What is Manus AI? The autonomous agent explained, without the hype

In early 2025, one name suddenly appeared everywhere: Manus. An AI that did not just answer, but carried out entire tasks on its own. Planning trips, running market research, building a working website, all while you were doing something else. The demos were impressive and the hype followed. The question business owners asked me then, and still ask, is simple: is this real, and should I be doing something with it?

The short answer: it is real, it is important, and you do not have to act on it today. But it does show where AI is heading, and that is worth understanding. Here is the level-headed version.

What is Manus AI?

Manus is an autonomous AI agent, built by a Chinese startup and launched in March 2025. The name comes from the Latin word for hand, and that captures the idea: not an AI that talks, but an AI that acts. Where a chatbot waits for your next question, Manus is given a goal and gets to work, from start to finish, with minimal input from you.

The difference with ChatGPT or Claude in their usual form is that those mainly produce answers. You ask something, you get text back. Manus receives a brief like "research these three suppliers and put the comparison in a table" and does the work: opening websites, gathering data, organising it, and delivering the result. In short, it is generative AI that goes one step further and actually carries out tasks. What that really means, the difference between talking and doing, I unpack in what is an AI agent.

It is real, it is important, and you do not have to act on it today. But it does show where AI is heading.

How does it work?

Under the hood, Manus does what most autonomous agents do: it runs a loop of thinking and acting. It receives a goal, drafts a plan with smaller steps, executes each step using tools, and after every step checks whether it is still on track, until the goal is reached.

The strength sits in three things. First, it works with multiple specialised sub-agents that pick up tasks in parallel, like a project lead dividing work across a team. Second, it runs in a sandboxed cloud environment where it can install software, write code and search the web on its own, without touching your computer. And third, it leans on existing top models, including Anthropic's Claude, for the reasoning itself. So Manus is not one new brain, but a smart orchestration layer on top of existing models.

That last point is important to grasp: the Manus breakthrough is not a better language model, it is the orchestration around it. It shows how far you can already get with good coordination of models that already exist.

What it can do well

In practice, Manus shines at tasks with lots of sub-steps that would otherwise eat a lot of time. Researching across multiple sources and pulling that into an overview. Collecting data from websites and organising it. Simple analyses with a few charts alongside. Producing drafts: an outline for a report, a first version of a website, a schedule. Work that boils down to "figure this out and hand it over like this".

For anyone who spends a lot of time gathering, organising and producing a first version, that is genuinely useful. Not because it is flawless, but because a reasonable first draft that you review is often faster than starting from scratch.

What it cannot (yet) do reliably

Here a sober tone is warranted. Autonomous agents like Manus are impressive in a demo and inconsistent in practice. The more steps a task has, the greater the chance something goes wrong somewhere, and because the system keeps going, a mistake in step two compounds into step seven. It can confidently do the wrong things.

On top of that, you have to check the work. An agent that produces a supplier comparison on its own can copy a price incorrectly or invent a source. For research where the outcome matters, human review remains essential. And for sensitive data the familiar point applies: know where your data is processed, especially with a provider based outside the EU.

In short: it is a strong assistant for the first pass of work, not an unsupervised employee you can trust with a final result. Anyone who uses it that way, with checks on the important points, will get value from it. Anyone expecting it to run entire processes flawlessly will be disappointed.

How does Manus compare to other agents?

Manus is not the only player. On the developer side, Devin got a lot of attention as an autonomous AI programmer, and the big vendors are building agent features into their existing products: Microsoft with agents inside Copilot, OpenAI and Google with their own agent capabilities. The difference sits mostly in focus. Manus positions itself as a broad, general-purpose agent that tackles anything, while Devin is heavily specialised in software development and a Copilot agent slots tightly into your Microsoft environment. For small and mid-sized businesses that distinction matters more than the brand name: a specialised agent that does one task well is almost always more useful than a broad one that does everything halfway.

The bigger story: autonomous agents are coming

Whether Manus itself ends up as the winner is not really the question. It is one of the first visible examples of a shift that is happening at scale: from AI that answers to AI that executes. Market research shows how quickly this is moving. The market for AI agents grew from roughly 7.6 billion dollars in 2025 to an expected 11 billion in 2026, and market forecasts project that by the end of 2026, around 40 percent of enterprise applications will include task-specific agents, up from less than 5 percent a year earlier.

That does not mean you should point a Manus-style agent at your entire business tomorrow. It means the direction is clear, and that it pays to understand now what agents can and cannot do, so you are ready when the technology matures enough for your process.

What does this mean for small and mid-sized businesses?

For most SMEs, the win is not a general-purpose agent like Manus that does everything, but a narrow agent that takes over one concrete task: pre-sorting the inbox, drafting quotes, running a recurring piece of research. Specialised and reliable beats broad and inconsistent, especially when you do not have a team to absorb the misses.

Dutch SMEs are not lagging behind here either: according to the CBS, almost three in ten mid-sized companies now use AI, and appetite to invest is higher in Europe than anywhere else. The key question is where to start, and which process is already reliable enough for an agent today.

Start sober

Do not follow the hype, follow your own process. Manus is an excellent reason to understand what agents can do, not a reason to build your business on top of one right away. The order stays the same as with any AI: start with a process that eats too much time, check whether an agent can take that piece over reliably, build in a review step, and only expand once it is working.

If you want to explore what work at your company is ready to be handed to an agent, take a look at AI agents and automation. And if you want to know where most of the manual work at your company is hiding, the free AI scan gives you a first analysis based on your own situation.

Autonomous agents are no longer a future story. But the trick is not buying the most impressive demo, it is finding the most specialised agent that can reliably take over your work.