The AI ​​track is a little tired, will the vertical Agent break the deadlock?

Web3 vertical AI agent: potential beyond Web2

This article discusses the application differences between AI agents in Web2 and Web3 and the future potential of Web3 agents. Web2 has widely used AI agents to improve efficiency, covering sales, marketing and other fields, and has achieved significant cost reduction and efficiency improvement. However, Web3 has given AI agents new application scenarios by integrating blockchain technology, especially in the DeFi field.

Web3 agents have the potential to surpass Web2 agents using token incentives, decentralized platforms and on-chain data. Although Web3 agents are currently facing challenges in market adoption and profit model, their unique decentralized advantages and community-driven growth model make it expected to compete with Web2 in the medium and long term, and even reshape the industry landscape.

Web2 AI agent application case:

Many companies have applied AI agents to their daily operations, such as:

• Apten_AI: AI-based SMS agent for sales and marketing.
• Bild_AI: Read architectural blueprints, extract material and specification data, and estimate costs.
• Casixty: Marketing agents, identify Reddit hot topics, automate replying, and increase brand participation.

These cases demonstrate the transformation role of AI agents in traditional industries, realizing task automation and workflow optimization.

Web3 AI agent: more than just chatbots

Web3 agents are no longer limited to simple chatbots, but integrate with various tools and plug-ins to perform more complex operations:

• sendaifun: Solana AI Intelligent Suite supports from basic token management to complex DeFi operations.
• ai16zdao: Integrates over 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 promising application area for Web3 AI agents. Agents not only simplify user experience, but also use on-chain data to create new opportunities. The structured data provided by blockchain (transaction history, governance activities, etc.) enables AI to analyze data, automate workflows, and improve decision-making capabilities.

The integration of Web2 vertical agent and encryption native model:

The launch of virtuals_io on Solana is a typical case. For example:

• _PerspectiveAI: AI-driven truth verification tool, continuous improvement.
• Roboagent69: Personal assistant, booking flights, taxis, etc.
• HeyTracyAI: AI-driven sports reviews and analysis.

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

Competition between Web3 AI agents and Web2 startups:

In the short term, Web3 intelligentsia faces challenges in market acceptance and profitability. But in the long run, the Web3 model has the following advantages:

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

The rise of open source AI has also accelerated the integration of encryption and AI.

Key application scenarios for encrypting native AI agents:

• DeFAI: Abstraction layer, automated trading agent, and pledge/lending solutions.
• Research and reasoning agent: AI-driven research assistant that analyzes data and generates actionable insights.
• Data-driven AI agent: Utilize on-chain data and social data to drive independent decision-making.

Conclusion:

Although the market has experienced a pullback, the fundamentals of Web3 agents have gradually become clear. Web2 vertical agents have proven their value, while Web3 agents have great potential. By combining token incentives, decentralization and on-chain data integration, Web3 agents are expected to surpass similar products in Web2. The key lies in whether the Web3 agent can achieve a adoption rate comparable to Web2 and reshape the industry landscape. In the future, the boundaries between Web2 and Web3 vertical AI agents will become increasingly blurred, and teams that successfully integrate the advantages of both will lead the next generation of digital economy.

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