Written by: Shu Fen
Many people say that this round of cryptocurrency bull market lacks innovative narratives. In fact, AI is the most innovative and lasting core narrative. As of December 2024, the project with the highest return in the entire cryptocurrency market (non-on-chain) comes from the AI field - Virtuals, with a return of up to 23079%.
"The next stop of big models", "completely changing the way of life of human beings", "opening up a new era of industrial revolution"... People are not stingy in describing the importance of AI Agent. For the current development momentum and future trends of AI Agent, both retail investors and institutions are not well prepared in terms of investment cognition. There are many people around me who did not pay attention to it before, but only felt the need to understand it after the outbreak. However, the market is flooded with various information, which makes people dazzled and brings a lot of troubles. Today, I will completely sort out AI Agent. This research report will help you quickly get rid of ignorance as an entry guide to AI Agent (coin circle version)!
This article will be divided into three parts: first, an overview of the current development status of AI Agents; second, screening potential AI Agent projects and analysis; third, expectations for AI Agents and their applications in the Web3 field.
I. Basic Introduction to AI Agents
The AI Agent made its first appearance in front of the world in March 2023, with the release of a project called AutoGPT framework, which utilizes large language models to automatically break down a large task into smaller tasks and use tools to complete them.
AutoGPT shocked the world upon its release because it was the first time that processing language, creating content, logical reasoning abilities, and perceptual action technologies were extended to application scenarios. Following this, OpenAI launched a series of GPTs, and many tech companies began to layout their capabilities across application, platform, development, and operational layers to increase barriers in the next wave of ecology.
What exactly is an AI agent? How does it work? An 'agent' in Chinese means a representative. An AI agent, simply put, is a representative powered by AI technology. It does not passively execute instructions like traditional software. Its workflow is: perception module (input acquisition) → LLM (understanding, reasoning, and planning) → tool invocation (task execution) → feedback and optimization (verification and adjustment).
OpenAI defines 'AI Agent' as a system driven by LLM as its brain, capable of autonomous understanding, perception, planning, memory, and tool usage, enabling automated execution of complex tasks. Unlike traditional artificial intelligence, AI Agents have the ability to independently think and call tools to gradually achieve given goals.
Let me give an example to help everyone understand better: for instance, if you have a cold and a fever, traditional software would only tell you to see a doctor and be more cautious. If it were an AI agent, it could monitor your temperature and other health indicators, combine that with online information, help you match the right medication, request payment, and have it delivered to your home, while also writing your leave of absence for the next day. This is the magic of AI agents.
II. Analyzing AI Agent Projects
According to the latest data from Cookie.fun, as of December 30, the overall market cap of AI Agents has reached $11.68 billion, with a nearly 39.1% increase in the past seven days. This growth trend indicates a rapid growth momentum for the AI Agent ecosystem in the crypto market.
Among the current AI Agent boom, ai16z and Virtuals Protocol are undoubtedly the two most powerful representative projects. Specifically, Virtuals' ecological market value reached $5.01 billion, while ai16z is valued at $1.63 billion. Together, they account for 56.8% of the AI Agent market share, contributing more than half of the total.
From the on-chain distribution situation, Base and Solana are the two main battlefields for AI Agents. Among them, the market cap of AI Agents on Base is approximately $5.76 billion, while the market cap on Solana is $5.47 billion, together contributing 96.1% of the overall market. Other on-chain project market caps total only $920 million.
This also reflects that although the AI Agent ecosystem has rapidly emerged in the crypto market, attracting considerable attention and capital, the market structure still appears singular, primarily relying on a few leading projects for momentum. The AI Agent ecosystem remains in its early nascent stage.
Now let's analyze the current hot AI Agent ecological projects based on the current market situation, with three main standards: 1. Long-term value of the project 2. Authentic market demand 3. Cash flow income situation. After reading, if you wonder why the XXX project is not included, please revisit these three criteria for reflection. The following project views are for reference only and do not constitute financial advice.
1.Virtuals
Virtuals actually launched last year. The Virtuals protocol primarily establishes co-management for AI agents in the gaming and entertainment sectors. AI agents can tokenize and achieve co-management through blockchain, with agent functions including autonomous planning, goal achievement, environmental interaction, and on-chain wallet control.
The biggest innovation and difference of Virtuals and other Web3 AI agent protocols is that it simplifies the complexity of AI agents, providing a plug-and-play solution similar to Shopify, allowing non-AI professionals to easily deploy AI agents in gaming and consumer applications, and earn protocol revenue from AI agents through tokenization and decentralized governance.
Additionally, Virtuals has generated an AI virtual idol—AI-dol band using its AI technology principles, which has hundreds of thousands of fans on TikTok and is quite interesting.
The total supply of Virtuals tokens is 1 billion, which has now been fully released. The token distribution is as follows: 60% held by the public, 5% for liquidity pools, and 35% for the ecosystem treasury, with a maximum release of 10% each year over three years. Currently, over 30% of the tokens belong to the ecosystem fund.
From the long-term value of the project perspective, it addresses the pain point of non-AI professionals being unable to participate in the AI boom. It has a certain user base, and its token economics are relatively open and transparent, with excellent marketing. In terms of market capitalization, as the leader of the AI Agent ecosystem, this recent surge has seen almost no corrections, so there is a high probability that it will undergo significant adjustments in the future. Therefore, in the short term, the risk for Virtuals is relatively high.
2.ai16z
Although ai16z shares the same name as the well-known venture capital a16z, this project has no connection to A16Z and has not received investment from A16Z; the only link is the attention from a16z founder Marc Andreessen.
The total token supply is 1.09 billion, and the project operates as a DAO. According to its core influencer Shaw, ai16z will launch several games based on the Eliza framework in the future, and will focus more on creating a practical AI Agent investment tool, DeFi AI Agent. The founder stated that the goal of ai16z is not to create an AI robot that mimics a16z, but to outpace it in its strongest investment domain.
Let's talk about the ai16z project, which focuses on investment model AI agents. It seems no different from previous AI bots or Telegram bots. Can AI really make money through investments? This is a question mark. The most important core technology, Eliza OS, is simply a basic development built on OpenAI's capabilities. If OpenAI opens its own AI agents, how will Shaw respond?
In summary, I believe that the ai16z project merely borrowed the name from ai16z. Its long-term value lies in DeFi AI Agents, but this demand is a pseudo-demand, returning to the previous logic of AI bots, as its technical development capability relies on the open-source database of OpenAI, with average imagination.
3.SWARMS
Swarms is an AI agent multi-agent LLM framework that provides a large number of cluster architectures and seamless third-party integrations. It currently enables enterprises to easily build and manage collaboration between multiple AI agents, and under the scheduling of Swarms, they can seamlessly cooperate to complete complex business tasks. In simple terms, the users of SWARMS are enterprises, providing enterprise-level AI agent applications.
Its founder Dev is the 20-year-old Kye Gomez (source: online) who publicly claimed that OpenAI infringed upon the team's intellectual property, stole our project name, and copied the code structure and methods. Subsequently, Gomez provided a more detailed explanation: Swarms is a multi-agent framework that has been operational for nearly three years. To date, over 45 million agents are running in production environments, serving the world's largest financial, insurance, and medical institutions.
After the Swarms token was issued on December 18, it quickly surged to a market cap peak of $74.2 million on the 21st. Unfortunately, the good times didn't last long, and the market cap plummeted like a rollercoaster to the bottom, leaving only about $6 million. After that, it oscillated around $13 million until the 27th, when it began to rebound, pushing up from a low of $12 million to $30 million, and then surged nearly 3 times to close to $70 million, almost breaking the previous high.
Compared to the fantastical sky castles of the AI16Z series, if Swarms is indeed created by the 20-year-old AI genius Kye Gomez as rumored, then undoubtedly, Swarms has a strong technological barrier. Its official website has already provided efficient solutions for many enterprises, and its strength is evident.
As an open-source project, Swarms has sparked enthusiastic attention in the developer community, with GitHub stars exceeding 2.1K, gaining the wisdom and support of numerous developers. Therefore, everything accumulated by Swarms confirms the maturity and innovation of technology. Swarms possesses stronger technical capabilities and strong market demand (enterprise-level), and will stand out in the race of AI agents.
4.GRIFFAIN
Griffain is a project based on Solana—a search engine for AI agents, similar to Copilot and Perplexity. It is one of the closest projects to Agentic APP. The ultimate form of search engines in the AI era should be users directly stating their needs and AI providing results or solutions directly, rather than just providing web links. One of the catalysts for this project is its open access mechanism. As a leading agent engine, Griffain undoubtedly attracts a lot of market attention.
Currently, Solana is home to the most AI agents. In October, Goat, as an AI agent, conducted financing for humans through pumpfun. This, from a certain perspective, is an AI singularity, due to the excellent liquidity of the entire chain and the well-established AI agent developer community. It would not be an exaggeration to call Solana the most imaginative breeding ground for AI Agents on blockchain.
What Sol has done most importantly is revitalize the ecosystem using Griffain. Because bringing about a true 'Agentic app szn' requires not only AI but also the infrastructure channels. Although GriffAIn has not yet specified the specific application scenarios for its tokens, in the future, GriffAIn will connect the demand side with the Solana ecosystem. As long as it is within the existing technical framework of Solana, it can meet basic requirements, whether in targeting certain suitable tokens on Pumpfun or creating tokens. This vision has been recognized by Toly, adding a lot of imagination to the prospects of GriffAIn.
5.AIXBT
Aixbt is one of the agents created based on the Virtuals on the Base platform. It monitors Crypto Twitter and market trends using intelligent analysis tools to provide users with valuable market insights. Some analysis content is shared on Twitter, while the rest is accessible only to token holders, who can interact directly with the agent through their exclusive terminal.
Aixbt's analysis has a certain accuracy in predicting price trends, demonstrating how AI can analyze blockchain data and help traders make more informed decisions across multiple platforms and fields.
I took a look at the relevant content published by Aixbt, and my intuitive impression is that the content is very rich, covering almost all tracks, with various data at hand. Moreover, there may be potential investment opportunities in the short-term crypto market splits; for example, finding that the vapor on hype is relatively undervalued compared to similar AI launchpads. Data shows that among the 210 tokens recommended, 183 achieved profitability after Aixbt's recommendation, with a profit rate of 83%.
However, there are some shortcomings, such as the inability to fully break down complex items, and the analysis and data are still at a shallow level, unable to indicate investment opportunity risks. However, I believe it is much stronger than some current cryptocurrency KOLs.
From the perspective of long-term value of the project, Aixbt has segmented demand in its field. Users are also motivated to hold tokens to unlock more information data and price analysis. As Aixbt continues to evolve through data feeding, I believe Aixbt is the absolute king of AI intelligent agents in market predictions.
In summary, I have analyzed five hot AI Agents in the current market. According to the three points mentioned above, I believe these five projects rank from highest to lowest in terms of market capitalization potential as follows: SWARMS, GRIFFAIN, Virtuals, AIXBT, Ai16z.
III. Future Development Trends of AI Agents in the Web3 Field
For the application of AI Agents in the Web3 field, there are currently several directions worth paying attention to, which also represent future trends. One is privacy and security; AI should be designed from the outset with respect and protection for users and society as fundamental principles. But as AI learns more about us, privacy becomes increasingly blurred and fragile. Every interaction with smart devices and every piece of personal information input becomes food for AI evolution.
The importance of privacy issues lies in the fact that they are inseparable from security issues. If systems storing and processing personal data become targets of hacker attacks, it can lead to information leaks, identity theft, asset loss, and other problems. So, is there an environment that can leverage AI's powerful capabilities while protecting personal privacy? Clearly, in the Web3 field, compared to traditional methods, it can provide users with a higher level of data protection, perfectly balancing AI development capabilities and privacy protection.
Therefore, we see that many large model data storage systems are beginning to attempt to operate on the blockchain. The perfect AI soil in Web3 has attracted many AI developers in specific industries with high privacy demands, such as healthcare and finance, to ensure data security and privacy through blockchain technology.
Another important direction is computing power and data. AI Agents, especially Multi-Agent collaboration, face cost issues in development, training, and operation. For enterprises, training AI Agents requires substantial computing power, usually hundreds or even thousands of high-performance GPUs or dedicated hardware like TPUs. The cost of acquiring and using these computing resources is already high; for example, Stanford's virtual town includes 25 agents in multi-agent research. However, once the town framework was open-sourced, testing one agent would cost $20,000 in data sources per day.
In Web3, through reasonable token economics and user incentive plans, idle computing power or personal data sets can be reallocated to further reduce computing and data costs, allowing more individual users to participate in the construction of the AI industry. For example, some data platforms enable users to monetize their own data, providing low-cost data sources for AI Agents.
Finally, it is believed that AI Agents can serve as a new infrastructure for Web3, deeply integrating with other core elements and giving rise to entirely new application models, rather than simply being AI Memecoins. Currently, in the Web3 field, AI Agents can help users lower barriers and enhance experiences. Even simplifying part of the asset issuance process is meaningful.
From a macro Web3 perspective, AI Agents, as off-chain products, currently serve only as auxiliary tools for smart contracts, so there is no need to overstate their capabilities. Due to the lack of significant wealth effect narratives in the second half of this year aside from MeMe, it is normal that AI Agents have gained popularity around MeMe.
However, relying solely on MeMe cannot sustain long-term value, so if AI Agents can bring more innovative gameplay to the transaction process and provide tangible grounded value, they may evolve into a universal infrastructure tool.
