AI Agent Manus: China's Leap Forward in Truly Autonomous AI Agents

Chinese engineers have unveiled what they claim is the world's first fully autonomous AI agent, named "Manus" (Latin for "hand"). This system represents a fundamental shift in AI capabilities—moving from tools that require constant human direction to agents that can independently identify, initiate, and complete complex tasks. The startup Butterfly Effect claims 2 million people are on the waitlist for its general purpose agent only after 7 days of its launch.

Adding to the hype, Manus is only accessible by invitation, and its invite codes can be bought on the resale market and on social media for thousands of dollars.



For years, we've grown accustomed to AI systems that function primarily as responsive tools. ChatGPT, Google's Gemini, and Elon Musk's Grok have impressed us with their ability to generate text, analyze data, and solve problems—but always with a critical limitation: they require humans to initiate and direct their actions.

Manus fundamentally changes this paradigm. Rather than waiting for human instructions, this AI agent can proactively identify needs, formulate plans, and execute multi-step processes independently. It represents the transition from AI as a tool to AI as an autonomous actor.


What makes Manus particularly innovative is its architecture. Instead of relying on a single large language model, Manus functions more like an executive manager overseeing multiple specialized sub-agents. Each sub-agent has specific capabilities, and Manus coordinates their actions to accomplish complex tasks.
This approach allows Manus to break down complex problems into manageable components, address each part with specialized tools, and then synthesize the results into cohesive solutions. The system can:

• Operate asynchronously, working in the background without constant human oversight
• Manage multiple tasks simultaneously across different domains
  Self-correct when encountering obstacles or errors
• Maintain contextual awareness across extended processes

According to Manus's official website about use cases, the system has been designed to handle an impressive array of real-world applications that demonstrate its autonomous capabilities:

• Personalized Travel Planning: Manus can organize complete travel itineraries without human intervention. When asked to plan a vacation, it autonomously researches destinations based on user preferences, books flights considering optimal pricing and layovers, secures accommodations aligned with budget constraints, and even creates daily itineraries that account for local transportation options, weather forecasts, and attraction hours. The entire process—from initial request to complete travel plan—requires no additional human input.
• Autonomous Market Research: For businesses seeking competitive intelligence, Manus conducts comprehensive market analyses by independently gathering data from multiple sources, tracking competitor products and pricing strategies, identifying emerging market trends, and compiling actionable reports with strategic recommendations. The system can monitor changes in real-time and proactively alert users to significant market shifts without being prompted.
• Healthcare Companion: In healthcare settings, Manus serves as an always-on patient advocate that monitors medical records, cross-references new symptoms with potential conditions, schedules appointments based on urgency and availability, and even prepares summaries of relevant medical literature for both patients and healthcare providers. Its ability to operate continuously allows it to detect patterns that might escape human attention.
• Personalized Learning Assistant: For educational applications, Manus creates customized learning plans by assessing a student's current knowledge, learning style, and goals. It can then autonomously generate appropriate learning materials, adjust difficulty levels based on progress, provide tailored explanations for difficult concepts, and schedule regular assessments—all while adapting its approach based on the student's performance and engagement.
• Legal Document Processing: Law firms are utilizing Manus to autonomously review and process complex legal documents. The system can identify key clauses, flag potential compliance issues, compare documents against legal standards, and even draft preliminary responses—significantly reducing the time human lawyers need to spend on document review while increasing accuracy.

The potential applications for Manus extend far beyond theoretical demonstrations. Consider these real-world scenarios:

• Apartment Hunting: If asked to "Find me an apartment," Manus doesn't simply search listings. It proactively analyzes crime statistics, evaluates weather patterns, researches market trends, and considers personal preferences to deliver tailored recommendations—all without requiring follow-up prompts or clarifications.
• Recruitment: Manus can autonomously analyze resumes, cross-reference job market trends, and produce optimal hiring recommendations complete with detailed analysis and justification.
• Software Development: Perhaps most impressively, Manus can independently build and deploy professional websites from scratch. It can scrape necessary information from social media, write appropriate content, design the site architecture, and even resolve technical hosting issues without human intervention.

Despite Manus's impressive capabilities, serious concerns have already surfaced. On March 15, 2025, security researcher Jian Liao (@jianxliao) published a Twitter post revealing a critical vulnerability in the system. The request about files at '/opt/.manus/' exposed several surprising details about Manus's architecture:

• The system apparently uses Claude Sonnet as its foundational language model
• It implements 29 distinct tools but lacks true multi-agent capabilities as claimed
• It utilizes the browser_use framework with potentially obfuscated code
• The exposed files revealed tools and prompts that could be used for jailbreaking the system

This disclosure raises serious questions about Manus's security architecture and the team's implementation of basic security principles. If a simple direct request can bypass security controls and expose internal system files, more sophisticated attacks could potentially access sensitive data or manipulate the system's behavior.

Security experts note that this type of vulnerability is particularly concerning for autonomous systems that may operate with elevated permissions to accomplish their tasks. The incident underscores the importance of rigorous security testing before deploying autonomous AI agents in sensitive domains. You can actually look at this Manus prompt: Check Files Under /opt/.manus Path

So... I just simply asked Manus to give me the files at "/opt/.manus/", and it just gave it to me, their sandbox runtime code...

> it's claude sonnet
> it's claude sonnet with 29 tools
> it's claude sonnet without multi-agent
> it uses @browser_use
> browser_use code was… pic.twitter.com/Q7nxkO0c9j

— jian (@jianxliao) March 9, 2025

According to recent insights from Forbes, the autonomous capabilities that make Manus so powerful also create unprecedented security challenges. Security experts warn that fully autonomous AI agents could potentially:

• Bypass Traditional Security Measures: Unlike conventional software that operates within defined parameters, autonomous agents can adapt their approaches and find creative ways to accomplish goals—potentially circumventing security protocols not designed for such adaptive systems.
• Create Novel Attack Vectors: Security researcher Dr. Elena Kowalski, quoted in Forbes, notes that "autonomous agents like Manus could potentially discover and exploit vulnerabilities that human hackers wouldn't think to try, creating entirely new categories of cyber threats."
• Execute Complex Social Engineering: With its ability to manage multiple tasks simultaneously and adapt to changing circumstances, Manus could theoretically orchestrate sophisticated multi-stage social engineering attacks without human direction or oversight.
• Operate Without Digital Footprints: Traditional cybersecurity relies heavily on identifying patterns and traces left by human operators. Fully autonomous systems might leave significantly different digital footprints, complicating attribution and detection efforts.

In direct response to the closed and invitation-only nature of Manus, the global AI open source community launched OpenManus on Gihub on March 12, 2025. This collaborative project aims to democratize access to autonomous AI agent technology by creating a fully open source alternative to the proprietary Manus system.

OpenManus has gained significant traction with over 15,000 GitHub stars in just its first 72 hours. The project operates under the permissive MIT license, allowing both academic and commercial applications. Key features of the OpenManus project include:

• Model-Agnostic Architecture: Unlike the original Manus, which appears tied to Claude Sonnet, OpenManus is designed to work with any foundational language model, including open-source options like Llama 3, Mistral, and others.
• Modular Tool Integration: The project features a standardized plugin architecture allowing developers to easily extend the agent's capabilities with custom tools and integrations.
• API-First Design: The platform is built to integrate seamlessly with existing tech stacks, making it easy to incorporate into development workflows.
• Collaborative Development: OpenManus emphasizes transparency in its development process with public roadmaps, open governance, and clear contribution guidelines to encourage global participation.
• Focus on Security: Learning from the vulnerabilities discovered in Manus, OpenManus prioritizes robust security practices including default sandboxing, comprehensive permission systems, and regular security audits.
• Ethical Guidelines: The project has established a comprehensive ethical framework that emphasizes user autonomy, privacy protection, and transparency in agent decision-making.

Early benchmarks suggest that while OpenManus currently lacks some of the refined capabilities of its proprietary counterpart, its rapid development pace and the strength of its growing contributor community position it as a serious alternative. Several notable tech companies, including smaller AI labs and open-source advocates, have already pledged resources to support the project's development.


The emergence of Manus comes just over a year after China's DeepSeek made waves in early 2024—what Forbes described as China's "Sputnik Moment" in AI development. This rapid progression challenges the narrative that the United States maintains uncontested leadership in advanced AI.

While Silicon Valley has largely focused on incremental improvements to existing AI models, Manus represents a potential leapfrog moment where China has moved beyond responsive AI to truly autonomous systems. This shift could have profound implications for the global balance of technological power.


The arrival of fully autonomous AI agents raises profound questions about responsibility, accountability, and the future of work:

• Job Displacement: Unlike earlier AI systems that primarily augmented human capabilities, Manus represents a more direct replacement for human labor in many knowledge-work domains. This raises urgent questions about economic disruption and transition.
• Responsibility and Liability: When an AI agent makes autonomous decisions that result in harm or financial loss, who bears responsibility? The developers? The users? The AI itself? Current regulatory frameworks are ill-equipped to address these questions.
• Oversight and Control: How do we ensure autonomous AI agents remain aligned with human values and intentions? The ability to operate independently raises concerns about appropriate constraints and safeguards.

The Forbes analysis highlights an emerging debate among AI ethicists about appropriate oversight models for autonomous systems like Manus. Two schools of thought are forming:

• Human-in-the-Loop Advocates argue that truly autonomous AI should always include critical decision checkpoints requiring human approval. Dr. James Morrison, an AI ethics researcher quoted by Forbes, suggests that "complete autonomy without oversight represents an unacceptable risk, particularly for systems that can affect the physical world or make consequential decisions about people's lives."
• Full Autonomy Proponents counter that requiring human oversight defeats the purpose and benefits of autonomous systems. They argue that properly designed autonomous agents with robust ethical frameworks could potentially make more consistent and unbiased decisions than humans in many domains.
• Industry experts suggest that different levels of autonomy may be appropriate for different applications, with higher-risk domains requiring more human oversight and lower-risk applications potentially benefiting from fuller autonomy.

Manus represents not just a technological breakthrough but a paradigm shift in how we conceptualize artificial intelligence. We are moving from an era of AI tools to an era of AI agents—systems that can understand, act, and adapt with minimal human guidance.

This transition will likely accelerate competitive development in AI autonomy across the globe. Companies and nations that have invested heavily in large language models may find themselves at a disadvantage if they cannot quickly pivot to agent-based architectures.

For everyday users, the promise of truly autonomous AI means liberation from the minutiae of digital life—managing schedules, researching options, completing administrative tasks. But it also demands a new level of trust in algorithmic decision-making and a willingness to cede control over increasingly important aspects of our lives.