AI Agent Various types of investment thinking logic for targets

Simply share the investment thinking logic of AI Agent’s various ‘targets’ by category:

1. Single AI: strong user perception, vertical application scenarios, short product validation cycle, but limited ceiling, investment must be based on the premise of experience application, for example, some new strategy analysis single AI appears, no matter how much others boast, it is not as good as actual operation once; such as: $AIXBT $LUNA ;

2. Frameworks and standards: high technical threshold, grand vision and goals, the degree of market (developer) adoption is crucial, and the ceiling is very high. Investment should be based on a comprehensive investigation of the project’s technical quality, founder background, narrative logic, application landing, etc.; for example: $arc, $REI, $swarms, $GAME;

3. Launchpad Platform: With a sound tokenomics system and a strong collaborative ecosystem, it will stimulate a positive cycle. However, if there is no popular product for a long time, it will seriously damage the market expectation. It is recommended to observe the market when it is in high heat and innovation is frequent. When the collective decline occurs, it is advisable to wait and see. For example: #Virtual, $MetaV;

4. DeFi trading AI Agent: The Agent landing in the Endgame form of Crypto has great room for imagination, but there are uncertainties such as intent identification and matching, Solver execution, accuracy of trading results, so be sure to experience it first before deciding whether to follow up; for example: $BUZZ, $POLY, $GRIFT, $NEUR;

5. Creative Featured AI Agent: The sustainability of creativity itself determines everything. It has high user stickiness and IP value. However, the initial potential often affects the high market expectations in the later stage, which tests the team’s ability to continuously update and iterate; for example: $SPORE, $ZAILGO;

6. Narrative-oriented AI Agent: It is necessary to pay attention to the integrity of the project team background, whether it can continue to launch iterative updates, whether the plan in the whitepaper can gradually be implemented, etc. The most crucial point is whether it can maintain a leading position in a round of storytelling; for example: #ai16z $Focai;

7）Business organizations promote AI Agent: It is a test of the coverage of B-end project resources, the progress of product and strategy, and the continuously refreshing new Milestone imagination space. Of course, actual platform data indicators are also crucial; such as: #ZEREBRO 、 #GRIFFAIN、$SNAI、$fxn

8. AI Metaverse Series AI Agent Platform: AI Agent promotes 3D modeling and metaverse application scenarios indeed have advantages, but the commercial vision has a high ceiling, significant hardware dependency, long product cycle, and attention should be paid to the continuous iteration and implementation of the project, especially the manifestation of ‘practical’ value; for example: $HYPER, $AVA

9. AI Platform series: Whether it’s data, algorithms, computing power, inference fine-tuning, DePIN, etc., they all require a large demand-side market in the ‘consumer-grade’ market. There is no doubt that AI Agent is a potential market with explosive potential, so how to connect with AI Agent is crucial; for example: @hyperbolic_labs, @weRoamxyz, @din_lol_, @nillionnetwork;

Note: The above is only a partial summary of AI Agent categories, and the examples listed for Ticker are for research and learning reference only, not as investment advice, DYOR!