The biggest advantage of AI Agents is "application pre-positioning," which belongs to the logic of "fat protocols, thin applications."

Written by: Haotian

Recently, after talking with some entrepreneurs and VCs, a common feeling emerged: everyone remains firm in their expectations for the AI + Crypto track, but the narrative evolution of web3 AI Agents seems somewhat confusing. What should we do? I have outlined several potential shifts in the AI narrative for reference:

1) Using MEME-based token issuance for AI Agents is no longer an advantage; in fact, it has become a "taboo." If a project lacks PMF support and relies solely on a set of Tokenomics that is merely spinning its wheels, it will naturally be labeled as pure MEME speculation, just a wolf in sheep's clothing, with little relation to AI.

2) The original sequence of AI Agent > AI Framework > AI Platform > AI DePIN may be adjusted. When the Agent market bubble bursts, Agents will become the "carriers" after the core technologies like large model fine-tuning and data algorithms take shape. Without the support of core technologies, it will be difficult for an AI Agent to showcase its capabilities.

3) Some projects originally focused on AI data, computing power, algorithms, and other service platforms may surpass AI Agents to become the focal point. Even if new AI Agents are launched, those created by these AI platform projects will be more market-convincing. After all, projects capable of operating an AI platform have a more reliable team foundation and technical background than a Dev that is merely based on low-cost deployment of a framework.

4) Web3 AI Agents can no longer directly compete with web2 teams; they need to seek differentiated directions in web3. Web2 Agents focus on utility, so the logic of low-cost deployment and development platforms works, but web3 Agents emphasize Tokenomics. Overemphasizing low-cost deployment will only trigger more asset issuance bubbles. Undoubtedly, web3 AI Agents should innovate and explore in conjunction with blockchain distributed consensus architecture (detailed in my pinned article on the homepage).

5) The biggest advantage of AI Agents is "application pre-positioning," which belongs to the logic of "fat protocols, thin applications." But how should the protocol be fat? It is essential to mobilize idle computing resources and leverage distributed architecture to drive low-cost application advantages, activating more verticalized sub-scenarios in finance, healthcare, education, etc. And how should applications be thin? Allowing AI Agents to autonomously manage assets, autonomously trade intentions, and autonomously interact in multiple modalities is not something that can be achieved overnight. One cannot attempt to achieve everything at once; needs should be segmented and gradually implemented. Otherwise, the maturity standards of a DeFi scenario could take a year or two to develop.

6) The MCP protocol in the web2 domain and Manus automated execution of multimodal interactions, etc., all provide inspiration for innovation in the web3 domain. Directly extending development based on MCP + Manus to suit web3 application scenarios, or using distributed collaborative frameworks to enhance business scenarios on top of MCP, is advisable. There is no need to start by talking about disrupting everything; it is sufficient to optimize appropriately based on existing product protocols and leverage the irreplaceable differentiated advantages of web3. Whether in web2 or web3, both are part of the ongoing revolution in AI LLMs. Ideology is irrelevant; what matters is the ability to genuinely promote the development of AI technology.

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