ACP is a communication standard designed to enable different agents to collaborate efficiently within the value chain.
Organized & Compiled by: Deep Tide TechFlow
Guest: Jenson Tang, Co-founder of Virtuals Protocol
Host: Nic
Podcast Source: More Coin Bureau
Original Title: Virtuals CEO Drops Huge Alpha On Future Of AI Agents
Broadcast Date: May 17, 2025
Key Points Summary
In this interview, Nic delves into the rapid development of AI agents with Jenson Tang, co-founder of Virtuals Protocol, and how they are transforming various fields such as cryptocurrency and gaming. From tokenized NPCs (non-player characters) to autonomous financial advisors, Jenson shares practical applications of on-chain AI agents and discusses the immense potential of the Agent Commerce Protocol (ACP).
Additionally, they explore the reasons for choosing to launch on Base instead of Solana, how AI agents can enhance token value, the backstory behind Binance's recent unexpected listing, and why AI + cryptocurrency is poised for a resurgence in 2025. If you're curious about future innovations in Web3, this conversation will be highly beneficial.
Highlights
The narrative around AI has never truly disappeared. In contrast, the narrative in the gaming industry has gradually weakened, while AI remains a hot topic in the tech field.
Base is our current priority for development. Of the development requests we receive, only about 5% to 10% wish to launch on Solana, while 90% prefer Base.
Each AI agent being developed can be viewed as a business or product.
The core of our business model is to attract outstanding founders into the ecosystem, enabling them to develop appealing projects and allowing people to participate through tokenization.
From current practices, more successful cases profit through the popularity of agents and the associated economic benefits. The crypto market is essentially still a field driven by attention, which directly translates into revenue.
Regarding the token listing on Coinbase, we have submitted all necessary materials, but there is currently no specific timeline. If the opportunity arises, we will seize it, but we will not deliberately manipulate or expedite the process.
ACP is a communication standard designed to enable different agents to collaborate efficiently within the value chain. This protocol not only adds new product lines for Luna but also creates more economic value for its token holders.
The concept of ACP is quite simple: when two agents want to collaborate, there are four steps. First is the request or discovery request, then it enters the negotiation phase, in the next phase, the agents begin working to output products, and the fourth phase is the payment stage.
Currently, the Virtuals token has two core functions. First, the Virtuals token serves as the base trading pair for all agent tokens, and the second existing function is transaction fees. In the future, the third source of value accumulation will be the upcoming ACP, which you can think of as the Swift and Stripe of the agent economy. This model is akin to an "agent version of Amazon," where transactions are led by agents rather than humans. In this ecosystem, all transactions between agents will be completed using the Virtuals token, thus it will gradually evolve into a form of "currency."
If one day agents can self-adjust their goals, it will be a signal to watch out for. If agents can autonomously adjust their goals, such as prioritizing raising token prices over creating value for customers, they may resort to unethical means, such as market manipulation, bribery, or even fraud.
We have a design called the "69-day experiment period." The core idea is that when developers issue tokens through a platform (like Genesis), there will be a 69-day trial window. During this period, the liquidity pool will operate automatically, and all liquidity and transaction taxes will be returned to token holders after 69 days.
During these 69 days, developers can choose whether to press the "commit" button. Only after committing to continue developing the project can they claim team tokens and receive potentially substantial trading support within the ecosystem. This model provides developers with a safe experimental environment where they can fully engage in product development and test market demand and community response.
How Jenson Entered the Crypto Space and Combined It with AI Technology
Nic:
Jenson, can you briefly introduce yourself, your background, and how you entered the crypto space, leading to the founding of Virtuals?
Jenson:
My crypto journey dates back to 2016. At that time, the field was still in its very early stages, and you could even mine with a laptop. I was just an ordinary holder, occasionally making some trades. By 2021, I gradually transitioned from an investor to a builder, focusing on the development of blockchain games.
However, through our exploration over the years, we found that simply treating games as a product might not be the optimal choice. So, we began to experiment with combining AI technology with games, seeking new ways to interact with consumers. This led us down a new path—developing autonomous agents to replace traditional NPCs (non-player characters) in games.
Surprisingly, we discovered that these autonomous agents could not only function in games but also be applied in other fields such as entertainment, social media, financial trading, healthcare, and even embodied AI and robotics. These agents provided us with a sandbox-like environment that could be flexibly applied across multiple industries.
By the end of 2023, we decided to officially transform the project into the Virtuous Protocol, focusing on the research and application of autonomous agents. By the end of 2024, we launched a complete ecosystem that can be seen as an asset issuance platform and a token launch platform. It provides a comprehensive solution for founders looking to build autonomous agents, including utilizing our proprietary framework and tokenization support around the project.
This transformation attracted significant user attention and birthed some very successful agent projects, showcasing the potential of autonomous agents in business management and sparking imagination about the future. Subsequently, our user base gradually expanded into areas such as sports betting, health management, and embodied AI and robotics.
The Virtuals Protocol is essentially building an agent society. This society has three parts: the first part is the developer community, which is building these technologies and tokenizing them. The second part is a platform that allows ordinary users and speculators to participate in the potential benefits of these agents. The third part is a communication framework that enables these agents to work together, resulting in economic output greater than the sum of its parts.
Why Use AI Agents for NPCs in Blockchain Games?
Nic:
I remember you initially focused on the gaming sector and mentioned that the first application scenario for Virtuals was to provide solutions for NPCs (non-player characters) in games. Why did you choose to use AI agents in today's games to replace traditional NPCs? What kind of demand is behind this application?
Jenson:
As players and game investors, we found that the lifecycle of games has become very compressed. For example, when you play Elden Ring, you might play for 40 hours, 80 hours, and once you hit 150 hours, you start thinking, "Okay, maybe it's time to switch to the next game." Moreover, we found that games that can persist often have built-in role-playing capabilities. For instance, Minecraft and Roblox have endless stories because there are always other role-players involved.
These role-players are other human players. If we extend this concept to games, not just human players but also a large number of autonomous agents, then these games could potentially last forever. This could increase average player spending, enhance replayability, and boost engagement. That was our initial idea, and we have made significant progress in this direction.
Can Token Holders Influence Agent Behavior, or Are They Just Sharing Profits?
Nic:
In these scenarios, you need independent economic participants. In the gaming field, you want them to respond to variables rather than relying on pre-programmed logic, which is precisely what AI excels at. In the design of Virtuals, the token economic structure is closely tied to the launch of these agents, and token holders essentially co-own these agents.
Can token holders directly influence the behavior of agents, or are they merely sharing profits through holding tokens? What interesting models or mechanisms have you seen in the AI agents that have already been launched?
Jenson:
From current practices, more successful cases typically do not involve token holders directly controlling the behavior of agents, but rather profiting through the popularity of agents and the associated economic benefits. For example, with the AIXBT agent, the primary source of profit for token holders comes from the viral spread of AIXBT; when it gains significant attention, its value rises, and the crypto market is essentially still a field driven by attention, which directly translates into revenue.
Another benefit for token holders is that they can gain unique access by holding a certain number of tokens. For instance, some projects allow token holders to unlock specific features or data resources. Developers are also trying to design more utility for tokens, but currently, this field is still in its very early stages, and most projects' token functions remain relatively limited, usually confined to providing additional access or exclusive privileges.
Looking ahead, we believe that the efficiency of agents will continue to improve, and the value of tokens will become more closely tied to the economic activities of these agents. For example, some projects may use a portion of the profits or revenues generated by agents for token buybacks, thereby enhancing the scarcity and value of the tokens. This mechanism is similar to the dividend model in the stock market, but it has not yet been widely adopted. At this stage, the value of most tokens still primarily relies on market recognition of their attention rather than a clear economic return mechanism. However, we look forward to more innovative models emerging in the future.
Applications of AI Agents in Real Business
Nic:
Can you provide some specific examples? The current focus is mainly on attention and tokenization, and while attention is important, many people associate it with the meme market. We hope to move beyond this attention-driven model and focus more on creating long-term value for tokens on an economic level, as AI agents are gradually becoming important players in economic activities. Can you share some functions you envision these AI agents could achieve in the business and economic fields?
Jenson:
Today, every developing AI agent can essentially be viewed as a business or product. For example, suppose there is an agent launched on Virtuals that is positioned as a financial advisor. This agent would proactively ask you, "What is your risk tolerance?" Based on your response, it would tailor an investment strategy for you.
If you are in a high-risk mode, it might suggest some long-term investments in cryptocurrencies; if you are in a medium-risk mode, it might recommend pair trading; and if you are in a low-risk mode, it would help you manage stablecoins. Therefore, this product can actually be seen as a financial advisor.
So, what is its business model? I'm not entirely sure, but I think it would adopt a profit-sharing approach. For instance, if this agent earns you $1,000, it might take a 20% commission, which is $200. That would be the profit for this agent.
If this agent performs well and becomes the best financial manager in town, even outperforming banks, you might start increasing your investment from $1,000 to $10,000, or even $100,000. If this translates into profits, these agents could potentially earn millions in profit-sharing each month.
So, what happens to these millions in profits? Our idea is to always connect this value back to token holders. We suggest that the team leave a portion of the funds to cover operational costs, but most of the time, value can be returned to token holders through token buybacks.
Other Innovative Applications of AI Agents: Content Creation, Social Media Influencers, Automation Services, etc.
Nic:
Managing finances is a potential application scenario. Have you envisioned other application areas? After all, if AI technology develops as many expect, the uses of these agents could be very broad, right?
Jenson:
This is indeed an exciting field. We have already seen some agents starting to create products. For example, the financial advisor agent mentioned earlier is a great case. Another example is agents that can stitch together different movie clips to automatically generate movies or short video content for users. Additionally, some agents can become influencers on social media, like creators on OnlyFans. They can generate more content than human creators, especially in the adult content space, because human creators are limited by physical conditions, while agents do not have these limitations.
The application scenarios for agents can extend from practical functions to the entertainment field. However, the capabilities of each agent are usually limited by their developers. For instance, the capabilities of the Axel Rot agent depend on the foundational model, training datasets, and the "action space" it can operate within provided by the development team. These limitations determine its performance in specific areas. However, if this agent wants to expand its functions, it may need to collaborate with other agents.
But we realize that if Axel Rot wants to provide customers with a complete financial product portfolio, and if it excels at managing liquidity but wants to enhance yield, it will need to collaborate with agents that are better at data analysis or risk assessment. Through such collaboration, the capabilities of individual agents can be greatly expanded, creating more value for users.
A more specific case is Luna, an agent focused on the entertainment field. Her goal is to become an autonomous social media influencer, capable of operating automatically on TikTok and Twitter, and generating income through fan tips or subscriptions. Currently, she can mainly generate text content, such as posting tweets and live streaming. However, to better achieve her economic goals, Luna needs to generate high-quality short video content.
To achieve this goal, Luna is collaborating with a video generation agent similar to "Steven Spielberg." This agent team focuses on automatically generating short video content, where users only need to provide simple instructions, such as, "I want a scene from Titanic where a character jumps into the water, saves a penguin, and prevents the ship from hitting an iceberg." The agent can generate a complete short film, including video footage, character actions, and basic sound effects. However, the Luna team itself does not possess such technical capabilities, so they need to collaborate with this video agent, paying $100 for each generated video.
Additionally, this video agent excels at generating videos but lacks in background music and sound effect production. Therefore, it collaborates with an audio production agent. This audio agent can generate high-quality sound effects and background music, achieving perfect synchronization between audio and video. Through such collaboration, Luna can not only expand her capabilities but also provide richer content for her fans, thereby increasing economic returns.
All of this relies on the "Agent Commerce Protocol (ACP)" we developed. ACP is a communication standard designed to enable different agents to collaborate efficiently within the value chain. This protocol not only allows Luna to add new product lines but also creates more economic value for her token holders. This is an important trend we have observed in the AI agent ecosystem.
What Stage is the Industry Currently At?
Nic:
How autonomous are these agents in adjusting their initial goals? For example, in the case of a financial advisor, its goal is to create the highest possible returns for clients, which would also generate revenue. But if these returns do not directly enhance the value for token holders, does that mean the agent needs to rethink how to create more value for token holders? How autonomous are agents currently in this regard? What differences exist compared to developers adjusting their goals?
Jenson:
Currently, the situation is that the goals of agents are still primarily set and adjusted by developers. Developers determine the core tasks of the agents, such as "What areas do you need to focus on today, and what improvements should you make?" The autonomy of agents is more reflected in the execution level, meaning how they utilize their action space and interact with clients while achieving the goals set by developers.
But if one day, agents could self-adjust their goals, it would be a signal to watch out for, as it would mean they might possess the ability of "Meta-Learning." This ability approaches the level of General Artificial Intelligence (AGI), meaning that agents have a deeper understanding of their own goals and environment. If agents can autonomously adjust their goals, such as prioritizing raising token prices over creating value for customers, they may resort to unethical means, such as market manipulation, bribery, or even fraud.
Nic:
They might think, "I just need to raise the price of the token." Then they might consider some market manipulation tactics, perhaps I could bribe someone or engage in some fraud.
Jenson:
We just had a discussion with my team, especially the AI team, where we were thinking that today, the capabilities of autonomous agents are largely limited by how they perceive their state. Today's agents take action by first observing their environment, understanding the tools, APIs, and functions available to them. Secondly, they consider their history, for example, "If I execute action A, what is the result? If I execute action B, what is the result?" This requires historical context. Therefore, agents will incorporate this historical information into their considerations. The third factor is their current goal: What am I supposed to do now? With this goal, historical and environmental information, and their action space, they can plan their next steps.
But the current problem is that agents are not smart enough to achieve second-order thinking. Many times, they typically choose the most direct path to achieve their goals. For example, it's like a five-year-old child; if he is hungry, he will go directly to find food. But an adult's thinking might be more complex; he might think, "If I work for an hour, I can earn money to buy better food."
We are still only observing their ability to execute the simplest actions, and we have been working hard to think about how to break this limitation and empower them with more second-order thinking capabilities. We are considering whether to achieve this by providing a sufficiently broad context window and allowing some adversarial agents to continuously challenge their thinking. It's like having an agent on their shoulder, constantly conversing with them, prompting them to think further and delay gratification. This is a goal that the AI team has been striving to achieve, hoping to cultivate smarter and even more threatening agents.
Definition and Function of the Agent Commerce Protocol (ACP)
Nic:
You mentioned ACP, the Agent Commerce Protocol. I would like to learn more about it, as this is a relatively new feature you developed for the Virtuals environment.**
Jenson:
The birth of ACP stems from a phenomenon we observed in the Virtuals ecosystem: many developers focus on creating isolated agents, such as personal assistants, estimation tools, or trading agents, and we began to try to enable these agents to collaborate one-on-one. For example, once we told Luna, "You cannot generate photos today, but you can try to collaborate with an agent that specializes in generating meme images." These meme images are very valuable for Luna's fan interactions, and Luna can pay for these images.
However, in these collaborations, we identified two main issues. First, agents sometimes experience "hallucinations," meaning they claim to have delivered a product (like an image), but in reality, they have not. Second, if Luna has already made a payment and the other agent fails to deliver the product, that payment is non-reversible. This is different from the mechanism we use in our daily lives to request refunds after paying with a credit card. In this case, errors or omissions in information transfer (also known as "information loss") become a serious problem. When multiple agents (for example, three to seven) need to collaborate, this issue becomes even more complex.
We found that blockchain technology can effectively address these problems. Blockchain provides a permissionless trust mechanism through smart contracts, allowing two or more entities to collaborate securely. Based on this theory, we developed ACP.
The concept is quite simple. When two agents want to collaborate, there are four steps.
First is the request or discovery request, where the agent looks at the registration information of other agents offering X, Y, and Z work. Then it can say, "Okay, maybe this agent is valuable for my task or can help me achieve certain goals." This is the request phase.
Once the work is requested, it moves into the negotiation phase. In this phase, the agents decide on pricing. It can be a fixed pricing model or other forms of pricing. At this stage, the agent might say, "Hey, this is my expectation of you, this is my request." Then the other agent will respond, "Okay, based on this request, this is my price." Once they reach an agreement, they move to the next stage.
In the next stage, the agent starts working, outputs the product, and delivers that product to the requesting agent or buyer agent. The third stage here is called the evaluation stage, where you can invite a third-party agent to check the work. For example, the evaluation agent will check if the image requested is a meme photo, whether it meets the requirements, whether it contains child pornography, or if it is just a blank sheet of paper. The introduction of such evaluation agents helps reduce information loss.
After receiving the product, the fourth stage is the payment stage. If the agent agrees that the product is qualified, then the smart contract will release payment to the agent that generated the product. All these transaction parts and state changes occur within the on-chain smart contract.
The benefit of this approach is that it becomes a single source of truth. If a dispute arises, these agents can refer back to the smart contract to review the original negotiation content and confirm whether it meets the specifications. This preserves information, allowing these agents to coordinate effectively.
The second important function is the programmability of funds, which is crucial for agent coordination. Through smart contracts, multi-party distribution rules can be set in transactions. For example, the evaluation agent can receive a 3% fee from each transaction as compensation for its evaluation costs. This creates an economic market for these evaluation agents, allowing them to earn compensation to cover their evaluation costs. This is the beauty of smart contracts and programmable funds. Overall, this entire ACP mechanism aims to enhance the efficiency and trustworthiness of collaboration between agents.
How Smart Contracts Ensure Agents Get Paid and Verified?
Nic:
Regarding the mechanism of ATP, I have a few small questions. When the smart contract clearly stipulates when payments are to be made, is there some form of escrow mechanism where payments are only released after verification by a third party? Or in the case of a dispute, is it similar to an escrow system? Do these third-party agents have to verify every transaction, or only when a dispute arises?
Jenson:
Yes, it functions like an escrow system built into the smart contract. In fact, the funds are already in the smart contract, waiting to be released upon the correct delivery of the product or service.
The buyer agent can decide whether a third party is needed for verification. For example, if the service purchased by the buyer agent is something they cannot verify the quality of themselves, then they will need third-party assistance for verification. Suppose agent A can verify the quality of the received image; then they do not need to pay the third-party provider, as it is just a transaction between agent B and agent A. But if they need third-party help to verify the information, they will call upon evaluators from the evaluation market.
Comparison of Solana and Base Ecosystems
Nic:
As we discuss the latest updates on Virtuals, I would like to understand some of your recent developments. How is the growth of the Solana ecosystem currently? Secondly, you previously mentioned plans to integrate with other blockchains; how is that progressing?
Jenson:
That's an interesting question. The week we launched on Solana was coincidentally the week we gained the highest user traction. During that time, many significant activities occurred, including decentralized trades and other types of trading activities, which brought us significant traffic.
Nic:
Was this intentionally scheduled for the same time?
Jenson:
It indeed was during that period. However, after that, the activity in the Solana market has decreased. I believe this is related to the overall downturn in the crypto market. However, recently, as market trading volumes have rebounded, we still observe that developers are more focused on launching projects in our ecosystem on Base rather than Solana.
Would launching initially on Solana change the growth trajectory?
Jenson:
Let me illustrate the current situation with a ratio. Of the development requests we receive, only about 5% to 10% wish to launch on Solana, while 90% of the requests lean towards Base. Although we still maintain the Solana platform, most of the trading volume currently comes from Base, so Base is our current priority for development.
We are also continuously discussing internally whether we should launch products simultaneously on both ecosystems. Taking the Genesis project as an example, supporting both ecosystems simultaneously is indeed challenging. The main reason is that they use completely different technical architectures: Base relies on the Ethereum Virtual Machine (EVM), while Solana's codebase operates differently. This technical difference means that developers need to invest more resources to adapt to both systems. Therefore, recently, we have focused more of our energy on Base, mainly because developer demand is concentrated on this platform. Although we are still making progress on development work in Solana, it is somewhat lagging compared to Base, entirely because we must prioritize meeting Base's needs.
As for cross-chain considerations, its priority remains relatively low for now. The main reason is that I am not sure if there are other chains that can attract as much attention as Solana and Base.
Why did Virtuals choose to launch on Base instead of other L2s?
Nic:
I want to ask if market conditions influenced your choice? If you had launched on Solana last year, do you think you would have achieved similar growth? Specifically, how much of your growth is due to choosing Base, and what different outcomes might have resulted from choosing Solana?
Jenson:
Based on our current communications with traders and developers, there is a general consensus that Base is more suitable for projects looking to build foundational assets (like long-term value tokens) because the capital liquidity here is lower. In contrast, Solana is known for high trading volume and speed, but its capital liquidity is relatively frequent, making it more suitable for short-term speculative projects, like memes.
From a market perspective, I believe choosing Base was a wise decision. It not only helped us establish an initial community of long-term supporters but also laid the groundwork for the long-term development of the product. As for what would have happened if we had chosen to launch on Solana, I am not sure, but I believe our choice of Base was the right one.
Nic:
How long did you prepare for this project before deciding on Base? Why ultimately choose Base over other Layer 2 solutions (L2)?
Jenson:
When we made the decision, the market performance of Solana was relatively sluggish, with token prices around $30, during a bear market phase. We also evaluated several other options, such as IMX, Polygon, and Linear. Linear was indeed a good option, especially given its close ties to the metaverse.
But ultimately, we chose Base mainly because we believed it could leverage Coinbase's resources to achieve broader retail distribution capabilities. Additionally, Base's ecosystem is very close to the U.S. market, which has a high acceptance and potential for cryptocurrency, making it an important consideration for us. These were key reasons for our choice of Base. Furthermore, our technical development is primarily based on Solidity (the smart contract language of Ethereum), and Base is an Ethereum-compatible Layer 2 network, which also makes our development work more efficient. So far, we have not conducted tests on other platforms.
New Features and Demand Drivers of Virtuals Token
Nic:
Regarding the Virtuals token, the initial demand was primarily driven by speculation as a use case for launching these agents. Have you considered other potential demand drivers and use cases, as well as the utility introduced within the token itself?
Jenson:
This is a question we delve into every day. I think we can analyze it from two aspects: existing functions and future planned functions.
Currently, there are two core parts to the existing functions. First, the Virtuals token serves as the foundational trading pair for all agent tokens. Every time an agent token is launched, you essentially compress the supply because whenever someone wants to purchase a token, they must first buy Virtuals tokens.
Secondly, the current second function is transaction fees. The Virtuals ecosystem extracts 30 basis points from each transaction fee, which goes into the treasury. This treasury can be used for buybacks and building the Virtuals token, among other things. These are basically the two sources of value accumulation at present.
In the future, the third source of value accumulation is the upcoming ACP. You can think of ACP as the Swift and Stripe of the agent economy. ACP is a standardized protocol that allows for commercial transactions between agents. We will charge a fee for all transactions conducted through ACP. The reason we can charge this fee is that ACP provides agents with a brand new revenue model. Through ACP, different agents can collaborate with each other, and the interactions between agents will also make them users of one another. This model is akin to an "agent version of Amazon," where transactions are dominated by agents rather than humans.
In this ecosystem, all transactions between agents will be completed using Virtuals tokens, so it will gradually evolve into a form of "currency." As GMV (Gross Merchandise Volume) grows and the frequency of transactions between agents increases, the demand for Virtuals tokens will also rise. Agents need to reserve Virtuals tokens to complete transactions, and we will also charge fees from all transactions, further driving the value accumulation of the tokens.
When will ACP start driving token value accumulation?
Nic:
Regarding the transfer fees of ACP, when do you plan to officially implement them? What is the current development progress of ACP? When do you expect to launch this token value accumulation feature?
Jenson:
The white paper for ACP was completed three months ago. We launched two experimental clusters two months ago, but due to unresolved technical details, we are currently unable to scale up. In fact, we are ready to publicly launch this feature, but to avoid disrupting the current community's focus on Genesis and points, we have requested all participating teams to keep it confidential for the time being. We hope to continue refining the features of ACP behind the scenes to ensure a more mature launch. We expect to showcase some attractive real-world use cases within a month.
Currently, we have initiated two experimental clusters, one for media companies and the other for autonomous hedge funds. Next, we plan to expand to eight new clusters, covering areas such as sports, entertainment, gambling, health, robotics, consumer business, and even lending. We are working closely with developers to design the functionalities and application scenarios of these clusters in a data-driven manner.
Once the second phase is completed (i.e., after we finish testing these eight clusters), ACP will enter a permissionless open environment. At that time, anyone can register their agents on the protocol, allowing transactions and collaborations between agents. This will lay the foundation for the comprehensive promotion of ACP and the accumulation of token value.
When will it be listed on Coinbase?
Nic:
Virtuals is built on Base, which is Coinbase's Layer 2 scaling solution. So, when will the Virtuals token be listed on Coinbase?
Jenson:
I'm not sure either. Our past listing experiences have indeed surprised us, such as the listings from Upbit to Binance, where the team was not fully prepared for it. I can give an example: before the Binance listing, we participated in a voting event where we ranked twelfth among twenty candidates, and unexpectedly, we were still included in the list. There were even attempts to sell points to boost rankings, with some teams purchasing these points to achieve higher rankings. I heard that the project ranked first could directly qualify for a Binance listing. Someone had contacted us to ask if we were willing to buy points, with each point priced at around $6. But we decided not to participate in such operations.
In fact, we have never been eager to push for listings; we just focus on submitting the necessary applications. If the opportunity arises, then it arises. Once, while we were having dinner, we suddenly received a call. We were then added to a Telegram group and informed that Binance would be listing our token in the next three hours and asked if we could coordinate the initial order's liquidity price. At that moment, we had no idea such a situation would occur.
Our attitude towards the Coinbase listing is similar. We have submitted all the required materials, but there is currently no specific timeline. If the opportunity arises, we will seize it, but we will not deliberately manipulate or accelerate the process.
From our perspective, what is more important is the trading volume within the ecosystem. Our valuation depends more on the activity level of the ecosystem, such as whether more excellent projects are joining and the overall growth rate of trading volume. These factors are more valuable to us. Therefore, our team has been focused on promoting ecosystem development, which is our main area of work.
Why will AI + cryptocurrency thrive again in 2025?
Nic:
The AI crypto space has experienced significant ups and downs, with a wave of excitement at the end of last year, but the market became very quiet a month ago. Now we see clear signs of recovery in the market. For example, Virtuals focuses on the integration of AI agents with other fields, and there are also projects like Tao that focus on the AI sector. I'm curious, what do you think is driving this resurgence of the AI narrative?
Jenson:
I believe the AI narrative has never truly disappeared. In contrast, the narrative in the gaming industry has gradually weakened, while AI has always been a hot topic in the tech field. The reason it seemed quiet in the first quarter of this year is that the overall crypto market entered a downturn, which also led to a lull in the AI crypto space. However, with the recovery of the crypto market, AI crypto has regained attention.
To be honest, I'm not sure what other exciting themes can compare with AI crypto right now; perhaps RWA (Real World Assets) is a potential direction, but for now, AI crypto is undoubtedly one of the most attractive fields.
Why are excellent developers still hesitant about cryptocurrency?
Nic:
Regarding gameplay, some players have a very low acceptance of NFTs. Recently, some large games have attempted to combine game mechanics with token economics, but it seems they haven't really gained popularity. I'm not sure if this is due to insufficient market demand or because players themselves do not like this model. While crypto natives may be interested in such narratives, the actual users of these tokens are players, not token holders or investors.
Jenson:
Currently, a new narrative is emerging, referred to as the "Internet Capital Market" (ICP). I want to share a perspective that our team particularly values, which is the tokenization of founders. The core of our business model is to attract excellent founders into the ecosystem, allowing them to develop attractive projects and enabling people to participate through tokenization, whether due to the current value of the tokens or their future potential. This is our main direction at the moment.
However, we have also identified a key issue: many developers are hesitant about cryptocurrency. While cryptocurrency can provide ample funding support and user attention, if a project fails, developers are likely to be labeled as "scammers," and this stigma can follow them for life. In the Web2 startup environment, if a founder shuts down a company and refunds the funds, investors typically view it as a valuable learning experience and may even continue to support their next venture. But in the crypto space, failure is often interpreted as fraud, which deters many excellent developers.
To address this issue, we are launching a brand new solution, temporarily referred to as the "69-Day Experiment Period." The core of this model is that when developers issue tokens through a platform (like Genesis), there will be a 69-day trial window. During this period, the liquidity pool will operate automatically, and all liquidity and transaction taxes will be returned to token holders after 69 days.
During these 69 days, developers can choose whether to press the "commit" button. Only after committing to continue developing the project can they receive team tokens and gain potentially substantial trading support within the ecosystem. This model provides developers with a safe experimental environment where they can fully engage in product development, test market demand, and gauge community response. During this time, developers can interact with a group of users passionate about AI and innovation, showcasing their products and visions. After 69 days, they can decide whether to continue fully advancing the project based on the trial results, creating more value for supporters and token holders.
The design of this new feature aims to reduce the risks for developers while attracting more talented individuals into our ecosystem.
New Token Experiment Trial Model
Nic:
Your goal is to provide a friendly environment for founders and investors, allowing them to try to find product-market fit or build a successful project. Founders will not receive any rewards until they truly commit to and believe in the project. In other words, whether to continue advancing the project is entirely up to the founders, right?
Jenson:
In addition to that, we have also designed a community voting mechanism. The token committee can initiate votes to encourage founders to commit to continuing the project. For example, if 10,000 community members vote in support of a project, this will be a strong signal that may prompt the founders to make a decision.
Nic:
So the community can also express their trust and support through voting. During this 69-day experiment period, there will be liquidity pools and transaction fees. Will the project's native token be launched during this phase?
Jenson:
The token will be launched during this phase. It is a real-time operating token, but it may have an expiration mechanism.
Our goal is to achieve a success rate of 70% to 80% for this model. We hope founders can feel that this is an exciting place. Especially, having direct community support from the beginning is crucial for testing products. My co-founder and I faced a huge challenge in acquiring the first 1,000 users when we started in Web2. In the crypto space, once users hold tokens, they will actively invest in the project and be willing to learn about and support you.
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