China has made great strides in artificial intelligence (AI) in recent years, with one of the most notable developments being Manus AI. Manus was launched in March 2025 with Butterfly Effects and with support from Tencent, it aims to transform industry by autonomously automating complex tasks.
From coding to financial analysis, this AI agent is designed to operate with minimal human intervention. Manus shows great potential, but there are limitations too. Understanding capabilities, limitations and areas for improvement is essential to understanding the potential role AI will play in the future.
What is Manus AI?
Manus AI is a cutting-edge autonomic agent developed by a Chinese startup known as Butterfly Effect AI. Unlike traditional AI assistants that typically rely on step-by-step instructions or focus on specific tasks, Manus can handle complex, real-world workflows with minimal human input. You can take on a variety of tasks, from writing code and generating financial reports, planning your trip itinerary, and analyzing large datasets.
What sets Manus apart is the ability to break down complex tasks into structured workflows, plan and execute each step, and adapt the approach based on the user’s goals. It uses a multi-model architecture and integrates advanced language models such as Anthropic’s Claude 3.5 Sonnet and Alibaba’s Qwen with custom automation scripts. This allows Manus to process and generate various types of data, such as text, images, code, and interact directly with external tools such as web browsers, code editors, and APIs, making it a highly versatile tool for developers and businesses. Manus also has an adaptive learning feature that allows you to remember previous interactions and user preferences. This improves performance over time, resulting in more personalized and efficient results. Asynchronous, cloud-based operations allow Manus to continue running tasks even when users are offline.
The rapid growth of discord communities and viral demonstration videos highlights the excitement and strong demand for Manus in the world of technology. Overall, Manus AI has made great strides in autonomous AI. Beyond simple chatbots, you can become a digital worker who can independently manage your entire workflow.
Manus AI Technology Architecture
Manus AI employs a complex architecture that integrates multiple advanced AI models and orchestration layers to enable efficient multi-step task automation. Unlike traditional AI models, Manus acts as a comprehensive system, tuning a variety of cutting-edge AI technologies, custom tools, and execution environments to effectively handle complex workflows.
Multi-model orchestration
Manus uses a multi-model approach to integrate top-large language models (LLMs) such as Anthropic’s Claude 3.5 Sonnet and Alibaba’s Qwen. This allows Manus to dynamically select and combine model outputs based on the requirements of each task. The orchestration layer acts as a central controller, breaking down complex requests into smaller, manageable tasks, assigning them to the most appropriate model, and synthesizing the results into a cohesive workflow.
Paradigm and tool integration code act
Manus’s key innovation is the Code Act paradigm. Instead of generating a text response, Manus creates an executable Python code snippet as part of that process. These code actions run in a secure, sandboxed environment, allowing the Manus to interact with external systems such as APIs, web browsers, databases, and even system tools. This means that Manus is simply a conversation assistant for a digital agent who can handle real tasks such as scraping web data, generating reports, and deploying software.
Autonomous Planning, Memory, and Feedback Loops
Manus includes an autonomous planning module that breaks down high-level goals into a series of steps. It also has both short and long term memory that is stored in a vector database and uses search extension generation (RAG) to remember user preferences, previous outputs, and related documents. This memory helps the Manus maintain accuracy and continuity across a variety of sessions and tasks.
Embedded feedback loops are also part of the system. After each action, Manus reviews the results, adjusts the plan as needed, and repeats the process until the task is completed or stopped. This feedback loop allows the Manus to adapt to unexpected results and errors, making them more resilient in complex situations.
Security, sandboxing, governance
Security is a top priority as Manus can run code and interact with external systems. Perform all code actions in an orphaned sandboxed environment to prevent unauthorized access or potential system compromise. Strict governance rules and rapid engineering are also implemented to ensure that Manus is compliant with safety standards and user-defined policies.
Scalability and cloud-native design
Manus is designed to work in the cloud and can be scaled horizontally across distributed systems. This design allows Manus to handle many users and complex tasks simultaneously without slowing down. However, as users report, system stability during peak use is an area where it is optimized for improved performance.
Real World Applications
Manus AI has the potential to transform industries such as finance, healthcare, logistics, and software development by automating complex workflows with minimal human intervention.
In the financial sector, Manus AI may assist in tasks such as risk analysis, fraud detection, and financial report generation. Processing large datasets in real time helps financial analysts identify trends and make informed decisions about investments, market risks and portfolio management.
Healthcare can use Manus AI to analyze patient data, identify patterns, and propose treatment plans. They may propose personalized healthcare options based on a patient’s medical history, which may play a role in improving patient care and supporting medical research.
In logistics, Manus AI may optimize supply chain management, deliver schedules, and predict potential disruptions. By adjusting delivery schedules based on real-time traffic data, delays can be minimized and operational efficiency can be increased.
For software development, Manus AI can write, debug, and create applications autonomously. This allows developers to automate repetitive tasks and allow them to focus on high-level problem solving. Manus can also generate reports and documents to further streamline the development process.
What sets Manus AI apart is the possibility of autonomous handling of the entire workflow. With the ability to break down complex tasks, plan and execute each step independently, Manus AI acts as a collaborator rather than just an assistant, reducing the need for constant human supervision.
It’s an impressive performance, but not without limitations
Manus AI has quickly gained attention in the field of autonomous agents and has shown impressive performances since its launch. According to Gaia Benchmark, Manus is superior to Openai’s deep research across task complexity at all levels. We scored 86.5% for basic tasks, 70.1% for intermediate tasks and 57.7% for complex tasks, compared to 47.6% for deep searches, compared to 74.3%, 69.1%, and 47.6% for deep searches.
The early user experience also highlights Manus’ ability to autonomously plan, execute, and refine multi-step workflows with minimal human input. This makes Manus particularly attractive to developers and businesses looking for reliable automation of complex tasks.
However, Manus still faces several challenges. Users report system instability, such as crashes and server overload, especially when AI is responsible for managing multiple or complex operations. It may also be that the Manus is repeatedly trapped in a loop or unable to complete certain tasks. This requires human intervention. Such issues can affect productivity, especially in high pressure or time sensitive environments.
Another concern is that Manus relies on existing models such as Anthropic’s Claude and Alibaba’s Qwen. These models contribute to Manus’ strong performance, but also raise questions about the originality of technology. Instead of being an all-new AI, Manus often acts as an orchestrator for these models, potentially limiting the long-term potential of innovation.
Security and privacy are also a major concern, especially since Manus can access sensitive data and execute commands autonomously. The risk of cyberattacks or data breaches is a concern, particularly taking into account the recent controversy surrounding data sharing by some AI companies in China. As industry experts have pointed out, these issues can make Manus even more difficult to adopt in the Western market.
Despite these challenges, Manus AI’s excellent benchmark results and real-world performance are a strong candidate for Advanced Task Automation, especially when compared to ChatGpt Deep Research. The ability to efficiently handle complex tasks is impressive. However, further improvements in system stability, originality and security are important to enable Manus to realize his potential as a mission-critical AI that he can trust.
Conclusion
Manus AI offers a great promise in changing how complex tasks are automated. The ability to handle multiple tasks with minimal human input can be a powerful tool for industries such as finance, healthcare, and software development. However, there are still challenges to overcome, such as system stability, reliance on existing models, and security concerns.
As Manus continues to improve, addressing these issues is essential to reaching their full potential. If these hurdles are cleared, Manus has the opportunity to become a valuable asset in a wide range of fields and evolves into a reliable digital assistant for both companies and developers.
