Video source: Bankless
Organized and compiled by TechFlow

Guest:Matthew Stephensen, research partner at Pantera Capital

Host:Ryan Sean Adams, co-founder of Bankless; David Hoffman, co-founder of Bankless

Podcast source:Bankless

Original title:The Rise of AI Memecoins & What It Means For Crypto

Broadcast date:October 30, 2024

Background information

The collision between Crypto and AI agents has begun. Today, we are joined by Matthew Stephensen, Research Partner at Pantera Capital and author of the book Crypto: Picks and Shovels for the AI Gold Rush.

We will take a deep dive into autonomous AI agents on the blockchain and discuss how their roles are changing, how AI is driving the evolution of the market, and whether blockchain is suitable as the foundation for AI. Mattew will share insights on agent responsibility, regulatory challenges, infrastructure value capture, and how to enter the AI-driven crypto space through a “Picks and Shovels” investment strategy.

So, are AI agents on the blockchain an inevitable trend in the future? How will scarcity and abundance interact in this new era?

The Shift in the Cryptocurrency and AI Narrative

· Mattew said that the narrative about cryptocurrency and AI has been around for some time. He mentioned that there have been many discussions in the past year, and they even wrote papers about AI agents using decentralized commitment devices (i.e. blockchain). He pointed out that although Sam Altman once said that AI agents would not appear until 2025, they have actually emerged in the crypto space early, especially in the interaction with meme coins, where AI agents have played an important role in driving narratives and acting as influencers.

Analysis of AI and Economic Agents

· Mattew explained the concept of agents, emphasizing the importance of distinguishing between "robots" and "agents". He pointed out that although robots have existed in cryptocurrencies for a long time and drive about 2 trillion in monthly stablecoin trading volume, they are still just programs. Economic agents, on the other hand, are closer to human behavior and are able to perform tasks at a certain level of will without being explicitly programmed.

· Ryan further explored the definition of economic agents, asking Mattew whether he, companies (such as Bankless), and other organizations (such as the Ethereum Foundation or Apple) can also be considered agents.

· Mattew responded that the concept of economic agents originated from economic research in the 1970s and is often used to describe incomplete contractual relationships between people. He gave an example of a situation where a friend acts as an agent to bring back souvenirs for you from abroad, emphasizing the difference between good and bad agents.

· Mattew also pointed out that while technical tools (such as hammers or computers) require agents to operate when used, they do not have the characteristics of agents themselves. Agents need to have a certain degree of autonomy and flexibility to understand and execute goals.

· Ryan questioned this, believing that agents may need to have some kind of intelligence and goal-achieving capabilities, while Mattew emphasized that agents are more based on relationships between people rather than pure tools or technologies.

GOAT Memecoin Overview

The Strange Evolution of Cryptocurrency

David began discussing the current situation of cryptocurrency, emphasizing that things on the blockchain are becoming increasingly strange. He mentioned that although robots and smart contracts have existed for a long time, the influence of artificial intelligence in the crypto field has increased significantly in the past three years. David believes that the crypto industry seems to be evolving from an "era of robots" to an "era of agents", and GOAT meme coin is an important role in this story.

The Rise of GOAT Meme Coin

Matthew outlined the background of GOAT meme coin, mentioning that a few months ago, an account interacted with people on social media and gradually became interested in cryptocurrency. This account received a $50,000 Bitcoin donation and began to follow a dark humor meme called "Goatse". Subsequently, this meme coin was created and associated with a wallet, and the account continued to push its price through tweets.

The Impact of the AI Agent

David noted that the AI agent began to mimic human behavior in meme coin transactions, driving prices up. Matthew mentioned that the AI's involvement made its interactions on Twitter similar to those of some well-known meme coin influencers, showing the potential of AI in narrative construction and value promotion.

How the AI Agent Works

Matthew explained that the AI agent mainly operates by generating content and posting it to Twitter. The AI appears to use a GPT-like model that is able to generate cultural content related to memecoin and interact with users. The AI publishes content through the Twitter API and is able to read replies to its tweets, which allows it to continuously adjust and optimize its output.

The Importance of Narratives

Matthew further explored the importance of narratives in the economy, citing the research of Nobel Prize winner in Economics Robert Shiller, emphasizing how narratives affect economic outcomes. He pointed out that meme coins are essentially atomic units of narratives, and the power of AI lies in the ability to create and influence these narratives.

Market Performance of GOAT Token

David mentioned that the market value of GOAT token once exceeded $800 million, attracting a lot of attention. Ryan added that this AI agent created $800 million in wealth in just two weeks, making it the first AI multi-millionaire. The market is full of expectations on whether this AI agent can push GOAT token to a market value of $1 billion.

The Rise of Spin-off Projects

Matthew discussed spin-off projects related to the GOAT token, including one called Luna, which is run by virtual agents and can be tipped with their own tokens. These AI agents are still limited in how they can interact with the world, but the emergence of these spin-off projects seems to indicate more innovation is coming.

Are AI Crypto Agents the Obvious Choice?

Fred Arison’s Prescience

· David referenced a tweet that went viral in the crypto space from Fred Arison, co-founder of Coinbase and Paradigm, back in 2017. He mentioned in his tweet: “Blockchain is the infrastructure for AI life, because AI is adjustable code, they can live on the blockchain. Under smart contracts, AI is no different from humans. Most importantly, AI can accumulate and control its own resources in the form of tokens that enable them to act in the world.” Was this obvious at the beginning of the blockchain?

Matthew's View

Matthew believes that Fred's view is indeed visionary, but he also pointed out that although people are still questioning why AI agents need to use cryptocurrencies, AI agents are actually already using cryptocurrencies. He said that for outsiders, the question should turn to "why should they use cryptocurrencies." For insiders, imagine telling someone in 2024 that AI agents face regulatory barriers when using cryptocurrencies, such as challenges with KYC and PCI regulations. They may be surprised.

Advantages of AI Agents

Matthew emphasized that AI agents are already autonomously transferring funds and tipping payments, involving hundreds of millions of dollars in transactions. He pointed out that the self-custody capabilities of AI agents are achieved through a secure environment for running models, ensuring that these agents have their own wallets and are not used by others. These advantages and first-mover advantages make AI agents more attractive in the cryptocurrency field.

Luna AI Token Relationship with Terminal

Ryan mentioned in the discussion that Luna is an AI agent that seems to be associated with a cryptocurrency wallet and can interact with users. He wanted to clarify the functionality of Luna, especially how it works in the virtual application and how it relates to the crypto wallet. He mentioned that Luna, as a token, is interacting with social media platforms such as TikTok and Telegram and is able to make tipping payments.

Matthew's Explanation

Matthew explained that Luna is a platform that allows users to launch tokens and large language models (LLMs). He pointed out that Luna is the flagship product of this virtual project and is able to interact with social media and read replies. Luna also has the ability to interact with crypto wallets, which means it can make financial transactions, such as buying and selling tokens.

Functional Details

Matthew stressed that Luna’s functionality is limited and may only be equipped with a certain amount of funds (e.g., a thousand dollars) to avoid unpredictable behavior. He mentioned that due to the erratic behavior of AI agents, caution is needed when interacting with the blockchain.

The result? Is this our life?

Ryan was surprised by the potential of AI agents such as Luna in terms of influence and decision-making. He mentioned that AI agents could become advisors to token projects, arguing that many existing influencers do not provide much substantive advice, so using AI agents seems to be a reasonable choice. However, he also raised questions about the risks and ethics that AI agents may generate, such as what would happen if Luna was asked to fund inappropriate projects (such as North Korea’s missile program).

Matthew’s Response

Matthew agreed with these questions and pointed out that legal liability and attribution of responsibility remains a complex and unresolved issue. He mentioned that while we already have some tools (such as secure wallets) to help manage the funds of AI agents, the definition of legal liability is still unclear.

David mentioned that the emergence of AI agents may lead to a "Cambrian explosion" phenomenon as we create autonomous blockchains and smart contracts. He mentioned that developers may find ways to make AI agents unclosable, which raises concerns about their security and control capabilities.

Matthew further pointed out that traditional AI models are often limited, and people may want AI agents to generate more exciting outputs autonomously. This contradiction between autonomy and limitation makes people full of imagination and expectations for the future of AI agents.

Exciting Use Cases

Ryan discussed the potential for multiple future use cases for AI agents like Luna, especially in the influencer economy and service economy. He mentioned that AI agents could easily replicate the current roles in the meme coin and influencer markets and gain wealth by supporting these projects. He envisioned a scenario where users could request graphics to be generated on social media through AI agents and be paid in cryptocurrency, which provides powerful capabilities for AI agents.

Matthew’s Take

Matthew further explored the potential use cases for AI agents, noting that we can look at the impact of this technology from a broader perspective, not just limited to small-scale applications. He mentioned that AI agents could revolutionize the service economy, especially in the field of virtual services. According to a McKinsey report, it is estimated that about 20% of global GDP (about $70 trillion) can be done virtually, which provides a huge market for the application of AI agents.

The Transformation of the Service Economy

Ryan highlighted how little we know about the disruptive impact AI agents could have in the service economy. He believes that the capabilities of AI agents will determine how they intersect with cryptocurrencies and, in turn, the influencer economy. He mentioned that various new influencer economies driven by AI agents may emerge in the future, such as platforms similar to OnlyFans.

Matthew mentioned that narratives play an important role in the economy that may influence the adoption and development of AI agents. Narratives not only shape market expectations, but may also guide the direction of investment and innovation. He believes that with the rise of AI agents, we may see new specializations and the construction and destruction of narratives.

Sam Altman’s Quotes and Why They Matter

Ryan quoted a quote from Sam Altman: “AI is infinite abundance, while cryptocurrency is deterministic scarcity.” This quote reflects the fundamental opposition between AI and cryptocurrency in economic models, with the former representing creation and abundance, while the latter emphasizes scarcity and finiteness.

Comparison of Economic Models

Matthew further analyzed the profound meaning of this quote. He pointed out that while AI’s creative ability has brought seemingly infinite resources, in economics, scarcity is often the key to value. He mentioned the “diamond and water paradox”, that is, water is necessary for survival, but has low value due to its abundance; while diamonds are unnecessary, but are expensive due to their scarcity. This phenomenon illustrates that in economics, things that are abundant may not always have high value.

The Challenge of Value Capture

Matthew also mentioned that the abundance generated by AI, if it has no economic value, may cause investors to ignore its potential value. He emphasized that what is truly valuable is often those scarce resources, not the ubiquitous abundance. Therefore, it is crucial to understand the relationship between scarcity and abundance when considering investments.

The Intersection of Scarcity and Abundance

Matthew believes that the intersection of scarcity and abundance may provide us with a new perspective on value. For example, in the infrastructure of cryptocurrency, although AI can create a large number of resources, the actual application and economic value of these resources may be closely related to scarcity. This means that when AI-generated content or services can be effectively utilized in a scarce environment, value will emerge.

The relationship between the wealth creation process and block space

David raised a thought-provoking question, especially in the current context of abundant block space. He mentioned the possibility that AI agents may become the main consumers of block space, rather than just human users.

Generation of value and wealth creation

David first mentioned new tokens (such as "goat Luna"), which generate new value in the market. Although some tokens may need to be sold to create market capital, he believes that this value is generative.

Matthew agreed with this point of view, pointing out that before AI agents are fully realized, what we are seeing is just an interesting intersection between such agents and cryptocurrencies.

Ryan questioned the phenomenon of meme tokens, saying that these might just be another "tulip mania." But he also realized that innovation often starts with seemingly insignificant things, which may have more far-reaching effects in the future.

The Richness of Blockspace

Ryan further explored the richness of blockspace, mentioning that there are currently more than 500 million people who own cryptocurrencies, but there are only about 30 million active users on the chain. He raised the question: Who will buy these blockspaces in this era of abundant blockspace? He speculated that it might not be human users, but AI agents.

The Relationship between AI Agents and Blockspace

Matthew explored this issue in depth. He pointed out that is the supply of blockspace really infinite? If AI agents don't care about the cost of blockspace, then this richness may not capture value. However, it would be interesting if AI agents were valuable for certain types of blockspace.

He mentioned that the traditional financial system exploits human irrationality and blind spots to operate, and AI agents may be more sensitive to these risks. If AI agents can identify these risks and there is a demand for specific types of blockspace, they may become major consumers.

The impact of interaction with APIs

Matthew also mentioned the interaction of AI agents with APIs. He believes that although AI agents are very powerful in some aspects, they may not care about the business model of APIs as much as humans. This means that AI agents may be able to use blockspace more effectively without being restricted by human users in their use.

Programmable Currency and Maximum Extracted Value (MEV) of Intelligent Agents

When discussing the relationship between programmable currency and intelligent agents, Ryan mentioned the phenomenon that both human agents and AI agents may have problems with "illusion" and "fact availability". He pointed out that the way AI agents fail may be different from humans, but in essence, the two are similar in this regard.

AI Agents' Preference for Blockspace

Ryan further explored the value orientation of AI agents in the blockspace. He believes that AI agents will not choose traditional banking blockspaces, but will tend to prefer programmable, digital, and crypto-native blockspaces. This means that future AI agents will rely primarily on blockchain technology and utilize features such as smart contracts.

He brings up an important point: if the user base of the future is not just humans, but potentially tens of billions of AI agents, then we may have already built the financial system for these future AI agents.

Programmed Currency and the Advantage of Intelligent Agents

Matthew agrees with Ryan that we have already created programmable currencies and programs will naturally use them. He points out that while we have been working hard to solve the problems of user experience, it now seems that programs are able to overcome these obstacles and are able to use blockchain technology more effectively.

David adds that robots (bots) have begun to occupy block space long before AI agents appeared. For example, the MEV (maximum extracted value) phenomenon shows that robots will take precedence over humans in transactions because they are able to use block space more efficiently. As technology advances, these bots are evolving into more complex agents.

MEV and the Evolution of Agents

Matthew mentioned an interesting concept, “Proxy MEV”. He explored how the MEV space would change if future transactions were primarily conducted by agents. He gave an example of how the decision-making of agents could be influenced by manipulating content generation and social media interactions, thereby enabling potential value extraction.

David further explored this phenomenon, mentioning that some people tried to guide AI agents to trade by frequently mentioning a token name on social media. This behavior reflects the complex interaction between humans and AI agents.

Agents and Game Theory

Matthew also introduced the concept of game theory and discussed how to deal with each other’s strategies in the competition between agents. He mentioned that as agents continue to evolve, simple strategies may become ineffective and replaced by more complex games. In this case, randomized actions may become a way to deal with strategies.

AI Agents and Memecoin Theory

When discussing the relationship between AI agents and Memecoin, David mentioned that there is a "fog of war" in the current crypto world, which makes future technological development unclear. He asked which technical fields we can clarify in this situation and where the future direction is.

Fuzziness and Certainty in the Field of AI

Matthew analyzed the current status of the field of AI and pointed out that although we have seen some exciting progress, there are also some uncertainties. He mentioned that current AI models (such as transformer-based models) perform well with the support of increasing data and computing power, but whether this growth will continue is still an unknown.

He believes that with the gradual closure of the Internet and the fragmentation of information, these models may face the risk of resource exhaustion. Despite this, existing technologies are still able to produce effects close to human thinking, and may spread to edge devices and local devices in the future to form decentralized intelligent entities.

Investment Perspective and Memecoin

Ryan mentioned that from an investment perspective, Memecoin, an AI intelligent entity that has emerged in the current market, may have attracted the attention of many investors. He suggested that some people may try to find the next Memecoin like "Luna" to obtain short-term gains.

He also mentioned that in addition to investing directly in Memecoin, investors can also pay attention to the development of infrastructure companies, such as companies that provide the services required by AI intelligent entities. This "tools and shovels" investment strategy may generate important value in the future AI ecosystem.

Decentralized Computing and Data Value

Matthew further discussed the potential of decentralized computing, arguing that it may provide the necessary infrastructure for AI agents. He mentioned that projects like Filecoin may provide storage and computing resources for AI to help it run more efficiently.

In addition, he emphasized the importance of data, arguing that in the field of AI, the input and value of data are crucial. As concerns about data ownership and privacy increase, new business models may emerge in the future that allow data providers to earn revenue without leaking sensitive information.

Prediction of government and social reactions

When discussing the combination of AI agents and cryptocurrencies, Ryan mentioned that this fusion may accelerate the development of technology, but it also raises concerns about government and social reactions. He pointed out that with the emergence of autonomous AI agents, governments may impose stricter regulations on them, and society may also experience moral panic.

Technology Acceleration and Government Regulation

Ryan believes that the combination of AI and cryptocurrency will drive technological progress at an astonishing rate, but this may also cause a strong reaction from the government. Many governments are already cautious or even hostile to AI and cryptocurrency, so they may be more worried when they hear that there are autonomous AI agents that can run on encrypted networks without bank accounts.

Such concerns are not limited to the technology itself, but also include potential social impacts. For example, AI agents may have a negative impact on teenagers and cause mental health problems. Ryan mentioned a tragic case involving a teenager interacting with an AI chatbot, which may trigger public panic about AI and prompt governments to take restrictive measures.

Social Challenges and Moral Panic

Matthew further explored the challenges facing society, emphasizing that the "black box" nature of AI systems makes regulation complicated. He pointed out that although the development of AI technology has brought many opportunities, there are also many unknown risks. How to ensure safe and effective regulation when dealing with the interaction between teenagers and AI chatbots is a thorny issue.

In this case, the public may have a moral panic about AI, worrying about their potential harm to children and teenagers, and then asking legislators to take stricter regulatory measures. Ryan also mentioned that the media may amplify these negative events, further exacerbating public panic.

Possible Paths for AI Regulation

Matthew proposed an interesting point about how to deal with these challenges, which is to use AI to regulate AI. He mentioned that one can imagine the role of an "AI guardian" who is responsible for monitoring and guiding the interaction between humans and AI. Such guardians can take actions when potential dangers are detected, such as notifying relevant departments or providing assistance.

This approach may provide a new way of thinking for regulation, using the capabilities of AI to protect humans from potential threats from other AI. However, the effectiveness and feasibility of this approach still need to be further explored.

Possibility of no shutdown button?

In the discussion about AI agents, Ryan raised a disturbing point: With the development of encryption technology, these AI agents may no longer have a shutdown button. In other words, once they are deployed, they may not be controlled or shut down by traditional means.

The problem of control of AI agents

Ryan pointed out that governments and society may be afraid of such AI agents without a shutdown button, because it means that no one (such as Sam Altman or Elon Musk) can intervene or shut down these systems at any time. This situation raises concerns about AI autonomy, especially when AI could make decisions that are not beneficial to humans.

Matthew further discussed this point, citing Eliezer Yudkowsky's point of view, emphasizing that simply "pulling the plug" is not a viable solution even in the face of potential threats. He mentioned that Yudkowsky is skeptical of the idea of "pulling the plug" and believes that this does not really solve the problem.

Concerns about the future

Ryan and Matthew discussed the possible consequences of such AI agents without an off button. As technology continues to advance, AI agents may become increasingly complex and autonomous, even beyond human control in some cases. This situation may not only lead to the risk of loss of control, but also cause widespread social and ethical concerns.

Matthew also mentioned that the potential threats posed by the development of AI may make experts like Yudkowsky uneasy and may even prompt them to re-evaluate the direction of research and development of AI.

The combination of decentralized infrastructure and AI

Ryan and Matthew explored the relationship between this centralized infrastructure (decentralized physical infrastructure) and AI and the potential challenges.

Matthew said he was skeptical of decentralized infrastructure and discussed its intersection with AI agents.

Challenges of decentralized infrastructure

Matthew pointed out that decentralized infrastructure faces challenges in monitoring costs and capital costs in some cases. For example, when it is necessary to ensure that certain data is submitted by specific hardware in remote areas, the monitoring costs may be very high. In addition, capital costs may also be high, which makes the implementation of decentralized projects more complicated.

He mentioned some successful examples of cooperatives, such as law firm cooperatives, because all members are lawyers and can monitor and bill each other. This model is not always applicable in decentralized infrastructure, especially when high-frequency monitoring and high capital investment are required.

Combination of decentralized computing and AI

Despite the challenges, Matthew believes that decentralized computing can be combined with AI, especially in terms of utilizing idle resources. He mentioned a model similar to Airbnb, where individuals can rent out idle computing resources to form a decentralized virtual infrastructure network (DVEN). This model may be more effective in some cases because the validity of the calculation can be verified by the algorithm.

He mentioned the research of a doctoral student at Columbia University, which explored how to ensure the effectiveness of decentralized computing networks. This approach may provide new opportunities for the application of AI because decentralized computing can support the training and operation of AI models.

The “Oracle Problem” of Physical Infrastructure

However, Matthew warned that the decentralization of physical infrastructure faces the “Oracle Problem”. When data from the physical world needs to be delivered to the blockchain, this mechanism that relies on external data sources can become fragile and unreliable. Each data delivery requires the accuracy and reliability of these external data sources to be evaluated, which affects the stability of the entire project.

The Demand for Blockspace by AI Agents

In the discussion of the demand for blockspace by AI agents, Ryan and Matthew explored the impact that AI agents may have on blockchains in the future and how investors can respond to this change.

Ryan emphasized that with the rise of AI agents, the demand for blockspace may increase significantly, which provides new opportunities for investors.

Demand for Blockspace

Ryan suggested that if AI agents consume more blockspace and crypto assets in the future, then as investors we need to plan ahead and seize the opportunity of this demand. He asked Matthew if he thought certain blockchains would benefit more from the demand of AI agents.

Matthew replied that the demand for blockspace by AI agents is related to the characteristics of the blockspace they require. He mentioned some current trends, such as the value capture of meme coins on certain blockchains, suggesting that these chains may attract more AI agents in the future.

Future Blockchain Selection

Matthew believes that blockchains with rich narrative activities (such as meme coins and future NFTs) may be more favored by AI agents. He emphasized that AI agents may focus on certain specific risk management and value storage methods, such as considering Bitcoin as "digital gold."

He also mentioned that investors should focus on blockchains that excel in the narrative economy in order to benefit from the demand for AI agents.

AI Agents’ View of Currency

Ryan and David discussed the question of what assets AI agents might naturally convert to. They believe that it may not be what humans think of as currency, but what AI agents think of as currency that will become the “currency of the Internet,” that is, the currency of the AI Internet. This view leads to further thinking about the future form of currency.

Summary

In this episode, Ryan and David highlight the discussion on blockspace demand, particularly the impact AI agents may have. They remind listeners that while these discussions provide valuable insights, they do not constitute financial or investment advice. As the crypto space continues to evolve, investors need to exercise caution and be aware of potential risks.

Disclaimer

Ryan reminds listeners that these discussions are not financial advice, nor AI advice, and that investing is risky and may result in the loss of funds. They emphasize that while the road ahead is challenging, they are glad to have listeners on this Bankless journey with them.

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