Think of it as Yoga for the brain, we are going to stretch a bit.
Meta Muse: The AI Agent That Finally Feels Like a Personal Assistant
After years of chasing the next big thing, Mark Zuckerberg may finally have another hit on his hands — and this time, it’s AI. -- YNOT!
Meta’s new Muse isn’t trying to be another ChatGPT. After using it on my phone, computer and even across my WordPress sites, I think that may be exactly why it is so interesting.
I use a lot of artificial intelligence.
I use Claude heavily for programming. I use ChatGPT for overall design, planning, research and thinking through complicated problems. I run my own local LLMs for everyday jobs where I want something fast, inexpensive and under my own control.
So when another AI product appears, my first question is usually: What am I supposed to do with this that I’m not already doing somewhere else?
With Muse, I found the answer surprisingly quickly.
Muse is different. It isn’t necessarily the biggest hammer in my AI toolbox. In fact, that misses the point.
I have started thinking about it this way: Claude is my shovel. ChatGPT is my philosopher. Muse is my dagger.
It is smaller, closer and more personal. It is the AI I can pull out on my phone, tell something to, let it remember what I am doing and increasingly have it actually take care of the job.
And that distinction between answering and doing may turn out to be much more important than another round of AI benchmark scores.
So What Exactly Is Muse?
Meta officially introduced Muse on September 8, 2026, describing it as a personal AI agent rather than simply another chatbot. Meta says the idea is straightforward: instead of merely answering a question and waiting for another prompt, Muse can work toward goals, operate across connected applications and perform multi-step tasks on a user’s behalf.
Underneath Muse is something Meta calls the Muse Secure VM.
Think of it as a dedicated virtual computer living in the cloud for your Muse. It has its own browser and can navigate websites, work with connected services and continue performing tasks even when you are not sitting there watching it. Meta says the agent is powered by its Muse Spark family of models, which were designed specifically around reasoning, tool use and agentic work.
That is an important distinction.
A traditional chatbot waits.
You ask something. It answers.
You ask something else.
An agent is supposed to be capable of taking a goal such as:“Find me a good used camera under this price.”
And then figuring out that it needs to search several places, compare products, keep track of what it found and come back with useful choices.
Eventually, the goal is for these agents to handle more and more of the tedious digital work we currently perform ourselves.
That is where Muse starts becoming interesting.
Muse Is Surprisingly Simple
One of the first things I noticed is how little there is to learn.
There isn’t an intimidating control panel with 200 options.
Most of the time, there is simply your main conversation with Muse.
You can create side chats when you want to separate something, but the central idea is that you keep talking to the same Muse.
That sounds almost too simple until you start using it.
With ChatGPT or Claude, I can have dozens of conversations. There are coding chats, server chats, research chats, website chats and whatever else I am working on.
Muse leans much more heavily toward the idea that this is your AI.
You aren’t continually introducing yourself to it. You keep talking to it.
Two of the features that help make this work are Ideas and Goals.
Muse can recognize things you have been discussing and turn them into ongoing goals. It can also suggest things it might be able to do based on those conversations.
For example, if you’re talking about an upcoming trip, Muse might suggest organizing the itinerary or researching activities.
You don’t necessarily have to sit there wondering:
“What should I ask my AI today?”
The AI can begin asking, in effect:“What can I take off your plate?”
That reversal is significant.
1. It Has a Browser — And It Actually Uses It
This is probably the first thing that makes Muse feel less like a chatbot.
Muse can operate a browser.
Meta says the Muse Secure VM can navigate the web, fill in forms, make appointments, handle customer-service workflows, research products and perform other web-based tasks.
Shopping is an obvious example.
Instead of asking:“What is a good camera?”
I can tell Muse what camera I’m interested in, give it my requirements and have it actually go looking.
It can search marketplaces and retailers, come back with several possibilities and help narrow them down.
Instead of simply receiving ten blue links, you’re getting something closer to having somebody sit beside you and say:
“I checked these. Here are the ones that make sense. This one is used, this one is refurbished, and this one is cheaper but has a few disadvantages.”
Meta has built shopping directly into the product. Muse can compare prices, monitor them and, where supported, complete purchases after receiving the necessary approval from the user.
That’s much closer to an assistant than a search engine.
And It Can Log Into Websites
This is where things get much more interesting for me.
Muse can work with websites requiring authentication without you simply typing your password into an AI conversation.
According to Meta, credentials are placed into secure credential storage so Muse can use the account without the agent itself being able to read the password. Meta also requires approval for critical actions such as sending emails or making purchases.
That opens up a much larger category of work.
For me, one of those categories is WordPress.
Muse and WordPress Changed My Opinion of It
I manage a number of websites.
That means there is always something that needs doing:
SEO checks. Plugin updates. Theme updates. Comment moderation.
Looking for something broken. Making repetitive changes.
Checking settings. Normally, none of these jobs is particularly difficult.
The problem is that they take time.
What surprised me is how competent Muse can be with this type of ordinary browser work.
Because it can operate the keyboard and browser, I can have it log into a WordPress website, examine parts of the site, check SEO-related items, remove unwanted comments and work through routine administrative tasks.
One evening I had it work through roughly 20 websites in about the time it would normally have taken me to manually work through a couple of them.
That got my attention. This is where the value proposition for AI agents starts becoming clearer. I don’t necessarily need another model capable of writing a better poem.
I need something capable of doing 43 boring things I don’t want to spend my evening doing. That is agentic AI.
And for anyone administering websites, running a small business or managing a lot of online services, that could eventually be transformational.
Obviously, I would still be careful about giving any AI unlimited administrative authority. Website backups, sensible permissions and supervision remain important.
But having an AI assistant capable of actually working inside the interface changes the equation considerably.
2. Muse Works Extremely Well From a Phone
This may actually be Muse’s greatest advantage.
I use it from my phone constantly.
And I rarely type. I dictate.
That makes the experience feel much more like having an assistant with me rather than opening an AI application and sitting down to “use AI.”
I might remember something while walking around.
I tell Muse. I might think of something I have to do tomorrow.
I tell Muse. I might need it to research something.
I tell Muse. The phone doesn’t feel like a stripped-down companion to the desktop application. For many tasks, it feels like essentially the same Muse.
That matters because the best personal assistant in the world isn’t very useful if it is only available when you’re sitting in front of a particular computer.
Meta currently offers Muse on iPhone and Android as well as desktop and web interfaces, and Muse can keep working on tasks even when the mobile application is closed.
3. Voice Memos Are More Useful Than They Sound
Here’s a deceptively simple feature that I have come to appreciate.
Muse can take something lengthy and turn it into something I can simply listen to.
Imagine asking about a complicated subject and receiving several screens of information.
Sometimes I don’t want to sit there and read all of it.
So I can ask for the short version as a voice memo.
Now the AI becomes something I can listen to while I am walking around, driving, doing chores or working on something else.
That sounds minor. It isn’t.
We tend to think about AI interfaces as text boxes because that is how ChatGPT-style AI started.
But personal AI increasingly needs to fit around the human rather than forcing the human to fit around the computer.
I will dictate a question to Muse and then have Muse give me the answer back in a form I can listen to.
That creates a completely different interaction model.
From Voice Memos to Personal Podcasts
Muse can take that idea further.
I have been experimenting with having it prepare longer audio-style briefings.
Think about the possibilities. Instead of opening half a dozen technology websites every morning, I can tell an AI: Every morning, research what’s happening in consumer AI. Tell me what is new with Muse, ChatGPT, Claude, Gemini and the other major platforms, and give me something I can listen to.
Now my morning information gathering becomes a personalized briefing.
That’s one of the directions I find most interesting.
The AI doesn’t just wait for me to remember to research something.
It becomes part of a routine.
4. Muse Can Work With Your Computer
This was another feature that surprised me.
I have a computer that stays running all the time. It is essentially part of my AI infrastructure.
With the Muse desktop application, the agent can work with local files and applications when given permission.
Meta currently describes its Mac application as being capable of organizing files and working with Messages, Calendar and Notes, in addition to accessing desktop files, applications and browser tabs.
The important part for me isn’t the technical description.
It is the simplicity. I can essentially say: “There’s a document on that computer. Read it and summarize it.”
Then: “Put that summary at the beginning of the document.”
And the job can be done.
This isn’t revolutionary because no other AI can manipulate files.
Other AI systems can perform more sophisticated computer tasks.
What I like is that Muse makes simple jobs feel simple.
That counts for a lot.
5. Muse Is Starting to Make Phone Calls
This is one of the more experimental parts of the experience, and my results have been mixed.
The concept is fascinating. Instead of merely finding the phone number for a business, an AI agent can potentially make the call for you.
Need to know whether a store actually has an item in stock?
Need to check whether a restaurant has availability?
Those are exactly the kind of small interruptions that consume little pieces of a person’s day.
In my testing, Muse’s business-call functionality prepares what it intends to ask, requires approval and identifies itself as acting on your behalf.
I like the concept. The reality is still developing.
Some businesses are not particularly enthusiastic about receiving calls from AI agents. Once the person realizes an AI is talking to them, reactions can range from cooperation to confusion to simply hanging up.
So I would put this feature in the promising but early category.
The technology will improve. The bigger question may be whether the rest of society is ready to have computers calling computers — and humans — all day long.
Security Matters More With an Agent
There is another side to all of this. A chatbot that writes a bad answer is annoying.
An agent capable of sending emails, buying something or modifying a website can cause an actual problem. The more useful AI agents become, the more important permissions and security become.
Meta’s architecture reflects that.
Muse runs inside its dedicated Secure VM, and Meta says a separate Sentinel agent reviews outbound activity. Sensitive operations can require approval, credentials are stored separately from the agent, and users can review an audit trail showing what Muse has done and what it plans to do. Meta also says Muse conversations and VM data are not shared with its advertising systems.
Those are important protections. They don’t mean users should stop paying attention.
Quite the opposite. We’re entering unfamiliar territory.
If I give an AI permission to operate websites on my behalf, I want to know exactly what “permission” means.
There has already been public discussion about the consequences of giving autonomous agents broad access to personal information and online accounts. As these systems become more capable, understanding those permissions will become as important as understanding smartphone privacy settings.
The rule I follow is simple: Give the agent enough access to be useful, but understand what you have authorized it to do.
Who Actually Created Muse?
Muse is a Meta Platforms product, and Meta officially launched it on September 8, 2026.
The underlying technology had been developing before the Muse product launch.
Meta introduced Muse Spark earlier in 2026 through Meta Superintelligence Labs, positioning the model family around its next generation of AI products. By September, Muse Spark had evolved into the model platform powering the new personal agent.
The broader effort is tied to Meta CEO Mark Zuckerberg’s push toward what the company describes as “personal superintelligence.”
Two people frequently associated with the development effort are Alexandr Wang, the former Scale AI CEO who joined Meta’s AI leadership, and Nat Friedman, the former GitHub CEO. Recent reporting from The Wall Street Journal and Business Insider describes Wang and Friedman as important figures in the development and launch of Muse.
Muse therefore isn’t simply a rebranding of Facebook’s old chatbot technology.
It represents a larger strategic shift inside Meta toward AI systems that can remember, plan and act.
Muse Isn’t ChatGPT — And That’s a Good Thing
The easiest mistake would be to compare Muse to ChatGPT by asking:
“Which one is smarter?”
That isn’t how I use them.
These products increasingly have different jobs.
Claude, for me, is heavily associated with programming and development work.
ChatGPT is the system I use for large-scale thinking, design, research, architecture and figuring out complicated problems.
My local LLMs handle a lot of routine AI jobs where privacy, speed and cost matter.
And Muse is becoming the personal agent that stays close to me and gets smaller jobs done.
That is why I used the analogy earlier: Claude is the shovel.
ChatGPT is the philosopher. Muse is the dagger.
I don’t want them all to become the same thing.
The AI market becomes far more interesting when different systems start specializing.
And Muse Is Surprisingly Affordable
Another reason Muse is getting attention is that Meta is making a significant amount of usage available without requiring everyone to immediately purchase an expensive subscription.
Meta currently says Muse has a free tier with a usage limit, with paid subscriptions available if someone needs more capacity.
My own account has had extremely generous limits. That could change.
AI companies frequently start products with generous allocations while they are building an audience and then adjust pricing and limits later.
So I would not choose Muse because I expect it to remain inexpensive forever.
I would choose it because I think the personal-agent model itself is worth experimenting with.
Where Muse Still Falls Short
Muse is not perfect. And I don’t think it is the most powerful AI system available.
There are things I would much rather give Claude.
There are complicated questions I would rather work through with ChatGPT.
There are tasks I would rather keep entirely on my own servers.
Computer automation can still fail. Websites change.
Browser agents can click the wrong thing.
Phone calls can become awkward.
And whenever an AI starts acting instead of merely talking, mistakes become more consequential.
That’s why I don’t view Muse as a replacement for everything else.
I view it as a new category.
The Real Story Is Bigger Than Muse
The most important thing about Muse may ultimately have very little to do with Muse itself.
For the first several years of mainstream generative AI, we mostly talked to AI.
We asked questions. We generated pictures. We wrote emails.
We created code. We summarized documents.
That was Phase One.
The next phase appears to be:Give the AI a job and let it do the job.
That is a much bigger transition.
Imagine telling your personal agent: “My car insurance renews next month. Check my existing policy, compare alternatives and come back to me if you find something substantially better.”
Or: “Watch airfare to Montreal and tell me when it drops below $300.”
Or: “Check these 20 websites tonight and tell me tomorrow morning which ones need attention.”
Or simply: “Handle this.”
That last sentence may eventually define the personal-AI era.
My Take After Actually Using Muse
Muse is probably the easiest AI agent I have used so far.
And its simplicity can fool you.
Underneath that simple conversation window is a browser, a persistent virtual computer, connected applications, memory, goals, automation and an AI capable of taking actions on your behalf.
I originally started using it on my phone for simple things such as keeping track of what I needed to do.
Then I realized it could browse. Then I started having it research products.
Then I started experimenting with voice. Then websites. Then files.
Then recurring jobs. That progression is exactly what makes Muse interesting.
You don’t necessarily sit down on the first day and say:
“I am now going to completely automate my digital life.”
You give it one little job. Then another. Then another.
And one day you realize the AI isn’t merely answering you anymore.
It is working for you. That is the part of Muse worth paying attention to.
Want to Try Muse?
Meta currently offers Muse on mobile, web and Mac, with much of the service available through its free usage tier.
My Muse referral code: EYWN3S
https://muse.ai/join
At the time I received the offer, using the referral code provided additional Muse tokens to both the new user and the person making the referral. Referral programs and usage limits can change, so check the current offer when signing up.
Meanwhile we keep exploring the technology that is changing how we live, work and interact with the world around us. Subscribe
