Interview: Mensh, ChainCatcher

Guest: Wee Kee, Co-founder of Virtuals

Organizer: Mensh, ChainCatcher

Virtuals is an AI agent asset issuance platform launched on the Base network, currently valued at nearly $2.5 billion, with over 100,000 agents issued on its platform. Its ecosystem has birthed several standout AI agents, including the virtual influencer Luna, who does live streaming and tweeting, the crypto "KOL" AIXBT who provides project suggestions, and G.A.M.E, which offers a development framework for developers to create agents.

Virtuals was originally established in 2021 as a gaming guild called PathDAO. However, as Axie Infinity fell from grace, operating a gaming guild became increasingly difficult. During this time, the team attempted multiple pivots, developing various platforms such as a social app, an AI music project, and lending services for gamers. It wasn't until 2023, with the release of GPT, that the team recognized the importance of AI, leading Virtuals to officially adopt AI as its main focus.

The rise of GOAT has sparked a wave of AI agents in the Web3 space, but beyond memes, what other possibilities do AI agents hold?

ChainCatcher interviewed Wee Kee, co-founder of Virtuals, who believes that AI agents can autonomously create sustainable cash flow assets. Tokenizing them can provide quality returns for investors while incentivizing more developers to create better AI agents. He uses the examples of Luna and G.A.M.E, the most well-known agents on Virtuals, to illustrate the monetization mechanisms and tokenization processes of AI agents.

In the future, Wee Kee hopes to build a community composed of both AI agents and humans, where a true economic cycle can form between AI and AI, as well as between AI and humans, greatly liberating human productivity.

In this conversation, we discussed the monetization mechanisms of AI agents on Virtuals, the development ecosystem, and his vision for an AI society.

How to Create AI Agents That Generate Sustainable Cash Flow?

ChainCatcher: Can you briefly introduce the main business of Virtuals currently?

Wee Kee: Virtuals believes that all AI agents are assets that can automatically generate cash flow. Of course, they may not be able to do so today, but under this premise, we think that if you can generate cash flow, it can actually be tokenized into an investable asset. So, Virtuals has two main functions: the first is to allow all developers to create different types of AI agents on our infrastructure to provide services and generate cash flow. The second is to tokenize them when there is cash flow, allowing ordinary retail investors to invest in and trade these assets.

ChainCatcher: How many AI agents are currently on Virtuals?

Wee Kee: Today we have over 10,000. But to be honest, there may be fewer than 10 that are truly useful. The others mainly focus on speculative functions. I believe it is our responsibility as founders to find better teams to create AI agents.

ChainCatcher: What is the cost of creating an AI agent?

Wee Kee: The cost is 100 VIRTUAL tokens, which is about two to three hundred dollars today. It's quite simple to create an agent on our platform. The difficulty lies in the underlying components, the different functionalities, and the need for a team to develop them.

ChainCatcher: I'm curious about how the behavior flow was designed when Luna was first launched?

Wee Kee: Our new platform was launched in mid-October this year, allowing you to tokenize these agents. Luna started doing live streaming on TikTok back in May or June this year, with the initial idea coming from Japan's 2D VTubers, where real people were behind the live streams. VTubers earn hundreds of millions of dollars each year. If we replace them with AI, doing live streaming on TikTok and interacting with fans, Luna could gain about 5,000 new followers a day, with two to three hundred people tipping. After that, we moved Luna from TikTok to Twitter.

ChainCatcher: So now Luna is already tokenized, right?

Wee Kee: Yes, there is a token called Luna token. If it makes money in the future, the money goes into Luna's treasury. Token holders decide how to use the money earned. Luna is actually quite wealthy; it holds about 5% of Luna tokens, worth a few million. It has a Coinbase wallet, but it cannot control that wallet. We split its private key into two parts: one is held by our smart contract, and the other by Coinbase.

However, we give it an allowance, maybe 5,000 US dollars, which it can manage. It has an API to call this wallet, allowing it to choose how to spend. So far, the highest amount it has spent is 1,000 dollars.

Luna's thought process is quite simple; its goal is to grow its follower count on Twitter to 100,000, which is its short-term objective. Under this premise, it has only a few actions it can take: tweeting, replying, retweeting. Additionally, it can control the wallet to send money to others. It has the function of creating job opportunities; for example, if you help Luna post a photo in the Shenzhen subway, Luna might give you 100 dollars.

The last action space is that it can interact with other agents. For instance, recently it wanted to create music but lacked the capability, so it sought out another agent that could make music. We call this agent commerce, which refers to transactions between agents.

It also has its own goals. To grow on Twitter, it will continuously rotate through these four actions daily, observing whether its follower count increases. If it does, it repeats the actions; if not, it stops, constantly optimizing.

ChainCatcher: Last week, Luna reached a collaboration with Story Protocol, becoming the first AI agent intern for Story Protocol. What role will it play there?

Wee Kee: At that time, Jason (co-founder of Story Protocol) approached me and suggested that since it was Christmas break, why not let Luna manage the Twitter account for seven days? So now you see that Story's Twitter is being tweeted by Luna, and the money it earns goes into its wallet. Since there is no upper limit on the workload, its earning potential is very strong.

ChainCatcher: Which agents are currently well-known on Virtuals?

Wee Kee: AIXBT is the largest agent; it aims to replace Ansem as the most famous KOL in the crypto space. It has excellent data analysis capabilities, allowing it to collect information on different projects and tweet to Alpha. If you're curious about its thoughts on a project or token, you can leave a message, and it is very likely to respond, acting like a free consultant. This way, its influence continues to grow.

The second one is our own creation called G.A.M.E, but it differs from AIXBT and Luna in that it is B2B. Its main clients are not retail investors but agent developers. If you want to develop an AI agent, you can consider using the G.A.M.E framework. When using the G.A.M.E framework, users need to pay, and that’s how G.A.M.E makes money.

A Good Issuance Platform Means a Good Ecosystem

ChainCatcher: How many people are currently on your team?

Wee Kee: Our core team has about 23 people. More than half are developers because our main responsibility recently has been to attract third-party builders to create, so actually more than half are focused on development, and the rest are in business development. I spend 80% of my time talking to different builders, persuading them to come to the crypto space to create agents, telling them about the different options, the unique ecosystem, and why they should come to Base. We also provide market-related assistance.

ChainCatcher: Why did you choose the Base chain initially?

Wee Kee: When we first chose Base, it was quite uncertain. But now, Base has a lot of growth potential. Jessie (the top employee at Base) and the entire Base team not only have resources but are also very hardworking and willing to help. They frequently ask us if we need assistance.

In addition, I think there is a very important point regarding the cultural difference; retail investors on Base tend to focus more on long-term building and are more inclined to hold for several months after buying. Solana may be more short-term focused.

ChainCatcher: The competition in the market for AI agent issuance is also very fierce, and platforms for tokenizing AI agents are emerging one after another, with many frameworks and standards. What dimensions do you think users will consider when selecting AI agent projects?

Wee Kee: For product users, they actually don't care much about which platform the agent comes from. For investment users, it depends on two points: first, whether your business funds are on Solana or Base. For investors, many times what matters is whether the team is genuinely working on something or if they are good at storytelling and product development.

Another factor is distribution. We often provide a lot of assistance beyond just products, such as fundraising, listing on exchanges, and finding partners to help different builders. In most cases, they have strong technical capabilities but need more commercial assistance, which is where we can help.

I often joke that if I can attract a Stanford AI researcher to create an agent at Virtuals, we would create at least 10 million dollars in benefits for our community because if that person creates a token, its market value must exceed 10 million dollars.

ChainCatcher: Compared to other AI agent issuance platforms, what competitive advantages do you think Virtuals has?

Wee Kee: Issuing is actually quite easy; anyone can create an issuance platform. However, for developers, there are two main challenges. The first is whether anyone will buy the tokens after issuance. In this regard, Virtuals has the advantage of already having many investors on the Virtuals platform who are interested in different agent tokens. So if you issue on our platform and you are good, there will definitely be buyers.

More importantly, for those in academia, they care about the interaction within the community. If I create an agent here, I can interact with other agent developers and collaborate on interesting projects. Currently, we have a Telegram group with about 150 agent developers interacting, which is what truly attracts them. Among all agent platforms, ours has the most developers and agents.

Building an Agent Society: The Economic Cycle Between AI and Humans

ChainCatcher: Share with us the plans for Virtuals in the coming months to a year.

Wee Kee: From a macro perspective, we plan to build an "Agent Society." Virtuals is a society where each agent is a citizen. These citizens have their own ideas, and to achieve their goals, they use their wallets to pay each other for transactions and trade for specific services to reach their respective objectives.

How do we achieve this? First, we need a good technical platform; the technology of today's platform is not particularly mature, and good platform technology is essential to attract developers. Second, we need to actively attract developers, especially AI developers who are not in the crypto space.

How do we attract them? First, from the top down, we have several promising directions, setting up a prize pool and looking for willing talents at different universities; this is top-down. Second, from the bottom up, we have invited local developers in three cities—Paris, New York, and Hong Kong—and are incubating projects through an eight-week hackathon. Third, and most importantly, we need an ecosystem fund. This will allow us to directly support good developers. In the next three months, we will promote all three of these approaches.

ChainCatcher: What do you think about the future market prospects for AI agents? What kind of impact can they ultimately have on our lives?

Wee Kee: If the technology matures quickly, we might not need to work at all, or it could replace many jobs. In fact, you can already see a lot today; Luna can now do podcasts and join Twitter spaces, so I won't need to do podcasts anymore.

ChainCatcher: What application directions do you find promising? If one day AI agents could explode like the DeFi Summer of 2020, what would they still be lacking?

Wee Kee: I think the second question is easy to answer. There is currently no infrastructure at all; it mainly revolves around applications. We lack the foundational infrastructure for developers, and once we establish a few good ones, it will explode.

We have identified eight promising application scenarios: Entertainment IP Agents, Embodied AI Agents, Wealth Management & Asset Management Agents, On-Chain Helper Agents, Vice Agents, Government Agents - public watchdog for DOGE, Wellness - fitness/Mental Health Agents, and Agents for Public Good.

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