Workshop

The Application and Exploration of AI Agent Technology in the Web3 Field Recently, a general-purpose AI Agent product called Manus has attracted widespread attention. As an AI agent capable of independent thinking, planning, and executing complex tasks, Manus demonstrates unprecedented versatility and execution power, providing new ideas and inspiration for the development of AI Agents. With the rapid development of AI technology, AI Agents, as an important branch of artificial intelligence, are gradually transitioning from theory to practice and showing great application potential across various industries, including the Web3 sector. The basic concept of AI Agent AI Agent is a computer program that can autonomously make decisions and execute tasks based on the environment, input, and predefined goals. Its core components include: -

DeFAI: The new rise point of AI Agent At the beginning of this year, AI Agent projects on the blockchain showed a rapid rise. Some well-known projects such as Virtuals and ai16z reached a market capitalization of several billion dollars at one point, while the market capitalization of AI Agent framework projects like ARC and Swarms also exceeded 600 million dollars. The market capitalization of DeFAI projects such as BUZZ and Grift touched 200 million dollars. This trend even attracted traditional Web2 AI Agent projects like Pippin and AIOS to venture into the blockchain field. However, with the change in market sentiment, the liquidity of AI Agent tokens has rapidly decreased. The sudden rise of DeepSeek has further burst the AI bubble. The market capitalization of Virtuals and ai16z has significantly shrunk, and other AI Agent tokens have generally declined.

Crypto Market Weekly: New Opportunities in the AI Sector, Trump's Policies Trigger Market Fluctuation This week, the crypto market has shown wide fluctuations, with the market sentiment index dropping to 10%, entering the extreme fear zone. The market capitalization of stablecoins continues to grow, indicating that institutional funds are still entering. Trump's failure to timely introduce cryptocurrency-related policies after taking office has raised market concerns. Although Trump later issued the cryptocurrency bill and repealed SEC SAB-121, it has not significantly boosted market sentiment. The DeFi sector performed well, with TVL increasing by 0.56% to $53.8 billion. This is mainly due to the rise in the prices of underlying assets and project incentive points, leading to a general increase in on-chain APY. Projects like Sumer.money and Meteora saw significant TVL growth, as investors refocused on the fundamental returns of DeFi. The AI sector is influenced by Trump's $500 billion AI infrastructure plan, with a total market value reaching 41 at one point.

The alts market has entered a period of stagnation; how should investors respond? The cryptocurrency market has been sluggish since the beginning of this year, and this trend has affected not only niche alts on exchanges but also significantly impacted on-chain coins that performed well in the fourth quarter of 2024. Taking AI-related tokens as an example, the decline since 2025 is as follows: - Virtual down 79.2% - Ai16z down 85.5% - AIXBT fell by 68% - Griffain dropped 80.3% - Buzz dropped 72.4% - Fartcoin dropped 67.5% - ARC dropped 62% - Swarms fell by 45% In less than three months, this once highly regarded project in the field has seen a decline of up to 80%. Although it cannot yet be concluded that this track has failed,

Exploring the Application of AI Agents in the Web3 Field: From Manus to MCP Recently, a globally first universal AI Agent product, Manus, has attracted widespread attention in the tech circle. Developed by a Chinese startup, the product saw a hot scene with a shortage of invitation codes on its launch day. As a universal AI Agent, Manus demonstrates the ability to think independently, plan, and execute complex tasks, providing new ideas for AI Agent development. An AI Agent is a computer program capable of making autonomous decisions and executing tasks based on the environment, inputs, and predefined goals. Its core components include large language models, observation and perception mechanisms, reasoning and thinking processes, action execution, and memory retrieval functions. The design patterns of AI Agents mainly have two development routes: one emphasizes planning ability, while the other emphasizes reflective ability. In the Web3 field