Web3 AI Agency's New Direction: Breaking Free from Token Speculation and Focusing on Technological Innovation and Application Implementation

Recently, after communicating with some entrepreneurs and investors, it is generally felt that everyone still maintains strong confidence in the integration of AI and Crypto Assets, but there seems to be some confusion regarding the development direction of Web3 AI agents. In response to this situation, I have organized several potential directions for AI narrative transformation for reference:

1. The advantages of AI agents engaging in speculation through token issuance no longer exist and may even trigger negative reactions. If a project lacks practical application support and relies solely on token economics for operation, it can easily be labeled as pure speculation, with little substantial connection to AI.

2. The originally expected order of the deployment of AI agents, AI frameworks, AI platforms, and decentralized physical infrastructure may undergo adjustments. As the AI agent market bubble bursts, agents may retreat to being the "carriers" after the maturity of technologies such as large model fine-tuning and data algorithms. AI agents without core technology support will struggle to stand out.

3. Some platform projects focusing on AI data, computing power, algorithms, and other services may surpass AI agents to become the market focus. Even if new AI agents are launched, agents developed by these AI platform projects may be more persuasive in the market. After all, project teams capable of operating AI platforms are often more reliable in terms of technical strength and team composition.

4. Web3 AI agents need to seek differentiated development directions and should not compete directly with Web2 teams. Web2 agents focus on practicality, while Web3 agents pay more attention to token economics. Overemphasis on low-cost deployment may lead to more asset issuance bubbles. Web3 AI agents should innovate in conjunction with blockchain distributed consensus architecture.

5. The greatest advantage of AI agents lies in "application preposition", which aligns with the logic of "fat protocol and thin application". The key is how to enrich the content of the protocol, how to mobilize idle computing power resources, and leverage distributed architecture to promote the low-cost application advantages of algorithms, activating vertical segments such as finance, healthcare, and education. At the same time, the "slimming down" of applications also needs to be achieved gradually, as functions such as AI agents autonomously managing assets, autonomous trading, and autonomous multimodal interaction need to be implemented step by step.

6. The MCP protocol in the Web2 domain and technologies such as Manus for automated execution of multimodal tasks provide inspiration for innovation in Web3. Applications suitable for Web3 can be developed directly based on these technologies, or the business scenarios of MCP can be enhanced using distributed collaboration frameworks. There is no need to pursue complete disruption; appropriate optimization based on existing products and protocols, leveraging the unique advantages of Web3, is sufficient. Whether in Web2 or Web3, both are in the process of AI large language model innovation, and what matters is the ability to truly promote the development of AI technology.