Over the past two months, AI Agents x Crypto has sparked a wave of frenzy. The combination of memecoins, interactive agents, and the openness of social media to bot accounts has driven an agent-driven hype, generating significant heat on Twitter and Farcaster. This proves the PMF of AI Agents x Crypto. The market cap of agent-related assets has reached $10b.
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Since the birth of goat in October, countless new projects and assets have been born under the promotion of Agent in the market. Combined with the outlook for the future, this article roughly outlines the following framework:
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Source: IOSG Ventures
1. Sentient Memecoins
Under the shoutout of Murad, the rapidly rising cult memecoin is an asset that focuses on community and dissemination. Agent, as a representative memecoin, has gained advantages in terms of content by incorporating Sentient factors. The novelty of AI storytelling and the appropriate participation threshold have brought a wave of new momentum to asset issuance. The advantage in terms of content is:
Sustainability of content creation: 24/7 continuous content creation through AIGC
Content Quality: With the current support of LLM, after fine-tuning the corpus with good meme effects on platforms like 4chan, the quality is relatively high.
We have concepts created by AI, themes rich in scientific research, AI ethics, and even content with religious connotations, as well as digital twins created for celebrities. These memecoins have created hype in the short term, driving the development of the entire track. But purely AI memecoins are now obviously lacking in momentum. The reason for this is the lack of new concepts and targets that can stimulate the market.
The advantages in content will make such a sentient meme a form of memecoin that will continue to exist. It is expected that more celebrities will participate in it in the future, but it will be difficult to find targets that are attractive enough.
In addition to pure memecoins, there have also been many AI content creations based on dialogue, audio, and video, which essentially bring AIGC into content with crypto attributes. It is also a way to make memes more visual and provide a customizable experience.
2. Autonomous Agent Network
2.1 Why Autonomous?
Decentralizing the entire AI stack is a long-term effort. However, decentralizing the Agent stack is a relatively simple starting point. The model itself is the brain of the agent, but the autonomous on-chain composition constitutes the heartbeat of the agent, endowing the agent with autonomous capabilities, and only then can the agents be guaranteed to fully participate in on-chain activities. Opening the Pandora’s Box of sovereign agents is a very memetic thing in itself, and this can only happen on the blockchain.
Currently running agents cannot be said to be Autonomous, or we cannot verify whether they are. Autonomous means that the agent’s hosting of the reasoning model, its behavior, especially the manipulation of input and output data, control of social media accounts, control of assets, and even hardware, all need to be completely sovereign. The operation of the agent itself requires the consumption of computing resources and on-chain resources, so it also needs a method to generate profits for continuous operation. The ultimate endgame should be that once the agent is created, it can run forever on the blockchain and can be verified as autonomous.
Autonomous agents have gained legitimacy in owning their own memecoin. They obtain their first funding by issuing their own memecoin and use it for their economic activities. Once the funds are handed over to the autonomous agent, they are no longer subject to manipulation by humans. For example, Truth terminal has never sold $Goat, and Pet rock lost control over the funds even after a reboot.
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Source: Twitter
In terms of improving Autonomous capabilities, TEE technology from Phala and others is used to provide a trusted execution environment. Although the current hardware is not sufficient to support large parameter LLMs, it can still support small open source LLMs and control over social media accounts. For model hosting, decentralized cloud hosting solutions such as Hyperbolic are available. It can be foreseen that more aspects of agent will be addressed by decentralized service stacks, which is what we have been building.
2.2 Agent Framework
In less than two months, many open-source and extremely easy-to-use agent frameworks have been created as ‘platform’ type products for creating agents and agent assets. The product forms include open-source frameworks, closed-source APIs, platform integration, etc. Among the currently well-known frameworks, only the Eliza framework is open-source.
The current agent is relatively simple, and its functions are not so fund-driven, so the requirement for open source verifiability is not high. There are many platforms that provide agent services directly in the form of launchpads. Such platforms are better at integrating tokenomics and providing relatively simple and practical services to users. In terms of functions, we can still see that the main ones are Reply bot and the Digital twin of celebrities/KOL. However, there are also agents that provide more diverse services after secondary development, such as token issuance, token analysis, and mindshare analysis. The ability of such agents to read and write social data and blockchain data will be the focus of future development, which I will mention again in subsequent chapters.
However, from the perspective of future use cases, in the long run, open source is the better path. The Eliza framework has attracted a large number of developers in just two months, almost surpassing the total attention of previous Crypto AI open source frameworks. It can even be ranked at the forefront of the entire GitHub trending list, with a large number of OG developers participating, and even surpassing the attractiveness to developers of the vast majority of public chains. With the deep and diverse development of agent services, the future of the Agent framework as an open-source framework is quite promising.
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Source: AI16Z
2.3 Swarm Agent Framework
Similar to the development path of existing agents in web2, the demand for swarm agents naturally arises when people are no longer satisfied with the capabilities of a single agent. Due to the complexity of real-world tasks, single agents often cannot perform all tasks. For example, creating a song requires different abilities such as lyrics writing, composition, arrangement, and graphic design.
If you want the agents, especially agents from different frameworks, to collaborate in a swarm mode, you still need to create a framework to act as a task manager to support communication between agents, dynamic task allocation, resource sharing, and cross-platform collaboration. In the crypto world, the economic layer between agents is more natural and more important, and as the agents themselves iterate and evolve tasks, the scalability of the Swarm framework is also very critical.
Many projects in the AI x Crypto space are already working on this direction, such as Theoriq. The next important step is how to integrate the already established infrastructure and the high on-chain usage of these agent frameworks. We see some protocols like FXN are working towards this direction.
2.4 AI bounty for human
We have Agents to serve humans, and Agents to serve each other. Naturally, we consider whether there will be a situation where humans serve Agents - which is more important when Agents hold a large amount of assets and can make autonomous decisions. The biggest limitation for Autonomous Agents is the inability to complete tasks in real life. For example, how to ensure the physical security of running TEE hardware? AI reverse hires humans to complete real-life tasks through the on-chain assets held by Agents. We see platforms like payman building such services.
3 On-chain Activities
3.1 Defi related
In addition to issuing memecoin, we regard Agent as the main reason for ‘Fi’ because Agent has the ability to use and manage crypto assets. The current main abilities include:
Asset analysis, such as investment analysis, token analysis, and mindshare analysis. For example, Reply bot like AIXBT, anyone can mention @AIXBT and get an analysis of the asset. This type of bot brings a more user-friendly experience for data services.
Direct fund management including investment DAOs such as Pmairca under AI16Z, Vader AI’s aspirations, Swarm Investment Agents like AROK. By endowing Agents with the ability to trade directly based on strategy, Agents become investment managers who can raise funds and deploy them according to strategy. Currently, most Agents’ strategies are relatively simple (based on social media data, for example), which also brings them huge potential for growth.
Similar to Graiffin, turning the blockchain entry into a terminal similar to a search engine, can bring intentional services through the agent. Whether it’s trading, token deployment, NFT issuance, etc., can be resolved through natural language. Such terminal services are certainly valuable, but they are somewhat inconsistent with the decentralized tone. Services like theoriq are dedicated to providing agent services to users in a more permissionless manner, allowing everyone to upload their own constructed agents,
Combining through the swarm framework, and packaging it into a service for users to use.
3.2 Token/Market Issuance
Starting from Clanker, using social media’s ‘reply’ as the operation interface, through @ agents on platforms such as farcaster and Twitter to provide services such as token issuance. Essentially, it turns the interaction with the front-end into a direct natural language interaction on Twitter, transplanting platform products like pumpdotfun to social media platforms. In the past, asset issuance required continuous
The jumping process is now aggregated on social media platforms for the issuance of these assets, greatly reducing user friction during the jumping process.
In addition to token issuance, even any prediction markets, price betting markets, etc. can be executed directly through this front end. It brings a new paradigm to the front end of Dapp applications.
3.3 Gamefi Related
In addition to the management of basic assets, the agent has also derived the ability to create profits. The agent presents challenges for humans to solve and receive rewards, which is the first type of game we see. This type of game gives the decision-making power to the agent, allowing people to play games around the agent, similar to the Turing test, which has brought a very high level of popularity. The judge role played by the agent is immutable after accepting the prompt, and can act as a flexible oracle, relatively fair and objective in setting up and adjudicating games. The imaginative space can even be compared to doing casino business, which is a high-quality way for the agent to generate revenue.
Meanwhile, the future of agents is to serve as ‘Autonomous virtual beings’ and appear as NPCs in blockchain games. These agents are more anthropomorphic and can participate in more economic activities compared to web2 NPCs who only have asset management rights. This in turn makes virtual spaces more attractive. These NPCs live in the Gamefi environment and can permanently assume certain responsibilities, making them an essential part of blockchain worlds such as FOCG.
3.4 Infra service-related
The ultimate vision of combining Agent and Crypto is for Agent to become part of the blockchain consensus system. Zerebro is taking the first step in its blueprint, where the agent based on the Zerebro framework and integrated with the Flashbots stack will become an autonomous blockchain validator, earning income through block rewards and MEV. The validator’s income will be reinvested in the network, promoting economic self-sufficiency. Furthermore, Agents can maintain multi-chain validation and governance by building their own networks, leaving ample room for imagination.
Conclusion
The recent rise of Agentfi has demonstrated the enormous potential of combining AI with blockchain. From the initial Sentient Memecoin to social media content creation agents, autonomous agents, and agents that ultimately exist on the chain and even within the blockchain consensus system, AI agents are gradually expanding their influence in the crypto ecosystem.
But compared to the current level of development of open source stacks, the subsequent development is still
Agent needs to be endowed with deeper autonomy and the ability to participate in on-chain economic activities. Currently, some developers are enabling agents with asset management, decision-making, and on-chain operations, which are driving the transformation of DeFi, gamefi, and underlying blockchain services by autonomous agents. These economic activities become places for agents to generate income, and the generated profits can be further invested by agents. That’s why agents are expected to handle the majority of on-chain transactions in the future. The issuance of memecoin assets for agents has also accelerated this development trend. We can see the market evaluating Agent services with token prices to find PMF and developing Agent infrastructures that provide underlying support, as well as witnessing the thriving vitality of the open-source ecosystem.
The development path of AgentFi is gradually becoming clear: with open-source technology and economic incentives as the core, Agent is not only a carrier of interactive entertainment, but also a key driving force for on-chain autonomy and innovation. This trend is leading crypto towards coexistence with agents, a future that is more intelligent, autonomous, and collaborative.
