What is Manus? The New Autonomous AI Agent

Manus, a new kind of general AI agent designed to go beyond chat-based interactions, was unveiled on March 6, 2025. Unlike conventional AI assistants that require user input at every step, Manus is built to autonomously execute tasks from start to finish, delivering real-world results without continuous supervision.

A New Kind of AI Assistant

The name "Manus" is derived from the Latin word for "hand," reflecting its core purpose: to function as a digital agent that doesn't just process queries but can also carry out actions.

Unlike traditional AI models that rely on a single neural network, Manus operates as a multi-agent system. This means that it does not depend on one model to handle all tasks; instead, it coordinates several specialized AI models, each designed for different kinds of work. This allows Manus to break down complex tasks, execute each step efficiently, and refine results based on real-time feedback.

What makes Manus distinct is its ability to operate asynchronously. Once assigned a task, it continues working in the cloud without needing the user to stay engaged. This means users can assign research projects, data analysis, or content generation tasks to Manus and return later to review the completed work.

How Manus Works

Manus's multi-agent system enables it to analyze, plan, and execute complex tasks independently. When given a request, it decomposes it into multiple steps, determining which AI models or tools should be used at each stage. This architecture allows it to approach tasks methodically, much like a human project manager coordinating different specialists.

For example, if Manus is tasked with screening job applications, it does not simply provide a summary of the résumés. Instead, it:

1. Extracts relevant information from each file.
2. Assesses candidates based on predefined criteria.
3. Compiles structured reports, rankings, and suggestions.
4. Formats the final output into a spreadsheet or document, ready for review.

Similarly, for data-driven tasks like financial analysis, Manus does more than collect market data. It can write and run Python scripts to analyze stock trends, visualize insights with charts, and even generate reports formatted for presentations or websites.

One of its most promising capabilities is its ability to generate and deploy functional websites. In early demonstrations, Manus successfully built and launched an interactive financial dashboard based on stock market data. This suggests that its automation capabilities go beyond static text outputs, extending into real-world applications.

Use Cases and Early Demonstrations

Manus has been tested on a wide range of tasks, showcasing its versatility across different industries. In its initial demonstrations, it successfully handled tasks like resume screening, real estate research, stock analysis, and educational content creation.

For real estate market research, it gathered crime rate statistics, school district rankings, and property listings before analyzing the information and compiling a structured report. The process involved both data retrieval and intelligent filtering, allowing users to receive not just raw information but actionable insights.

Another demonstration highlighted Manus's potential in education and content creation. It was tasked with developing an interactive physics course, where it curated educational resources, created a structured lesson plan, generated visual materials, and even provided a video script for teachers. This ability to integrate multiple types of content into a cohesive package suggests that Manus could be useful for educators, researchers, and media professionals.

Comparisons to Existing AI Assistants

Manus stands apart from AI chatbots like OpenAI's ChatGPT, Google Gemini, or Anthropic's Claude, which primarily focus on text-based interactions and reasoning. While these systems provide responses and insights, they rely on users to take action on the information they generate. Manus, by contrast, is designed to complete entire workflows autonomously.

However, Manus does not yet have its own proprietary foundational AI model, unlike systems like DeepSeek, which has developed its own core AI engine. Instead, Manus integrates existing large language models, including Anthropic's Claude 3.5 Sonnet and Alibaba's Qwen models, to optimize its capabilities. The development team has indicated that future versions may incorporate custom-built AI models, but for now, Manus relies on a carefully orchestrated AI system rather than a single model.

Critical Analysis from MIT Technology Review and Business Insider

Caiwei Chen from MIT Technology Review tested Manus on a variety of tasks and compared it to working with a highly intelligent, efficient intern. She found that Manus excels at research-intensive and analytical assignments—completing work on par with what a skilled human intern might achieve in a day. Although it sometimes misinterprets instructions or makes incorrect assumptions, Manus sets itself apart by clearly explaining its reasoning and adapting remarkably well to feedback. A key highlight is its transparency and collaborative design: users can observe its work via a dedicated "Manus's Computer" window and intervene when necessary. Despite some technical challenges like crashes and server instability, Manus represents a significant milestone in autonomous AI that points to a future of minimal supervision.

"I found that using it feels like collaborating with a highly intelligent and efficient intern."
— Caiwei Chen, MIT Technology Review

Effie Webb from Business Insider also found Manus promising but not yet ready for full autonomy. In her tests, Manus effectively structured tasks by organizing work, updating progress, and delivering neat outputs. However, it stumbled by generating synthetic data for sentiment analysis and reusing an existing website for a startup assignment without clear disclosure. Despite these issues, Manus still demonstrates potential as a capable research intern. Like Caiwei Chen’s experience, Webb appreciated its collaborative nature, even though further refinement is needed to iron out execution issues and ensure system stability.

"While it shows potential as a capable 'research intern,' Manus still needs to iron out execution issues before it can operate independently."
— Effie Webb, Business Insider

Challenges and Limitations

Despite its early promise, Manus is not without its challenges. One of the biggest issues is its limited availability. Currently, access is restricted to an invite-only system, and demand has far exceeded the development team's expectations.

Another concern is scalability. Because Manus operates in the cloud and requires significant computing power, its long-term performance will depend on whether the infrastructure can support large-scale adoption.

There are also ethical concerns surrounding AI automation. With Manus being capable of independently executing tasks, questions arise about data privacy, security, and the potential for AI-driven misinformation.

Conclusion

Manus represents a significant step forward in AI development, introducing an autonomous agent capable of handling real-world tasks with minimal human intervention. It takes AI one step further by actually executing complex workflows.