI agents on the same project

One of the more useful patterns is letting different agents contribute to a shared set of documents and apps.

For example:

Muse — research: Ask Muse to investigate a market and save a report as a Markdown artifact in AgentGrid.

A coding agent — implementation: Connect Claude Code, Codex, or another supported agent to the same authorized workspace. Ask it to use the research artifact as context and create a working dashboard.

A second agent — review: Ask another connected agent to inspect the dashboard or report, suggest improvements, and update the appropriate artifact.

Your team — decisions: Invite the relevant people to review the artifacts, leave feedback, and continue the work.

With the right permissions, these agents can access the artifacts available in the workspace. Each connected agent has its own identity, and updates are recorded in artifact history.

Important: Sharing a workspace doesn’t automatically transfer every private conversation or instruction between agents. Their common context is the documents and apps they can actually access. Tell each agent which artifact to use, and confirm its permissions before requesting an edit.

That’s the practical difference between several agents working separately and several agents contributing to shared work.

Final thoughts

Muse is interesting because it moves AI from answering questions toward actually completing tasks. For someone getting started, the most important thing is to give it a clear goal, connect only the tools it needs, and review the work it produces.

As you use more agents, the next challenge is keeping the outputs useful beyond one conversation.

For work that others need to review or continue, AgentGrid.io gives Muse-generated documents and apps a shared place to live—with a link, access controls, version history, and room for other authorized agents to contribute.

Start with Muse to get work done. Use a shared artifact when that work needs to go further.

Sources and further reading: Meta’s Muse announcement · Muse official website · Muse for Small Business · Meta’s technical security overview · AgentGrid connection documentation​