AI Investor Timo Shares Web3 AI Investment Strategies

At a recent Web3 networking event, AI investor Timo shared his investment experiences and insights in the Web3 AI field. Timo focused on primary market investments in the AI sector during the Web2 era, began engaging with cryptocurrencies in 2017, and after experiencing the ups and downs of contract trading, started focusing on on-chain trading, especially related to AI projects, since early last year.

Web3 AI Investment Strategies

Timo's on-chain AI trading strategy mainly focuses on two-stage market trends, looking for projects with potential returns of over ten times. He emphasizes the importance of position management, with no more than 15% invested in a single project. This strategy currently has a success rate of over 90%.

In addition to on-chain transactions, Timo also holds a large Beta position on exchanges, including mainstream tokens such as BTC, ETH, and SOL.

AI Targets Worth Attention

Timo believes that the development of AI in Web3 basically follows the trend of Web2 AI. He analyzed several noteworthy directions from the perspective of the industry chain:

1. Protocol Layer: Achieve intelligent cross-platform interaction between Agents.
2. Model Layer: Develop specialized models for specific domains, such as Solana-specific models.
3. Data Layer: Provides high-quality data cleaning and labeling services.
4. Tool Layer: Build an open platform that allows the invocation of various tools.
5. Application Layer: Develop high-frequency applications that attract Web3 users, such as the combination of AI and DeFi.

Suggestions for Two-Stage Trading Operations

Timo suggests that when conducting a two-stage transaction, one should first analyze the fundamentals and then analyze the market conditions. Fundamental analysis includes four aspects:

1. Narrative: Focus on projects that users frequently use and that can tap into liquidity or infrastructure.
2. Control the fund: prioritize selecting projects with strong market makers.
3. Products and Technology: Group analysis, some look at the code, some experience the product.
4. Team Background: Look for "regular troops", verify resumes and research achievements.

Regarding the position for building a position, Timo suggests paying attention to the timing when market makers accumulate, which is usually a good entry point.

Avoid Trading Errors

Timo emphasized two points:

1. Conduct thorough research: Obtain firsthand information, such as directly conversing with developers.
2. Reasonable position building and position management: Stay patient, do not rush to fill your positions, and do not overly rely on technical analysis.

AI Project Valuation Methods

Timo proposed two valuation methods:

1. Benchmark Valuation Method: Suitable for new projects in existing sectors, referencing the market capitalization of leading projects.
2. Cognitive Valuation Method: Applicable to brand new projects, based on individual judgment of the project's potential.

Regarding profit-taking, Timo suggests setting three target price levels and gradually reducing positions in stages.

Continuous Growth Suggestions

Timo shared four personal growth tips:

1. Shrink the ego and view things objectively.
2. Maintain curiosity and an open mindset to adapt to market changes.
3. Learn to review and reflect to avoid repeating mistakes.
4. Accept others' opinions and doubts, and absorb valuable suggestions.

Finally, Timo emphasized the importance of understanding market rules and suggested participating in trading only after fully understanding the on-chain ecosystem.