AI Investor Timo Shares Investment Strategies in the Web3 AI Field

Recently, an investor focused on the AI field, Timo, shared his investment strategies and insights in the Web3 AI space. Timo is a professional AI track VC in the Web2 realm, and his trading journey in Web3 began in 2017 when he bought Bitcoin. After experiencing the ups and downs of contract trading, Timo started focusing on on-chain trading last year, exploring various areas such as inscriptions, token swaps, and pre-sales, ultimately concentrating on the zoo and AI tracks.

Timo emphasized that investing in AI assets is very different from other crypto assets, stating, "You should engage with things you can understand; if you just blindly follow the trend, you can only become someone else's liquidity in this market." His on-chain trading strategy for AI assets mainly focuses on two segments, seeking Alpha opportunities with potential returns of over ten times and higher ceilings, while strictly controlling positions, with a single coin investment not exceeding 15%. Currently, this strategy has a win rate of over 90%.

Investment Opportunities in the Web3 AI Sector

Timo believes that the development of AI in Web3 essentially follows the footsteps of Web2 AI, from technology application to narrative to talent level. He analyzed several key links of Web3 AI from the perspective of the industrial chain:

1. Protocol Layer: It is necessary to develop a bottom-layer protocol that supports intelligent interaction between Agents.

2. Model Layer: In addition to general large models, there is significant room for development in specialized domain models and technologies that reduce inference costs.

3. Data Layer: The filtering, cleaning, and labeling of high-quality data is crucial.

4. Tool Layer: The open platform allows for the invocation of various tools, which may become a potential direction.

5. Application Layer: Applications that can attract Web3 users for frequent use, such as the combination of AI and DeFi, still have significant room for development.

Two-Phase Trading Strategy

Timo's two-stage trading strategy includes two steps: fundamental analysis and technical analysis. Fundamental analysis determines whether to buy, while technical analysis decides at which position to buy.

Fundamental analysis mainly considers four aspects:

1. Narrative: Product positioning determines the project cap.

2. Control: Strongly managed markets usually have a longer lifecycle and greater imaginative space.

3. Products and Technology: The market is maturing, and pure storytelling is difficult to sustain.

4. Team Background: Look for "regular troops", verify resumes and research achievements.

Regarding the entry position, Timo suggests paying attention to the operations of market makers, as there are usually two bottoms to consider for entry.

Risk Control

To avoid mistakes, Timo emphasized two points:

1. Thorough research: Collect first-hand information, such as talking directly with developers.

2. Reasonable position entry and position management: Do not go all in, stay patient, and pay attention to market maker behavior.

AI Target Valuation

Timo proposed two valuation methods:

1. For new targets in existing tracks, use the comparable valuation method.

2. Valuate new projects through understanding.

In the profit-taking strategy, Timo suggests setting three stages of valuation targets for the project and gradually reducing positions as the targets are reached.

Suggestions for Continuous Growth

Timo made four suggestions:

1. Shrink the self-ego and see the essence of things.

2. Maintain curiosity and an open mind, and keep up with market trends.

3. Learn to review and reflect.

4. Accept opinions and doubts, and absorb beneficial external information.

Overall, Timo emphasizes that it is crucial to deeply understand the operational rules of the on-chain ecosystem before participating in Web3 AI investments. Only by fully understanding the market rules can one achieve success in this rapidly evolving field.