The track is cold, can the AI ​​Agent in the vertical field break the deadlock?

Web3 Vertical AI Agent: Subvert tradition and reshape the industry structure?

This article discusses the application differences of AI Agent in Web2 and Web3 and the future potential of Web3 Agent. Web2 has widely used AI Agent to improve efficiency, covering sales, marketing and other fields, and has achieved significant economic benefits. Web3 Agent combines blockchain technology to open up new application scenarios, especially in the DeFi field. It demonstrates potential beyond Web2 Agent through token incentives, decentralized platforms and on-chain data analysis. Although Web3 Agent is currently facing challenges, its unique advantages make it expected to compete with Web2 in the medium and long term, and even reshape the industry landscape.

Web2 AI Agent: Efficient automation assistant

Many companies have applied AI Agent to daily operations, such as sales, marketing, finance, etc., to achieve automated task processing, significantly improving efficiency and reducing costs. Web2 companies have invested heavily in AI-driven sales and marketing agents, and Agent providers have also made huge profits through SaaS subscriptions or a fee-based model for usage.

The following are some application cases of Web2 AI Agent:

• Apten_AI: AI SMS Agent, optimize sales/marketing processes.
• Bild_AI: Read the building blueprint, extract the data and estimate the cost.
• Casixty: Marketing Agent, identify Reddit hot topics and automate responses to increase brand participation.

Web3 AI Agent: surpass efficiency and unlock new value

Web3 AI Agent not only focuses on improving efficiency, but also integrates blockchain technology into it to unlock new application scenarios. At first, most Web3 Agents were limited to simple Twitter bots, but now they are integrated with a variety of tools to perform more complex operations.

Some Web3 AI Agent cases:

• sendaifun: Solana AI Agent suite supports from base token management to complex DeFi operations.
• ai16z dao: Integrates numerous plug-ins to cover social media interactions, automated transactions and DeFi operations.
• Co d3 xOrg, @Almanak__: No-code infrastructure, supports users to create independent transaction agents.
• gizatechxyz: Self-contained DeFi assistant specially customized for investors.

DeFi field is the most promising application scenario for Web3 AI Agent. Agent uses on-chain data (transaction history, governance activities, etc.) for analysis, automates workflows and optimizes decisions.

Fusion of Web2 vertical agent and cryptographic native model

Web2 vertical agent is also fusing with cryptographic native model, for example:

• _PerspectiveAI: AI-driven fact-checking agent, continuously improving through community feedback.
• Roboagent 69: Personal Assistant Agent, you can book flights, taxis, etc.
• HeyTracyAI: AI-driven sports review and analysis Agent.

These agents usually use token gating mechanism, and users need to pledge tokens to obtain advanced permissions.

Web3 AI Agent's competitiveness and future prospects

In the short term, the Web3 team faces challenges in product market compatibility and user adoption. But in the medium and long term, the Web3 model has significant advantages:

• Community-driven growth: Through token incentives and interest alignment.
• Global Accessibility:Decentralized and unmanaged platforms lower the threshold for use.

In addition, the rise of open source AI has also accelerated the integration of encryption and AI.

Key application scenarios:

• DeFAI: Improve the efficiency of DeFi infrastructure.
• Research and Reasoning Agent: AI-driven research assistant, analyzing data and generating actionable insights.
• Data-driven Agent:Use on-chain and social data to make independent decisions.

Conclusion:

Although the market has experienced a pullback, the Web3 AI Agent has great potential. By combining token incentives, decentralization and on-chain data integration, Web3 Agent is expected to surpass similar products in Web2 and even redefine the industry landscape. In the future, the boundaries between Web2 and Web3 Agents may be blurred, and teams that successfully integrate the advantages of both will lead the next generation of digital economy.

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