Author: Haotian, Source: Author's Twitter @tmel0211
Sharing a simple overview of the investment logic for different categories of "targets" for AI Agents:
1) Single AI: Strong user perception, vertical application scenarios, short product verification cycle, but limited ceiling. Investments must be based on the premise of experiencing the application. For example, some new strategy analysis on single AI, no matter how much others boast, cannot surpass actually trying it out; such as: $AIXBT $LUNA;
2) Frameworks and Standards: Higher technical threshold, grand vision and goals, the degree of market (developer) adoption is crucial, and the ceiling is very high. Investments require comprehensive examination of the project's technical quality, founder background, narrative logic, and application landing; such as: $arc, $REI, $swarms, $GAME;
3) Launchpad Platforms: Well-designed Tokenomics, strong ecological synergy effects, will catalyze a positive flywheel effect, but prolonged lack of blockbusters will severely damage market expectations. It is recommended to consider following the uptrend when market enthusiasm is high and innovation is frequently replaced, and to choose to wait and see when the collective downtrend occurs. For example: #Virtual, $MetaV;
4) DeFi Trading AI Agents: The Agent's landing in the Crypto Endgame form has immense imaginative space, but there are uncertainties in intent matching, Solver execution, and trading result accuracy. Therefore, it is essential to experience it first before deciding whether to follow up; such as: $BUZZ, $POLY, $GRIFT, $NEUR;
5) Creative and Distinctive AI Agents: The sustainability of the creativity itself determines everything, with high user stickiness and IP value attributes, but the initial momentum often affects the subsequent market expectation height. It requires the team's continuous update and iteration capabilities; such as: $SPORE, $ZAILGO;
6) Narrative-Oriented AI Agents: It is necessary to pay attention to whether the project team's background is upright, whether they can continuously launch iterative updates, and whether the whitepaper's plans can be gradually implemented. The key is whether they can maintain the leading position in a narrative cycle; such as: #ai16z $Focai;
7) Business Organization Promotion AI Agents: It is more about testing the coverage of B2B resources, the progress of product and strategy promotion, and the continuous refreshment of new Milestone imagination space. Of course, the actual platform data indicators are also crucial; such as: #ZEREBRO, #GRIFFAIN, $SNAI, $fxn
8) AI Metaverse Series AI Agent Platforms: AI Agents do have advantages in promoting 3D modeling and metaverse application scenarios, but the commercial vision ceiling is too high, hardware dependence is large, and the product cycle is long. It is necessary to pay attention to the project's continuous iteration and landing, especially the manifestation of "practical" value; such as: $HYPER, $AVA
9) AI Platform Series: Whether it's data, algorithms, computing power, or reasoning fine-tuning, DePIN, etc., they all require a huge demand-side market. Undoubtedly, AI Agents are a market with huge potential to be unleashed, so how to interface with AI Agents is crucial; such as: @hyperbolic_labs, @weRoamxyz, @din_lol_, @nillionnetwork;
Note: The above is an incomplete summary of AI Agent categories, and the tickers mentioned are for research and learning purposes only, not as investment recommendations. DYOR!
