Author: Zhou Zhou, Foresight News

In the past month, AI Agents have sparked a new wave in the cryptocurrency industry.

In less than a month, the market capitalization of the entire AI Agent sector reached tens of billions of dollars. Among them, Virtuals reached a market cap of $3 billion, while ai16z, Fartcoin, and others reached a market cap of $1 billion. According to incomplete statistics from Foresight News, there are at least 14 cryptocurrencies related to AI Agents that have surpassed $100 million.

Many Web3 practitioners believe that AI Agents may be one of the biggest narratives of this cycle, just like DeFi, NFTs, and the metaverse in previous cycles. So, when a brand new cryptocurrency narrative is in its early stages, how can we find the leading AI Agent projects through a good methodology? The author attempts to list ten methods for readers.

1: On-chain Revenue Method

This method is more suitable for assessing platform-type AI Agents, such as Clanker, vvaifu.fun, and Virtuals. If there are fluctuations in daily on-chain revenue or the number of on-chain transactions, such as rapid growth over several consecutive days, it may indicate that this AI Agent could have good development prospects. Conversely, it may suggest that development has stagnated.

Image Source: Dune

For example, Clanker, as a star project in the Base ecosystem, shows from on-chain data that after November 26, both the number of issued tokens, the number of traders, and on-chain revenue began to decline, and this trend was immediately reflected in the token price.

2: Developer Attention Method

A high number of stars on GitHub may indicate that more developers are paying attention to and recognizing this framework. This method is more suitable for assessing framework-type AI Agents, such as Eliza.

Search GitHub to see how many stars framework-type AI Agents have. For example, ai16z/Eliza gained 5,300 stars in less than a month. This is quite an astonishing figure.

Data Source: GitHub

As shown in the image, the developer attention for ai16z/Eliza surpassed that of Uniswap in just one month, indicating a high level of interest from developers in this framework. Another set of data for comparison: Sui currently has 6,400 stars, Solana has 13,000 stars, Ethereum has 50,000 stars, and Base has 70,000 stars.

However, it is important to note that stars on GitHub can also be manipulated, although such behavior is not widespread. Therefore, this metric can serve as an auxiliary reference for decision-making.

3: KOL Follower Count Method

One relatively certain track for AI Agents is KOLs.

Currently, well-known AI Agent-style KOLs include: Terminal of Truths (210,000 followers), aixbt (160,000 followers), Zerebro (60,000 followers), Eliza (14,000 followers), and LUNA (30,000 followers on Twitter, 500,000 followers on TikTok).

A significant difference in this round of the AI revolution is the semantic change. The author predicts that an AI Agent KOL leader will emerge, and the market cap of this leader's token may even exceed $5 billion. The change in follower count may become one of the important metrics.

4: Influential Figures Method

Prominent figures in the AI industry are continuously entering the crypto space. Notable examples include Marc Andreessen, founder of a16z (supported representative project: ai16z), and Sam Altman (supported representative project: Worldcoin). They have brought multiple billion-dollar cryptocurrencies to the crypto world. It is expected that more will follow, such as Elon Musk and his company Grok.

There are also less certain figures, such as those from Apple, Meta, TikTok, etc., like Claude, Copilot, and Gemini, which could bring something different to crypto.

Particularly noteworthy are tech giants that are researching both AI and crypto, such as Musk, Marc Andreessen, Sam Altman, and Jensen Huang. Their leadership in the tech industry often translates into influence in the crypto sector.

5: External World Breakthrough Method

If AI Agents are indeed one of the biggest narratives of this cycle, it is essential to pay extra attention to their influence on the external world. For instance, Web2 developers are attracted to Web3's AI Agent frameworks and products. As far as the author knows, Eliza is currently receiving attention from some AI practitioners outside the circle.

Products from KOLs, such as Terminal of Truths and LUNA, have also garnered attention from outsiders, with both surpassing 200,000 followers and their influence continuing to expand. It is necessary to understand and assess whether this trend will further break through barriers and impact a broader external world.

6: Leading Exchange "Listing Effect" Method

Those who participated early in Sandbox may know that some metaverse concepts skyrocketed after being listed on Binance. Leading exchanges are called leading because they need to ensure that the tokens they list can lead the market; if they are led by other exchanges, they will gradually lose their leading position.

Pay close attention to the listing information and Launchpad information from the five exchanges: Binance, Upbit, Coinbase, Bitget, and Hype, as they are in fierce competition regarding the "listing effect" this cycle.

Particularly, Coinbase and Hype are leading in the general AI Agent space in the U.S., giving them a faster information advantage.

7: Public Chain Method

Some public chains are naturally suitable for the birth of AI Agent projects, inherently lowering the barriers for AI Agent emergence. Finding a few good public chains and identifying promising AI Agent projects within them can yield significant results.

For example, Base has 70,000 developer stars, surpassing Ethereum and far exceeding Solana and Sui, making it a standout with latecomer advantages.

Coinbase itself places great importance on AI Agents and has laid out its strategy early. This will provide a significant first-mover advantage in future competition.

Solana's advantage lies in its strong meme platform, and since AI Agents heavily rely on memes to rise, this is a significant advantage for Solana.

8: AI Agent Community Method

Everyone has their own blind spots, but the power of a team is comprehensive and all-encompassing.

Establishing your own AI Agent discussion group and community, or finding one or two high-quality communities, is very important. Opportunities for AI Agents often arise in unnoticed corners, where the strength of the community is needed.

9: Track Segmentation Method

AI Agents are also divided into various tracks, such as KOL track, beautiful streamer track, investment research blogger track, meme platform track, VC track, platform track, framework track, etc.

There are many tracks within AI Agents, and not all tracks can be validated. It is necessary to find the tracks that truly have a chance to survive until the end.

10: Origin Method

Where did it all begin? Which AI Agent initiated the narrative of the entire track? It may very well be the leader of this track.

In the NFT space, CryptoPunks has always held a transcendent position, while Apes initiated a new narrative for the entire track, and Fat Penguins are among the best NFTs that combine with Web2; in the metaverse space, Sandbox and Decentraland were among the first to be listed on leading exchanges and occupy leading positions in the metaverse; Uniswap was the first to implement the concept of automated market makers in decentralized exchanges (DEX), becoming a pioneer in the market… Projects that achieve systematic innovation often capture the largest share of the track's dividends.

It will be like BTC, making you always feel it is expensive, but looking back, you realize it was indeed very cheap at that time.

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