In the past month, AI Agents have sparked a new wave of interest in the crypto industry.

Within less than a month, the market cap of the entire AI Agent sector reached tens of billions of dollars. Among them, Virtuals hit a market cap of $3 billion, while projects like ai16z and Fartcoin each achieved market caps of $1 billion. According to incomplete statistics from Foresight News, there are at least 14 cryptocurrencies related to AI Agents with a market cap exceeding $100 million.

Many Web3 practitioners have noted that AI Agents might become one of the most significant narratives of this cycle, akin to the rise of DeFi, NFTs, and the Metaverse in previous cycles. So, when a brand-new crypto narrative emerges at such an early stage, how can we identify leading AI Agent crypto projects using a robust methodology? Here, I outline ten approaches for readers to consider.

1. On-Chain Revenue Analysis

This method is particularly suited for evaluating platform-based AI Agents, such as Clanker, vvaifu.fun, and Virtuals. If there are unusual changes in metrics like daily on-chain revenue or the number of on-chain transactions—such as consistent high growth over several days—it might indicate promising development potential for that AI Agent. Conversely, stagnation in these metrics could signal that the project’s growth has plateaued.

Image Source: Dune

For instance, Clanker, a flagship AI Agent project in the Base ecosystem, exhibited a decline in several on-chain metrics after November 26. These metrics included the number of tokens issued, active traders, and on-chain revenue. This downward trend was quickly reflected in the token’s price, signaling potential challenges for the project.

2. Developer Engagement Analysis

The number of stars on GitHub can serve as an indicator of developer interest and approval of a framework. This method is particularly effective for evaluating framework-based AI Agents, such as Eliza.

To apply this method, search GitHub and check the developer engagement for framework-based AI Agents by examining their star count. For example, the ai16z/Eliza project garnered 5,300 stars in less than a month—an astonishing number that underscores significant developer interest.

Data source: GitHub

As shown in the chart above, the developer engagement for ai16z/Eliza surpassed Uniswap in just a month. This indicates a high level of interest among developers in the Eliza framework. For comparison, other notable projects have achieved the following star counts on GitHub: Sui currently has 6,400 stars, Solana has 13,000 stars, Ethereum has 50,000 stars, and Base has 70,000 stars.

However, it should be noted that stars on Github can also be brushed with data, although this behavior is not common. Therefore, this indicator can be used as an auxiliary reference for decision-making.

3. KOL Follower Count Analysis

A key sector within AI Agents is KOL (Key Opinion Leaders). Notable AI Agent KOLs include:

• Terminal of Truths: 210,000 followers
• aixbt: 160,000 followers
• Zerebro: 60,000 followers
• Eliza: 14,000 followers
• LUNA: 30,000 followers on Twitter, 500,000 on TikTok

One distinguishing feature of this AI revolution is its semantic shift. The author predicts that a leading KOL in the AI Agent space might emerge, with a token market cap potentially exceeding $5 billion. Changes in follower counts could serve as a critical metric for evaluating influence in this sector.

4. Influence of Key Figures

Several prominent figures in the AI industry have already entered the crypto space, including:

• Marc Andreessen (founder of a16z, associated project: ai16z)
• Sam Altman (associated project: Worldcoin)

These leaders have facilitated the creation of billion-dollar cryptocurrencies. Future entrants may include high-profile figures like Elon Musk with his Grok initiative.

Other companies, such as Apple, Meta, and TikTok, as well as projects like Claude, Copilot, and Gemini, may also bring new value to crypto.

Special attention should be given to tech giants exploring both AI and crypto. Influential leaders like Elon Musk, Marc Andreessen, Sam Altman, and Jensen Huang may transfer their technological leadership to the blockchain space.

5. Breaking into External Markets

For AI Agents to truly dominate this cycle, they must gain influence beyond the crypto community. Examples include:

• Eliza, which has attracted interest from AI professionals outside the blockchain space.
• KOL-driven products like Terminal of Truths and LUNA, which have gained over 200,000 followers and continue to expand their reach.

It’s crucial to assess whether this trend can further break barriers and impact a broader audience.

6. Listing Effect on Major Exchanges

The phenomenon of a “listing effect” on major exchanges cannot be ignored. For example, projects like Sandbox soared after being listed on Binance. Leading exchanges, including Binance, Upbit, Coinbase, Bitget, and Hype, strategically list tokens to maintain their market dominance.

In this cycle, Coinbase and Hype are particularly noteworthy, given their strong presence in the AI Agent space and potential information advantage in the U.S. market.

7. Blockchain Compatibility

Certain blockchains naturally lower the barriers to entry for AI Agent projects. Identifying strong blockchains and their top projects can yield significant advantages.

• Base: With 70,000 stars on GitHub, Base outshines even Ethereum and Solana, demonstrating a strong latecomer advantage. Coinbase’s early focus on AI Agents gives it a significant edge in the competition.
• Solana: Known for its success as a meme platform, Solana aligns well with the meme-driven nature of AI Agents, making it a strong contender.

8. Community-Driven Discovery

No individual can have a complete view of every opportunity, but communities can uncover overlooked possibilities. Building or joining high-quality AI Agent communities can provide valuable insights. Many opportunities arise in unobserved corners, and community collaboration is vital for identifying them.

9. Niche Sector Analysis

The AI Agent space encompasses various sub-sectors, including:

• KOL-driven platforms
• Live-streaming hosts
• Investment research bloggers
• Meme platforms
• Venture capitalists
• Frameworks
• Platforms

Not all niches will withstand scrutiny. Identifying sectors with long-term survival potential is crucial for success.

10. Origin Analysis

A promising approach is to trace the origins of the narrative. The project that kickstarted a sector often retains a leadership position.

For example:

• In NFTs: CryptoPunks holds an iconic status, while Bored Ape Yacht Club pioneered new narratives, and Pudgy Penguins excelled in integrating Web2 elements.
• In the Metaverse: Sandbox and Decentraland established leadership after early listings on top exchanges.
• In DeFi: Uniswap became a trailblazer by introducing the AMM concept to DEXs.

Systemic innovators often reap the greatest benefits, much like Bitcoin, which seemed expensive at first but proved to be incredibly valuable over time.

Disclaimer:

1. This article is reprinted from Foresight News. All copyrights belong to the original author [Zhou Zhou]. If there are objections to this reprint, please contact the Gate Learn team, and they will handle it promptly.
2. Liability Disclaimer: The views and opinions expressed in this article are solely those of the author and do not constitute investment advice.
3. The Gate Learn team translated the article into other languages. Copying, distributing, or plagiarizing the translated articles is prohibited unless mentioned.