Projects with application logic that is not closed-loop and lack clear use cases are hard to escape the fate of rapid demise.
In contrast, the design philosophy of @Surf_Copilot demonstrates the beauty of theoretical self-consistency and closed loops, with its core logic summarized as "Discovery → Research → Trading."
- Theoretical Closed Loop: Discovery → Research → Trading
Discovery: By utilizing on-chain trading indicators and social media signals, it provides users with a window to discover early high-quality projects. For example, its "Smart Account Follow" indicator can accurately capture the attention trends of high-quality X accounts towards early projects.
Research: Relying on its self-developed Cyber AI model, it integrates multi-dimensional information sources such as CoinGecko Terminal, RootData, curated X information streams, and on-chain data to generate high-quality research reports.
Trading: Through the AI trading assistant, Surf allows users to generate trading instructions in simple natural language.
From a theoretical perspective, Surf's logical closed loop progresses layer by layer, exhibiting a high degree of self-consistency.
- Practical Experience: Potential and Unresolved Issues
On the practical side, after spending over $200 to purchase a Surf Pro annual subscription and experiencing it, my feelings are:
First, the quality of the research reports is very high and comprehensive. In addition to the usual project introductions, team backgrounds, financing information, and related news, it also covers market cap estimates, social media indicators, and the likelihood of Binance spot listings, making it very practical.
Second, the AI responses are accurate but slow in output. Compared to general AI models, Cyber AI shows higher accuracy in handling unique terminology and complex data in the crypto field, but the lag in generation speed affects user experience. Improvement is hoped for.
Third, AI-assisted trading is theoretically feasible, but there are still many issues at present. On one hand, security remains a concern in users' minds; on the other hand, the transition from traditional trading habits to an AI-driven model requires time and guidance. How to cultivate user trust and habits while ensuring security is a challenge that Surf needs to overcome further.
Lastly, I hope that the Surf "Discovery" section can quickly launch more projects, and the evaluation dimensions can be more diverse; this is the feature I look forward to the most.
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