Dialogue with trader Timo: After $Trump, does Ai Agent still have a ...
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Introduction
The following text is compiled from the series Twitter Space #DialogueTraders, hosted by FC, founding partner of SevenX Ventures. This episode’s guest: Timo, AI investor. In Web2, Timo is a VC that specializes in investing in the primary market AI track and has invested in many domestic AI companies working in different directions. As for Web3, his trading journey started with buying Bitcoin in 2017. In 2019, he played with contract rollovers, with the highest floating profit of tens of millions, but lost most of it in several liquidations. He started playing with the chain at the beginning of last year, and tried inscriptions, currency conversion, and pre-sales, and then the zoo and AI.
Trading Strategy
Timo's strategy for trading AI targets on the chain can be summarized as playing the second stage, that is, looking for Alpha with a potential return of more than ten times and a relatively high upper limit, while doing a good job of position management, and investing no more than 15% in a single coin. So far, the winning rate of this strategy is over 90%. In addition to looking for Alpha on the chain, Timo's large Beta positions are all placed in exchanges, including BTC, ETH, SOL, DOGE, PEPE, and AAVE.
Web3 AI Development
In general, Web3 AI is actually following Web2 AI, from the application of technology, to narrative, to the level of talent, so the trend of Web3 AI can basically refer to the development of Web2 AI. Currently, many models are general-purpose large models that know a little bit about everything, but not too much. There are many opportunities in this field, especially in training the model with proprietary data and improving the inference cost of the model.
Application Layer in Web3
In Timo's definition, the application layer is actually a variety of AI Agents. The focus in Web3 is on applications that can attract the attention of Web3 users and make them use them frequently. The second stage gameplay involves analyzing the fundamentals and then analyzing the market to determine the position to buy. Timo suggests forming a team for analysis and emphasizes the importance of obtaining first-hand information from DEVs.
Valuation and Profit Taking
Valuation in the AI market can be done using benchmark valuation methods for existing tracks or through cognition for completely new projects. Timo's method for stopping profits involves setting three valuations: the valuation of the first stage, the valuation of the second stage, and the final valuation. He also emphasizes the importance of taking profits based on individual acceptance of profits and drawdowns.
Conclusion
To conclude, Timo advises traders to stay curious, open-minded, and to care about the basic capabilities of a project when doing the second stage of trading. It is important to accept missed opportunities and follow your own trading system.
