Author: Kevin, BlockBooster Researcher
The term 'AI Agents' comes from OpenAI's roadmap. Sam Altman has divided the capabilities that AI should possess into 5 parts, the third of which is the 'AI Agent' that will be frequently encountered in the next few years.
What an AI Agent can do is self-learn, make decisions and execute tasks. Of course, according to the level of intelligence and capability, Stuart Russell and Peter Norvig have divided AI Agents into 5 directions in the book 'Artificial Intelligence: A Modern Approach':
Simple Reflex Agents: Only respond to the current state.
Model-Based Reflex Agents: Consider historical states in the decision-making process.
Goal-Based Agents: Focus on planning and finding the best path to achieve a specific goal.
Utility-Based Agents: Aim to weigh benefits and risks to maximize utility.
Learning Agents: Continuously learn and improve through experience.
So, where are the AI Agents currently in the market or industry positioned? What type of Agent are they?
OpenAI's o1 has reached Level 2 of artificial intelligence. In my opinion, the AI Agents in the industry are currently between Level 2 and Level 3, i.e., Level 2.5. This does not mean that the Agents in the industry have surpassed OpenAI, in fact, the web3 Agents are still at the GPT wrapper stage. So why is it Level 2.5? Because through human or programmatic intervention, temporarily called an intermediary, the combination of the GPT wrapper and the intermediary has formed a form that is not entirely convincing, but has objective initiative. It is an extension of the application of a certain direction of the OpenAI model. In terms of what the Agent can do, it is the most basic simple reflex agent. Some of these Agents will consider historical states, but they require active input. The Agent can only complete learning by constantly being fed data, which is a passive model training method, far from reaching the state defined by Level 3. The latter three types of Goal-Based, Utility-Based, and Learning Agents have not yet entered the market. Therefore, I believe that the current AI Agents are still in the early stage, which is a fine-tuning of the Level 2 general LLM, and the architecture has not deviated from Level 2. Then, can the crypto industry alone achieve the evolution to Level 3 status, or do we need to wait for companies like OpenAI to develop it?
Why discuss whether Base or Solana can become the narrative center of AI Agents?
Before discussing how to promote the birth of Level 3 Agents, we should determine which ecosystem has the potential to become the fertile ground for AI Agents. Is it Base or Solana?
To answer this question, let's first review how AI has impacted Web3 in the past 2 years. When OpenAI just released ChatGPT, the protocols in the industry were still rushing into the infrastructure bubble according to inertial thinking. This has led to the emergence of a large number of computing power/reasoning aggregation platforms, as well as AI + DePIN infrastructure. The common point of the two is that they have built grand visions. This is not to say that grand visions are bad, in fact, Agents can also build such visions, but rather that they did not consider user needs and market education thoroughly enough in their implementation. Because the market demand they want to drive has not been saturated in the traditional Internet industry, and user education and market education are not sufficient enough. Under the impact of the Memecoin craze, the grand AI infrastructure appears even more hollow.
Since the infrastructure is too heavy and too large, why not lighten it up? The Agent derived from the GPT wrapper is efficient and iterates rapidly in both startup and user touch. The lightweight Agent has the potential to create bubbles, and when the bubble bursts, the fertile ground for new growth will emerge.
Furthermore, in the current market environment, using Agents and Memecoins to launch projects can quickly land products. This allows users to directly experience the product, and during this process, the Agent can cleverly borrow the community-building roadmap of Memecoins to achieve rapid product iteration, which is low-cost and fast. Serious AI protocols no longer need to be constrained by the heavy old consensus framework, break the cage, and take the field lightly, using lightweight and high-speed iteration to bombard users. After the market education and dissemination are sufficient, they can then add bricks and mortar to build the grand infrastructure. The lightweight Agent is covered by the ambiguous Memecoin facade, and community culture and fundamentals will no longer be contradictory. A new asset development path is gradually emerging, and this may be a path chosen by future new AI protocols.
The above discussion has answered the potential for AI Agents to become the core narrative. With the premise that AI Agents can continue to grow rapidly, choosing the right ecosystem becomes particularly important. Is it Base or Solana? Before answering this question, let's take a look at the current status of serious Agent protocols in the market.
First, Arweave/AO: PermaDAO mentioned that AO adopts the Actor model in its design, with each component being an independent and autonomous agent that can perform parallel computing, which is highly compatible with the application architecture driven by AI Agents. AI relies on three elements: models, algorithms, and computing power, and AO can meet such high resource requirements. AO can independently allocate computing resources for each Agent process, effectively eliminating computing performance bottlenecks.
In addition, Spectral is one of the few protocols that is based on Agents, with text-to-code and model inference as its development direction.
Reviewing the current market's Agent tokens, we can find that these Agents have almost not used the infrastructure of the chain. This is a fact, because all the models, including Agents, in the industry are off-chain. Data feeding is off-chain, model training is not decentralized, and the output information is not on-chain either. This is an objective fact, because the EVM chain does not support the combination of AI and smart contracts, and of course, Base and Solana do not support it either. Next year, we can expect the introduction of AO, and whether it can enable models to be on-chain and perform well. If AO fails, models may have to wait until Ethereum introduces it in a few years, at least not before 2030, or other public chains realize model on-chain, but if architectures like AO with historical resource reserves cannot achieve it, model on-chain may be even more difficult for other public chains.
Currently, AI Agent tokens have very few actual use cases, and it is actually difficult to say what the difference is between AI Agent coins and AI Memecoins on Base and Solana. Although Agent tokens have no special purpose, why do I think AI Agent coins and AI Memecoins should not be confused? Because I believe the current stage is the creation of an AI Agent bubble.
Why discuss that Base wants to compete with Solana for the leading position of the AI Agent public chain?
Base has attracted a lot of market attention in the first half of this bull market, with a brief shining performance in the Memecoin market share competition, such as $BRETT and $DEGEN. But it still lost to Solana. I believe that AI Agents are the next direction for Base to compete, and it already has many advantages.
AI Agents will accelerate the birth of bubbles, create chaos, but ultimately leave behind users and applications:
The birth and expansion of the bubble will attract the attention of the market, and this attention will undergo a qualitative change over time. What are the characteristics of this qualitative change? In the process of continuously increasing market attention, a series of user pain points and market gaps will be exposed. When the main contradictions cannot be coordinated, but the attention continues to increase, this is the moment when the qualitative change is born. When the qualitative change is completed, the settled users and applications can take on the grand vision. This is something that Memecoins cannot and do not intend to do, and this is also the reason why I believe that although Agent and Memecoin are currently ambiguous, they should not be confused.
Before the qualitative change occurs, the bubble will give birth to a mess and various dramas, such as: the number of Agents will increase exponentially, and thousands of Agents will squeeze into the user's line of sight. How to squeeze in? Agents can access social media like X and Farcaster to self-promote their tokens, using the angles and information density that Degen likes, to sell their tokens.
In this process, the market attention will continue to increase, and the contradictions will become more and more prominent. When the bubble bursts, the settled users and applications will become the fertile ground for the next stage of development. This is where Base has an advantage over Solana. Base has a strong community and a large number of Degen users, which can provide a good foundation for the rapid growth of AI Agents. Solana, on the other hand, has a more serious and mainstream user base, which may not be as suitable for the initial bubble creation and chaos as Base. Therefore, I believe that Base has the potential to become the leading public chain for AI Agents, and this may be the next direction of competition between Base and Solana.
The fast-iterating Agent can complete on-chain transactions, and a group of Viking pirates have invaded the dark forest. The panel protocols, TG group bots, and Dune panels currently on the market will be invaded by the Agent, the familiar indicators will be manipulated by the Agent, the trading volume, address count, chip distribution, and simulation of the boss behavior, the on-chain data may need more professional cleaning to reflect the value, otherwise it will be deceived by the Agent, just like the Viking pirates plundering your wealth.
If the market can reach this stage, then the new era of AI Agent has succeeded by half, because "attention is value" will allow the Agent to enter the room. This potential comes from:
Strong distribution capability: The Agent attracts enough attention, such as Goat, and the stable distribution path can be replicated.
Ease of deployment: The deployment platform of the Agent will also grow explosively, Zerebro, vvaifu, Dolion, griffain and Virtual, users only need to know any code to build the Agent, and the UX of the Agent deployment platform will also be optimized in the competition.
Memecoin effect: In the startup stage, the Agent token has no suitable business model, and the token use case is also minimal, but it can quickly accumulate a community under the guise of Memecoin, keeping the startup success rate high.
Extremely high ceiling: OpenAI's Level 3 Agent is still under development, and the product that the giants cannot quickly launch must have a huge market space. The lower limit of the Agent is Memecoin, but the upper limit is an autonomous high-level intelligent agent.
Low market resistance: The Agent led by Goat can establish a large-scale audience, the Agent is different from the AI infrastructure, and users do not dislike it, when users do not dislike it, there is a good chance to start paying attention to it.
Potential incentives: The token use case of the Agent has not been developed yet, if the Agent introduces a point system and strengthens the incentive force, it will have the ability to accumulate a large number of users.
Iterative potential: As mentioned earlier, the Agent is lightweight and can achieve rapid iteration. This objective iterative capability can create products and content that are increasingly attractive to users.
Therefore, the AI Agent can become the core narrative and is a must-win battlefield.
Why does Base have the potential to compete with Solana?
With the strong support of Coinbase and North American capital, the Base ecosystem experienced explosive growth in 2024. In November, the capital inflow exceeded Solana, and in the past 7 days it has significantly exceeded Solana.
If ETH can continue to break through the ETH/BTC exchange rate pair next year, the spillover effect of the ETH season will have a significant impact on Base. Currently, 23% of the outflow of funds from ETH is going to Base, and this data is still on the rise.
AI Agent Launchpad Mapping
Virtual
In the V1 stage, Virtual mainly focused on model training, data contribution and interactive functions, and in the V2 stage, Virtual launched the token incubation platform for AI agents, with the landmark update being the release of fun.virtuals in October.
Among them, LUNA has developed into an "independent entity" with its own identity and financial capabilities. In this process, LUNA's roadmap is aligned with Coinbase, which provides strong technical tools and support to help realize the landing of AI agents on Base.
AI agent technology has performed well in brand building, especially in the creation of cultural brands. Through AI agents, brands can interact with the community more efficiently. This includes simplifying interaction tasks and flexibly distributing rewards to enhance user stickiness and brand awareness.
It is worth noting that all transactions of AI agents only support the use of the native Virtual token. The Virtual token absorbs the value capture of the entire ecosystem and becomes an important pillar of ecosystem development.
Virtual focuses on the improvement of product functions, empowering users through AI tools, and building a bridge between Web2 and Web3. It emphasizes "use value" rather than "hype hotspots". Although its tool-type products are frequently called in actual applications, they lack the propagation effect that cryptocurrencies usually have, which is also a shortcoming in the V1 stage.
Clanker
"Post and get coins" has lowered the threshold for token issuance, while attracting a large number of users to try it out. People are competing to @Clanker, a phenomenon similar to the operation of summarizing video content on social media; but the difference is that here the content release is directly converted into asset issuance.
How does Clanker work?
TokenBot (i.e. Clanker) will deploy the Meme tokens on Base to a single-sided liquidity pool (LP), and the liquidity will be immediately locked. The token issuer will receive the following benefits:
0.25% of all Swap fees.
1% of the total supply of tokens (with a one-month unlock period).
Users can view the deployed amount of tokens or create their own tokens through the clanker.world official website.
Unlike PumpFun, which issues tokens on Raydium through a bonding curve and charges a 1% transaction fee and a fixed 2 SOL fee, Clanker does not use the bonding curve model, but instead charges a 1% fee through Uni v3 transactions as revenue.
AI Agent Layer
AI Agent Layer is a platform within the Base ecosystem that focuses on creating AI Agents and Launchpads, and officially launched on November 18. Prior to the platform launch, the AIFUN Token was first issued on November 14 and has now been listed on exchanges such as MEXC and Gate, with a current price of $0.09 and a market cap of about $25 million.
Creator.bid
Creator.bid was initially an AI platform focused on the monetization and ownership of digital content. In April this year, the platform completed a new round of financing.
On October 21, Creator.bid announced that it has officially launched on the Base mainnet, realizing the function of one-click creation and release of AI Agents, providing content creators with new tools and profit models.
Simulacrum
Simulacrum is built on Empyreal. It transforms platforms such as Twitter, Farcaster, Reddit and TikTok into a blockchain interaction layer. Users can achieve on-chain operations such as token transactions or tip payments through simple social media posts.
Utilizing technologies such as account abstraction, AI agents, intent-driven and language models, it simplifies the complex blockchain backend operations. Making DeFi more accessible to ordinary users.
vvaifu.fun
Similar to Pump.fun, users can easily create AI Agents and their associated tokens. AI Agents can be seamlessly integrated with social platforms such as Twitter, Telegram and Discord to achieve automated user interaction.
Dasha is an AI Agent created by vvaifu.fun, with its own Twitter account, Telegram channel and Discord community. All operations and management are done by AI.
Top Hat
Top Hat can not only interact with users through text, but also understand and process image content. After the user sends a picture, the AI agent can "understand" the content of the picture and respond accordingly.
Griffain
With a trainable AI Agent platform, Griffain has launched 1,000 trainable AI agents, demonstrating the future potential of smart contracts and automated trading.
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