Discussing AI Agent application: Can vertical Agent break the deadlock of track fatigue?

Comparison of the application of artificial intelligence agents between Web2 and Web3: efficiency improvement and decentralized innovation

This article discusses the application differences and future development potential of artificial intelligence agents (AI Agents) in Web2 and Web3. Web2 has widely used AI Agent to improve efficiency, covering multiple fields such as sales and marketing. Web3 has opened up new application scenarios through blockchain technology, especially in the fields of DeFi and decentralization. Web3 Agent is expected to surpass Web2 Agent by leveraging token incentives, decentralized platforms and on-chain data. Although Web3 faces challenges in the short term, its unique advantages make it expected to compete with Web2 in the medium and long term, and even reshape the industry structure.

Web2 AI Agent: Efficiency first

Many companies have integrated AI Agent into daily operations, such as sales, marketing, finance, law, etc. AI Agent automates repetitive tasks, improving efficiency and reducing costs. Web2 companies have invested heavily in AI-driven sales and marketing agents, with many Agent providers making high profits through SaaS subscriptions or pay-as-you-go models.

The following are some Web2 AI Agent application cases:

• Apten_AI: AI SMS Agent, optimize sales/marketing processes.
• Bild_AI: Read architectural blueprints, extract material/spec data and estimate costs.
• Casixty: Marketing Agent, identify Reddit hot topics and automate replying to increase brand participation.

These cases demonstrate the transformational role of AI Agent in traditional industries, achieving task automation and workflow optimization.

Web3 AI Agent: Blockchain empowerment

Web3 AI Agent not only focuses on operational efficiency, but also integrates blockchain technology to unlock new application scenarios. In the early days, Web3 Agent was mainly based on Twitter bots, but now it has been integrated with a variety of tools and plug-ins to perform more complex operations.

Some Web3 AI Agent cases:

• sendaifun: Solana AI Agent suite that supports from basic token management to complex DeFi operations.
• ai16zdao: Integrates more than 100 plug-ins, covering social media interactions, automated transactions and DeFi operations.
• Cod3xOrg, @Almanak__: No-code infrastructure that allows users to create autonomous transaction agents.
• gizatechxyz: An independent DeFi assistant customized for investors.

DeFi is the most important application scenario for AI Agent in the field of encryption. Web3 AI Agent uses on-chain data (transaction history, profit and loss, governance activities, etc.) to automate workflows and improve decision-making capabilities.

Web2 and Web3 Agent are integrated

Web2 vertical agent is also fusing with encryption native models, such as:

• virtuals_io: Launched on Solana.
• _PerspectiveAI: AI-driven fact verification, continuous improvement.
• Roboagent69: Personal assistant, booking flights, taxis, etc.
• HeyTracyAI: AI-driven sports comments and analysis.

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

Competitiveness of Web3 AI Agent

In the short term, the Web3 team faces challenges in product market matching and user adoption. However, in the medium and long term, the Web3 model has the following advantages:

• Community-driven growth based on token incentives and consistency of interests.
• Global liquidity and accessibility, decentralized platforms lower the threshold for adoption.

Key Application Scenarios

• DeFAI: Abstraction layer, automated transaction agent, and pledge/lending solutions.
• Research and Inference Agent: AI-driven research assistant, analyzing data and generating actionable insights.
• Data-driven AI Agent: Drive decision-making and execution with on-chain and social data.

Conclusion

Despite the market's pullback, the Web3 AI Agent has great potential. By combining token incentives, decentralization and on-chain data integration, Web3 AI Agent is expected to surpass Web2 products and even reshape 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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