Manus AI is the world’s first general-purpose AI agent (AGI Agent) developed by Monica.im, a Chinese AI startup.
Background
Manus AI was developed by Monica.im, a Chinese AI startup, and its co-founder and chief scientist Yichao Peak Ji (纪逸超) officially launched the AI in early March 2025 through a demonstration video.
The video showcased Manus’s autonomous execution capabilities, attracting a large number of users’ interest in invitation codes. The system is described as the world’s first fully autonomous AI agent, in contrast to traditional AI assistants (such as chatbots that only provide suggestions or answers), Manus is able to independently perform tasks from planning to completion.
The development team includes serial entrepreneur Xiao Hong and AI product manager Zhang Tao. Xiao Hong previously founded Nightingale Technology and launched AI tools such as “Yiban Assistant” and “Weiban Assistant”, which received investments from Tencent and Zhen Fund.
He later developed Monica, an AI assistant that integrates large models such as Claude 3.5 and DeepSeek, with more than one million users in overseas markets.
Manus follows the philosophy of “less structure, more intelligence”, emphasizing data quality, model capabilities, and flexible architecture rather than predefined functions.
Key Features
What makes Manus AI unique is its autonomy and multi-domain capabilities:
Autonomous execution: Unlike traditional AI chatbots, Manus AI can independently plan and execute tasks without constant guidance from users. For example, it can create travel brochures or analyze stock data, and users only need to initiate tasks.
Multi-domain capabilities: It is able to handle a variety of tasks, including but not limited to travel planning, stock analysis, educational content creation, insurance policy comparison, and B2B supplier procurement.
Asynchronous operation: Manus AI supports asynchronous operation in the cloud, users can turn off the device, and the AI will continue to work in the background and provide results after the task is completed.
Performance and Benchmarks
Manus AI’s performance was evaluated using the GAIA benchmark, which assesses the ability of AI assistants in real-world problem solving. The study showed that Manus AI achieved state-of-the-art (SOTA) performance on all three difficulty levels, surpassing OpenAI’s Deep Research.
The GAIA benchmark was introduced by the 2023 Meta AI (FAIR), Hugging Face and other research teams, and contains 466 problems, each of which requires multi-step reasoning to solve, involving tool use (such as web browsing, code interpretation) and multimodal input (such as images, videos, Excel tables).
Humans scored 92% on the GAIA test, while GPT-4 with a plug-in scored only 15%, indicating that GAIA is challenging for AI. Manus AI claims to achieve SOTA on all difficulty levels, but this claim has not been fully verified by an independent third party.
How to apply Manus AI?
As of March 6, 2025, Manus AI is only available in the form of an invitation preview. Users can apply for access with an invitation code through the official website (web link). After Manus became popular, it attracted a large number of users’ interest in invitation codes. The hype of invitation codes on second-hand platforms has exceeded 50,000 yuan.
Manus AI Agent: Redefining the “executor” era of artificial intelligence
1. Technological Revolution: Paradigm Breakthrough from “Thinking” to “Action”
The birth of Manus AI Agent marks the leap of artificial intelligence from passive response to active execution. As the world’s first general AI agent, it was developed by the Monica.im team and officially released in March 2025. Its core breakthrough lies in the Multiple Agent System, which breaks down complex tasks into three independent modules: planning, execution, and verification. Each module is driven by a dedicated language model or reinforcement learning algorithm, and achieves real-time collaboration through API.
For example, in a stock analysis task, the planning agent calls the financial API to obtain data, the execution agent writes Python code to generate charts, and the verification agent predicts trends based on the market sentiment model – ultimately forming a complete report that can be directly used for investment decisions.
Unlike traditional AI (such as ChatGPT) that only provides suggestions, Manus has end-to-end task closed-loop capabilities:
- Tool call: It can independently operate browsers, code editors, databases and other tools to complete the entire process from information collection to output results.
- Long-term decision-making: It supports interruption and recovery across days and tasks. For example, if a user asks to “analyze Amazon’s financial report and write a PPT”, Manus will call the data analysis tool to generate a chart, and then call the design software to complete the presentation.
- Autonomous learning: Optimize decision logic through user feedback, and the memory module stores historical preferences (such as travel destination preferences and work habits) to achieve personalized services.
2. Functional Panorama: “Digital Agent” covering corporate, personal and creative scenarios
(I) Enterprise-level efficiency revolution
Business operation automation
- Supplier management: Automatically organize B2B enterprise lists (such as YC W25 batch startups) and generate purchase lists.
- Sales optimization: Analyze Amazon store sales data and provide inventory and pricing strategy suggestions.
- Financial decision-making: Integrate macroeconomic data and financial reports to build a dynamic investment portfolio. The accuracy of internal user feedback analysis is 45% higher than that of traditional tools.
Market research and decision support
- Public opinion analysis: Real-time capture of social media and news data to generate brand reputation reports.
- Cross-border investment: Combine geographic information and policy data to assess overseas home purchase risks (such as Japanese real estate investment, automatically calculate the cost-effectiveness of houses and generate home purchase reports).
(II) Personal life “super butler”
Travel planning
- Case: A user asked to “plan an in-depth tour of Japan’s cherry blossom season in April”. Manus integrated flights, hotels, and visa policies to generate an itinerary manual with budget and attraction recommendations, with a user satisfaction rate of 92%.
- Functions: Support multi-language price comparison, real-time weather integration, and emergency plan design.
Education support
- Teaching material development: Convert physical concepts (such as the momentum theorem) into animated courseware to assist teachers in efficient teaching.
- Learning planning: Dynamically generate a question bank based on students’ knowledge blind spots and provide videos for analyzing wrong questions.
Life affairs management
- Career optimization: Automatically screen resumes and simulate interview dialogues (Case: A technology company improved its recruitment efficiency by 80% through Manus).
- Insurance decision-making: Compare hundreds of policy terms and generate cost-effectiveness rankings.
(III) “Full-stack tools” for creative content production
- Multimodal output: Supports the full-process creation of text, images, and videos.
- Case: Generate scripts, design sound effects and covers for podcasts; write code and create test scenarios for game development.
- Business design: Customize corporate business cards, LOGOs, and promotional videos, and support automated operations of Adobe tools.
III. Technical architecture: Co-evolution of cloud-based intelligent agents and open source ecology
(I) Core technology modules
Multi-agent collaboration system
- Planning agent: Decompose tasks into sub-steps (such as “analyze financial reports → generate charts → write reports”).
- Execution agent: Call the tool chain to complete operations (such as Python code execution, web page data crawling).
- Verification agent: Cross-check the accuracy of results (such as multi-source comparison of stock data).
Cloud asynchronous computing
- Equipped with independent cloud computers (equipped with GPU/TPU resources), support continuous processing of complex tasks in the background (such as analysis of millions of rows of data).
- Visualization of task dashboard: users can check progress and interrupt/resume tasks at any time.
Memory and autonomous learning
- Long-term memory stores user preferences (such as travel budget cap, investment risk preference).
- Optimize decision paths through reinforcement learning, such as reducing repeated search steps.
(II) Open source plan and ecological expansion
- Open source strategy: The team plans to open source some models and reasoning modules to attract developers to build an ecosystem.
- Derivative projects: such as OpenManus (3-hour core function replication) and OWL (enterprise-level performance optimization).
- Tool chain integration: Support ROS robot system, Meta Ray-Ban AR glasses and other hardware, and explore the “end-side AI agent” scenario.
IV. Industry impact: reconstruction of business model, professional structure and social efficiency
(I) Business model innovation
- Enterprise service subscription
- From “buying software” to “subscribing to AI capabilities”, small and medium-sized enterprises can call Manus on demand to build an automated customer service system, reducing costs by 70%.
- Vertical field specialization
- Customized AI agents (such as OpenAI’s Operator service) appear in high-end markets such as finance, medical care, and law, with monthly fees of up to $20,000.
(II) Reshaping of the professional ecosystem
- Job extinction: Demand for basic data processing, customer service, and other positions has decreased.
- New occupations are born: Jobs such as AI trainers, intelligent system architects, and ethics auditors are on the rise. Microsoft predicts that 20% of jobs will be related to AI collaboration in 2030.
(III) Social efficiency leap
- Public field applications:
- Medical care: Generate personalized treatment plans based on patient data.
- Education: Dynamically adjust teaching plans to make up for knowledge blind spots.
- Hardware integration: Integrate with devices such as sweeping robots and smart glasses to achieve a closed loop of “environmental perception-decision-action”.
5. Challenges and the future: three major battles of technology, ethics and ecology
1. Technical bottlenecks
- Computing power dependence: complex tasks (such as multimodal data fusion) require cloud support, and end-side deployment is limited.
- Autonomous training: 90% of capabilities rely on third-party APIs, and autonomous model training needs to be strengthened.
2. Ethical risks
- Decision-making responsibility: For example, investment losses caused by biased real estate recommendations, the attribution of responsibility needs to be defined by law.
- Privacy protection: security vulnerabilities in the storage and call process of user data in the cloud.
3. Ecological competition
- Giant layout: Microsoft, Google and other companies accelerate the development of AI agents (such as Copilot Studio, Bard Agent).
- Open source community: It is necessary to balance technology sharing and commercial interests to avoid ecological fragmentation.
6. The ultimate vision of Manus AI Agent
The release of Manus AI Agent is not only a technical milestone, but also a turning point in the human-machine collaboration model.
With the deepening of multimodal capabilities (such as combining vision and voice models) and the acceleration of hardware integration, AI agents will become the “extended organs” of humans in the digital world in the future – from performing repetitive tasks to stimulating creativity, and finally realizing the ultimate vision of “letting machines complete basic work while humans focus on innovation and decision-making”. In this intelligent revolution, Manus may be the fulcrum that will usher in a new era.
Future Prospects
The launch of Manus AI marks a significant milestone in the field of AI assistants, whose ability to autonomously perform complex tasks could have a profound impact on productivity, efficiency, and innovation.
For example, in business settings, it could automate supplier sourcing and financial analysis; in personal life, it could simplify travel planning and educational resource creation.
In addition, Manus AI’s asynchronous mode of operation could change the way users interact with AI, allowing tasks to be completed without real-time monitoring. This could be particularly useful for tasks that require long computations or data processing, such as stock market analysis or large report generation.
As AI technology continues to develop, Manus AI’s capabilities are expected to expand further, potentially redefining the role of AI in personal and professional settings, especially in the competitive AI market, directly competing with OpenAI and other major players.
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FAQs
Below are some frequently asked questions and answers about Manus AI:
Manus AI is the world’s first general-purpose AI agent developed by Chinese AI team Monica.im, capable of independent thinking, planning, and performing complex tasks to deliver results directly. Its core concept is “hands and brains together”, emphasizing the combination of the intelligence of large models and the execution capabilities of tool calls. Manus AI is a general AI agent developed by a Chinese AI startup, which has attracted widespread attention around March 6, 2025.
The core functions of Manus AI include:
Autonomous execution of tasks: such as stock analysis, travel planning, code development, etc., without human intervention.
Multi-field coverage: Covering multiple fields such as finance, education, medical care, e-commerce, etc., handling tasks such as document writing, data analysis, and contract review.
Personalized customization: Memorize user preferences and optimize output results.
Manus AI adopts a hybrid architecture design, including a natural language understanding layer, a task planning engine, an API interface matrix, and an execution monitoring system. This design enables it to have multi-modal instruction parsing capabilities, dynamic resource scheduling mechanism, automatic rollback of exception handling, and cross-platform compatibility and adaptation.
Manus AI has a wide range of application scenarios, including but not limited to:
Financial field: stock analysis, investment advice, and automated processing of financial data.
Education field: courseware generation, learning path design, and academic content conversion.
E-commerce and operations: sales data analysis, competitive product monitoring, and customer service.
Medical field: diagnostic advice, electronic health record management, and clinical trial management.
Travel and shopping: itinerary planning, housing analysis, and shopping price comparison.
No. Manus AI supports pure natural language interaction, and users can use it without programming foundation.
Manus AI is fully compatible with Windows, macOS, and Linux systems.
Yes. All operations of Manus AI run in a local sandbox and are not uploaded to the cloud to ensure the security of data processing.
Manus AI plans to open source the reasoning module to attract developers to jointly build tool call plug-ins and promote the development of the open source ecosystem.
Users can visit Manus AI’s official website, click “Join Waitlist” to enter a commonly used email address, complete a simple technical awareness questionnaire, and then wait for an invitation email. Usually a response will be received within 1-3 working days.
Unlike traditional AI such as ChatGPT, Manus AI not only provides suggestions, but also directly delivers complete task results. It emphasizes the ability of the “execution layer” and realizes full-link automation of complex tasks through multi-agent collaboration and tool calls.
The world’s first general-purpose AI Agent that can think, plan and perform complex tasks (such as programming, data analysis, travel planning) independently like humans, and directly deliver complete results.
Traditional AI only provides information or suggestions, while Manus can directly operate computer tools (browsers, code editors, APIs, etc.) to complete multiple tasks and generate final files (such as Excel, web pages, reports).
You need to apply for an invitation code through the official website to register an account, enter a natural language task description (such as “Plan a 7-day trip to Japan”), and Manus will automatically break it down into subtasks (booking air tickets, hotels, itineraries) and execute them.
Support real-time feedback, such as changing the travel destination or hotel preference midway, Manus will dynamically adjust the plan.
It may be due to vague task descriptions or data boundary restrictions (such as inability to access paid resources). Suggestions:
Check whether key details (such as budget, format requirements) are missing.
Manual input is required for private data or paid content.
Currently, intermediate formats such as Markdown may be output, and complex designs need to be adjusted manually, but they can be gradually improved by optimizing prompt words.
Network instability, tool configuration errors (such as API key expiration) or too complex tasks. It can be executed in stages or the description can be simplified.
Multi-agent architecture (planning, execution, and verification run independently to avoid interference) + memory function (learning user preferences) + support for custom tool integration.
It cannot completely replace manual processing of private data or paid resources.
Complex tasks may require multiple optimization of prompt words.
Currently in the internal testing stage, an invitation code is required for experience.
Check network stability.
Perform complex tasks in steps (such as analyzing requirements first, then performing operations).
Analyze the execution process through the task playback function and optimize prompt words.
Provide clear requirements (such as “generate Python code + visual charts”), format preferences (such as Excel tables), and use historical tasks to optimize subsequent instructions.
Currently, feedback is mainly provided through the official website. Internal testing users can apply to join the Manus AI Agent community for help.
The team plans to expand cross-platform operations, custom tool integration and enterprise-level API services, and gradually open up more resource access rights.
Visit the official website and click “Experience Now”, register with a domestic mobile phone number and fill in basic information, and wait for review (passed in as fast as 5 minutes). The official has not opened a paid invitation code channel, please report if you encounter charges.
Absolutely not, natural language interaction throughout the process, as simple as guiding an intern.
Covering document processing, data analysis, code generation, project management and other scenarios, such as automatic generation of PPT, stock analysis, travel planning, resume screening, etc.
User feedback shows that efficiency has increased by 40% after 3 days of use, and asynchronous operation is supported (AI continues to execute after the device is turned off).
Traditional AI mostly provides suggestions, while Manus can execute autonomously and deliver complete results (such as automatically crawling data to generate reports).
Using a multi-agent federated architecture, planning, tool calling, and verification are coordinated in stages, reducing the error rate by 87%.
All operations are run in a local sandbox, supporting private deployment, and sensitive information (such as financial data) is not leaked.
It is good at structured tasks (such as data analysis), but has limited support for open creation (such as literary writing).
In actual testing, the server may crash due to load, and the task interruption problem needs to be optimized.
The team plans to open source the reasoning module framework to attract developers to expand vertical field functions.
As the world’s first general AI Agent, it has achieved a leap from “suggestion” to “execution” to meet the needs of efficient office work.
Overall positive, but it needs to be improved in complex table processing and accurate information positioning.
Develop a cross-platform collaborative version to support multi-person AI collaboration, custom workflow market, etc.
Check out the official “Common Problem Solutions”, covering more than 90% of usage scenarios.
