In the past few days, @ManusAI_HQ has been trending, reportedly hailed as the 'truly universal AI Agent' product, claiming it can think independently, plan, and execute complex tasks, ultimately delivering complete results.

From the video demo, whether it’s screening resumes, researching stocks, or purchasing real estate, the operational experience of Manus is indeed impressive. But aside from the unemployment anxiety within social circles, what exactly is it? What insights can it bring to the integration of Web3 and DeFi (i.e., DeFai)?

What is Manus?
Manus is developed by the Chinese AI startup http://Monica.im and is positioned as the next generation autonomous AI Agent. Similar to the Operator launched by OpenAI a month ago, Manus can also complete tasks such as restaurant bookings and shopping in the browser.
Compared to the Operator, which relies on a single model-driven approach and tool calls, Manus's core innovation lies in its multimodal large model architecture and 'multi-signature system'.

Specifically, Manus mimics the human PDCA cycle (Plan-Do-Check-Act), breaking tasks down into multiple stages completed collaboratively by different large models:
Planning Stage: One model is responsible for understanding the task and formulating an execution plan;

Execution Stage: Another model calls tools or interacts with the environment according to the plan;

Checking Stage: A model then verifies the results and adjusts actions.

This division of labor not only reduces the risk of errors from a single model but also enhances overall efficiency.

The 'multi-signature system' is its highlight — by cross-verifying decisions across multiple models, it ensures the reliability and consistency of outcomes. This mechanism resembles a blockchain multi-signature wallet, which explains why some link it to the decentralized concept of Web3.

In contrast, while the Operator is powerful, users still need to intervene in key decisions, limiting its autonomy. Manus's multimodal collaboration and verification mechanisms take it a step further in handling complex tasks, creating an 'extraordinary' experience at least.

Advantages and limitations of Manus: The gap from Demo to reality
From the Demo, Manus performs impressively in Web2 scenarios. For instance, it can autonomously browse the web, analyze data, and generate reports, even handling unstructured user commands.
This 'Less Structure, More Intelligence' philosophy means it has a higher fault tolerance for prompts, requiring users to provide less precise guidance. However, this does not imply it has reached a revolutionary level.

Its core challenges lie in task complexity and real-time performance:
Fault tolerance for complex tasks: Can Manus consistently deliver high-quality results when faced with non-standardized inputs? How is success defined?

Real-time bottlenecks: In dynamic environments (such as financial transactions), multi-model collaboration may miss opportunities due to data transmission delays.

Taking the Web3 DeFai scenario as an example, suppose Manus needs to execute on-chain arbitrage transactions:
1) The Oracle layer model must collect on-chain data in real-time and analyze prices;

2) The decision layer model formulates trading strategies based on the data;

3) The execution layer model completes the trading operation.

It seems perfect, but the ever-changing nature of the on-chain environment (such as fleeting arbitrage windows) places high demands on the real-time nature of multimodal collaboration. In contrast, the data update frequency in Web2 scenarios (like e-commerce order processing) is lower, with less pressure for dynamic balance. Therefore, Manus is currently more suitable for repetitive, information-intensive Web2 tasks, while in Web3 financial scenarios, it still needs to resolve more underlying issues.

Although Manus has not fully adapted to Web3, its design philosophy provides valuable insights for the development of DeFai. For a long time, many DeFai projects have attempted to rely on a single AI model for autonomous decision-making, a somewhat naïve approach that often proves impractical in financial scenarios. Manus’s multimodal collaboration and multi-signature mechanism correct this misconception, pointing towards a more realistic direction — true DeFai requires a systematic multi-agent framework.

Envision a mature DeFai ecosystem:
Oracle Agent: Responsible for on-chain data collection, verification, and real-time monitoring, forming a reliable data source;

Decision Agent: Conducts risk assessment and strategy formulation based on data;

Execution Agent: Optimizes Gas costs, handles cross-chain states, and completes transactions.

These agents need to work together under a unified resource scheduling and fault tolerance mechanism to cope with the high complexity and uncertainty of financial scenarios. The 'LLM OS' (Large Model Operating System) concept proposed by Manus may well be a prototype of this framework. It no longer pursues the 'almighty' nature of a single model but achieves overall intelligence through division of labor and verification.

The practical significance and future potential of Manus:
In the Web2 domain, the emergence of Manus could trigger a wave of transformation. Repetitive tasks such as clerical work and information filtering will be replaced by AI, and the anxiety within social circles is not unfounded. However, in the Web3 domain, it resembles a 'touchstone', validating the feasibility of multimodal AI Agents while exposing shortcomings in real-time performance and complexity.

In the future, if Manus can further optimize collaborative efficiency and enhance real-time data processing capabilities, it may become a catalyst for DeFai scenarios. But until then, it remains 'iterative innovation' rather than 'disruptive revolution'. For Web3 practitioners, the value of Manus lies in inspiring ideas: the true DeFai revolution should not stop at breakthroughs of a single AI but should build a powerful, collaborative agent ecosystem.

In summary, Manus is a bold attempt in the field of AI Agents. Its potential in Web2 has already begun to shine, and in the journey of Web3 DeFai, it may just be getting started. What do you think about the future of this emerging AI Agent?