Author: Haotian
A simple sharing of investment thinking logic for various categories of AI Agent 'targets':
1) Individual AI: Strong user perception, vertical application scenarios, short product validation cycles, but the ceiling is limited. Investments must be based on the premise of experiential applications; for example, some new strategy analysis individual AI, no matter how much others brag, is no substitute for hands-on practice; for example: $AIXBT, $LUNA;
2) Framework and Standards: High technical barriers, grand vision and goals, the degree of market (developer) adoption is crucial, and the ceiling is very high. Investments must be based on comprehensive assessments of project technology, founder background, narrative logic, and practical application; for example: $arc, $REI, $swarms, $GAME;
3) Launchpad Platforms: Complete tokenomics, strong ecological synergy effects, will generate positive flywheel effects, but if there are no hot products for a long time, it will severely damage market expectations. It is recommended to consider following the upward trend when market enthusiasm is high and innovations are frequently replaced, and to observe during collective declines. For example: #Virtual, $MetaV;
4) DeFi Trading AI Agents: Agents are landing on the endgame form of Crypto, with immense imaginative space, but there are uncertainties in intent identification, Solver execution, and trading result accuracy, so it is essential to experience before deciding whether to follow up; for example: $BUZZ, $POLY, $GRIFT, $NEUR;
5) Creative and Distinctive AI Agents: The sustainability of the creativity itself determines everything, high user stickiness, and has IP value attributes, but the initial momentum often affects the later market expectation height, which tests the team's ability for continuous updates and iterations; for example: $SPORE, $ZAILGO;
6) Narrative-Driven AI Agents: Attention must be paid to whether the project team background is upright, whether they can continuously launch iterative updates, and whether the white paper's plans can gradually land, the most crucial thing is whether they can maintain a leading position in a round of narratives; for example: #ai16z, $Focai;
7) Business Organization Promotion AI Agents: It tests the coverage of resources on the B-end projects, the advancement degree of products and strategies, and the continuous refreshing of new milestone imaginative space. Of course, actual platform data indicators are also crucial; for example: #ZEREBRO, #GRIFFAIN, $SNAI, $fxn
8) AI Metaverse Series AI Agent Platforms: AI Agents have advantages in promoting 3D modeling and metaverse application scenarios, but the commercial vision ceiling is too high, hardware dependence is significant, and product cycles are long. Continuous iteration and practical implementation of the project should be monitored, especially the emergence of 'practical' value; for example: $HYPER, $AVA
9) AI Platform Series: Whether it's data, algorithms, computing power, or inference fine-tuning, DePIN, etc., it all belongs to the 'consumer-grade' market, which requires the introduction of a large demand-side market. Undoubtedly, AI Agents are a market with explosive potential, so how to connect with AI Agents is crucial; for example: @hyperbolic_labs, @weRoamxyz, @din_lol_, @nillionnetwork;
Note: The above is only an incomplete summary of AI Agent categories. The listed Tickers are for research and learning reference only and should not be considered investment advice. DYOR!
