Meet Manus: The AI that works independently

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In this newsletter, we’re excited to share that Chinese startup Monica has launched Manus AI, a groundbreaking autonomous agent that's generating significant buzz in the tech world. Unlike traditional chatbots, Manus works independently in the cloud to plan and execute complex tasks across multiple domains without continuous human oversight. Released on March 6, 2025, the system reportedly outperforms competitors like OpenAI's DeepResearch on benchmark tests, featuring a multi-agent architecture that delegates specialized tasks while displaying its workflow in real-time. Currently available by invitation only, Manus represents what many are calling China's second "DeepSeek moment" in AI development.

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Manus AI: The next frontier in autonomous AI agents

In the rapidly evolving landscape of artificial intelligence, a new player from China has emerged that's generating significant buzz across the tech industry. Manus AI, developed by Chinese startup Monica, launched on March 6, 2025, and has quickly positioned itself as a groundbreaking autonomous agent capable of executing complex tasks with minimal human input. As AI technologies continue to advance, Manus represents what many are calling China's second "DeepSeek moment," following the earlier success of DeepSeek's R1 model.

What is Manus AI?

Manus AI distinguishes itself from conventional chatbots by functioning as a general-purpose AI agent designed to bridge human intent with action. Unlike traditional AI systems that require continuous oversight and step-by-step guidance, Manus operates autonomously, planning, executing, and delivering end-to-end results across various domains.

What sets Manus apart is its ability to work asynchronously in the cloud even after a user disconnects. The system notifies users upon task completion, making it function more like a highly intelligent digital assistant than a mere conversation partner.

For example, when tasked with creating a research paper on global warming, Manus independently sources data, writes the report, generates charts, and compiles the final document without additional prompts. Similarly, for travel planning, it analyzes weather patterns, budgets, and preferences to craft comprehensive day-by-day itineraries while displaying its workflow in real-time.

Key features and capabilities

Autonomous task execution

Manus operates without continuous oversight. Once assigned a task, it works asynchronously in the cloud even if the user disconnects and notifies them upon completion. Its capabilities include:

• Multi-step workflows: Creating reports, analyzing stocks, translating lectures into notes, and even purchasing products online.

• Tool integration: Interacting with browsers, code editors, and databases to execute tasks like web scraping or software coding.

• Background processing: Continuing to work on tasks even when users are offline.

Multi-agent architecture

At its core, Manus utilizes a structured agent loop that iteratively processes tasks in a step-by-step manner. The system delegates tasks to specialized sub-agents while acting as an executive that manages the team. This architecture enables it to resolve complex workflows by breaking them down into smaller components that can be handled by specific agents working in parallel.

Each Manus session follows a systematic process:

1. Analyze events and understand user requests

2. Select appropriate tools or APIs for the next step

3. Execute commands in a Linux sandbox environment

4. Iterate and refine actions based on new data

5. Submit results in the form of messages, reports, or deployed applications

Multi-modal processing

Manus processes textual, image, and coding materials, allowing it to:

• Generate comprehensive presentations

• Perform visual data analysis

• Automate programming tasks

• Create interactive dashboards

Real-time interaction and workflow display

A standout feature of Manus is its transparency in showing users its work process. The system displays its workflow side-by-side, demonstrating how it browses websites, takes screenshots, and updates spreadsheets in real-time. This gives users insight into its decision-making process and builds trust in its outputs.

Adaptive learning

The AI learns from user interactions, gradually customizing its outputs based on implicit preferences. For instance, it builds travel plans using a user's preferences or fine-tunes workflows for repetitive tasks, becoming more personalized over time.

Technical innovations

GAIA benchmark performance

Manus has demonstrated impressive performance on the GAIA benchmark, which evaluates AI agents' capabilities in logical reasoning, multi-modal processing, and tool usage. According to benchmark tests, Manus outperformed OpenAI's DeepResearch across all difficulty levels:

• Level 1 (basic tasks): Manus scored 86.5%, compared to OpenAI Deep Research's 74.3%

• Level 2 (intermediate tasks): Manus achieved 70.1%, slightly above OpenAI Deep Research's 69.1%

• Level 3 (complex tasks): Manus led with 57.7% versus OpenAI's 47.6%

Cloud-based execution environment

Manus operates within a controlled Linux sandbox environment where it can:

• Install software

• Run scripts

• Manipulate files

• Navigate websites

• Extract data

• Deploy applications to public URLs

Open-source roadmap

Monica plans to open-source parts of Manus's technology stack by late 2025, fostering collaborative innovation. This hybrid strategy blends proprietary breakthroughs with open-source initiatives, potentially accelerating community-driven experimentation in AI development.

Real-world applications

Manus AI has demonstrated versatility across various industries and use cases:

Business and finance

• Automates financial analysis and generates detailed reports

• Optimizes hiring processes by analyzing resumes against market trends

• Creates interactive dashboards for data visualization

• Conducts sentiment analysis on financial markets using natural language processing

Travel and planning

• Crafts detailed itineraries by analyzing budgets, weather patterns, and safety data

• Provides personalized recommendations based on user preferences

• Compares transportation options and accommodation choices

Education

• Converts lecture recordings into structured notes

• Creates interactive learning materials

• Summarizes research papers and academic resources

Development and IT

• Builds websites from concept to deployment

• Debugs code and resolves hosting issues

• Automates repetitive development tasks

How manus compares to competitors

When comparing Manus to competitors like OpenAI and Google, several distinctions emerge:

Early challenges and limitations

Despite its impressive capabilities, Manus AI faces several challenges as it navigates its early deployment:

Technical issues

Early testers have reported glitches and inconsistencies, including instances where Manus loops or gets stuck in repetitive cycles when facing complex, ill-defined tasks. The system has also experienced server overload issues similar to what DeepSeek encountered during its initial release.

Architectural questions

Investigations into Manus's architecture suggest that it heavily integrates existing models like Claude Sonnet and fine-tuned versions of Alibaba's Qwen, rather than using a unique, proprietary model. This has raised questions about whether Manus is pioneering new AI methods or cleverly orchestrating existing technologies.

Security and privacy concerns

Manus's ability to execute commands, retrieve files, and interact with external systems raises important security considerations. If not properly sandboxed, an autonomous AI with access to sensitive data could introduce unintended vulnerabilities.

Context limitations

Despite its autonomy, Manus still has limitations on the amount of data it can process at once due to its context window constraints, which affects its ability to handle extremely large or complex tasks.

Accessing manus ai

Currently, Manus is available only as an invitation-only web preview. The system is in private beta, and users require an invitation code to access it. Those interested can request access through the official platform (manus.im), though due to high demand, the waiting list is substantial—reportedly less than 1% of waitlisted users have received invites so far.

Monica has not yet announced a public release date or pricing details, though the company has indicated plans to eventually open-source aspects of the model for developer use.

Is this a "DeepSeek Moment" for AI agents?

Much like DeepSeek's R1 model changed perceptions about what was possible with reasoning models, Manus may represent a similar paradigm shift for autonomous AI agents. DeepSeek proved that strong reasoning models could be built at a fraction of the previously assumed cost, that advanced AI chips might not be as crucial as thought, and that open-source AI could compete with proprietary models.

Similarly, Manus challenges assumptions about what's required to build powerful AI agents. Based on initial discoveries, Manus operates using a combination of Claude Sonnet, Qwen fine-tunes, and modular AI agents, demonstrating that highly capable autonomous systems can be built without training massive proprietary models from scratch.

This development is particularly interesting in the context of rumors that OpenAI plans to launch advanced AI agents with subscription fees ranging from $2,000 to $20,000. If Manus delivers on its promise of low-cost, open access to autonomous AI, it could force companies like OpenAI to reconsider whether AI automation needs to be locked behind expensive paywalls.

Future implications

The emergence of Manus AI raises several important considerations for the future of work and AI development:

Productivity and workflow changes

Manus promises potential productivity gains of 30-50% across various sectors by handling repetitive tasks autonomously. This could significantly change how knowledge workers allocate their time and attention.

Job market impact

While Manus's creators emphasize that the system is meant for "augmentation as opposed to replacement," the advanced automation capabilities raise questions about potential job displacement in certain sectors.

Global AI competition

Manus represents another significant entry from China into the global AI race, following DeepSeek's impact. This continues to challenge the perception of Western dominance in cutting-edge AI development.

Ethical considerations

As AI systems become more autonomous, questions about responsibility, oversight, and governance become increasingly important. Who is accountable when an autonomous system makes decisions that have real-world consequences?

Conclusion

Manus AI represents a bold step toward truly autonomous AI agents capable of executing complex real-world tasks with minimal human intervention. While it's too early to determine whether Manus will fully deliver on its promises or overcome its early challenges, its emergence signals an important shift in how we conceptualize AI assistants.

Rather than being mere respondents in a conversation, systems like Manus are beginning to function as independent actors that can plan, reason, and act in service of human-defined goals. This transition from passive to active AI assistance could fundamentally change how we interact with technology and distribute cognitive labor.

As with DeepSeek before it, Manus's true impact may not be measured by how many users ultimately adopt the platform, but rather by how it reshapes expectations and approaches to AI development. Whether Manus becomes a widely used tool or remains a technological curiosity, it has already contributed to expanding our understanding of what's possible in the realm of autonomous AI agents.

The coming months will reveal whether Manus can overcome its early technical challenges and fulfill its potential as a transformative force in AI, or whether it will join the ranks of promising but ultimately limited AI experiments. Regardless of its ultimate fate, Manus has already succeeded in pushing forward the conversation about the future of AI autonomy.

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