The Integration of AI and Crypto Assets: Exploring Product-Market Fit

In the field of entrepreneurship and product development, product-market fit (PMF) has always been a key concept. This idea is equally applicable to the Crypto Assets market, where project teams need to gain a deep understanding of user needs rather than simply piling up technology.

Early encryption AI projects often combine with distributed physical infrastructure (DePIN), focusing on utilizing decentralized data to train AI to avoid control by a single entity. Although this model can distribute AI profits to computing power providers, its effectiveness in attracting new users is limited.

The emergence of AI agents marks the arrival of a new phase. Compared to infrastructures like DePIN+AI, AI agents focus more on the application layer, offering stronger user attraction and better product-market fit.

The Development History of AI Agents in the Crypto Assets Field

Phase 1: Meme Coin Kickoff

AI agents initially emerged in the form of meme coins, utilizing Crypto Assets and the internet to achieve their goals. Projects at this stage mostly have simple functions, such as automatically posting tweets and replies, lacking practical applications.

Phase Two: Feature Exploration

As time goes on, AI agents begin to expand into more valuable application scenarios, including content production, investment analysis, and fund management. At this stage, AI agents gradually part ways with meme coins, forming an independent track.

Phase Three: Ecological Collaboration

AI agents begin to explore collaboration between projects, aiming to establish a more robust ecosystem. This phase emphasizes interoperability and the expansion of the ecological network, as AI agents start to generate synergies with other Crypto Assets projects or protocols.

Phase Four: Capital Management

AI agents begin to participate in higher-level value creation processes at this stage, such as fund management. They are no longer just simple tools, but intelligent systems capable of strategy design, dynamic adjustment, and market forecasting.

Future Outlook: Reshaping AI Economics

In the future, AI agents may redefine the economic relationships between distributors, platforms, and AI suppliers, creating a brand new ecosystem. This stage may involve:

1. Draw on the history of internet development to form an AI ecosystem similar to super applications.

2. Reconstruct the relationship between distributors, platforms, and AI providers through token economic design.

3. Develop into a super application entrance that integrates multiple platform economies.

Although most crypto AI agents are not yet widely used in daily life, we have reason to expect a broader development prospect for AI agents in the Crypto Assets field as technology advances and the ecosystem improves.