This interview delved deeply into the investment trends, market status, and future opportunities of the AI Agent project. Analyst defioasis shared his investment experience in on-chain assets, memecoins, and AI-related projects, including the rise of key projects (such as GOAT, Worldcoin, Turbo, Pippin, etc.) and the underlying market logic. Additionally, it analyzed investment methodologies, position management strategies, signs of market bubble cooling, as well as the importance of industry trend changes and project narratives.
Please briefly introduce yourself and review when you started researching AI Agents and when you officially started investing money, and what is the overall rate of return so far
defioasis: Hello everyone, I am defioasis. I am usually interested in on-chain data, on-chain assets, and the derived gameplay. Since last year, my main focus has been on playing with on-chain things.
In fact, the research on AI Agents also stems from the exploration on the chain. I have been observing on-chain assets since last year, but pure Memecoins are not really my forte, mainly just watching, and I couldn't really convince myself to play with big money.
The turning point was mainly at the end of October and the beginning of November last year, when GOAT surged to a market capitalization of several hundred million dollars in a very short period of time, and the listing of GOAT futures on Binance made me rethink this track. Of course, before talking about that, I want to talk about some AI-related things before GOAT. Before GOAT, there were two relatively big events, one was Worldcoin, because the co-founder is Sam, the founder of OpenAI, so WLD was treated as the Meme of OpenAI in Crypto, with a fully diluted valuation once exceeding 100 billion dollars; the second was Turbo, which claimed to be an AI Meme created by GPT, and it also surged 200-300 times on the CEX last year. So these two events show that people are very interested in and worth hyping the AI+Crypto theme.
Going back to the end of October last year, after GOAT was listed on Binance futures, I quickly associated it with Worldcoin and Turbo, and Binance has the ability to lead the track. At that time, there were 4 assets that I found very eye-catching, two of which were AI-related, one was ai16z and the other was ACT; the other two non-AI-related were LUCE and BAN. Now, ai16z seems to be much better than ACT, but at the time, the situation was that the founder of ai16z, Shaw, was still a nobody, and ai16z was launched by daosfun, with some issues with the token contract being mintable, and the volatility was particularly large due to the small pool. At that time, I took a position in ai16z at a market capitalization of 25 million dollars, spending about $3,000, but the pool was small and it was once dropped below 10 million dollars due to FUD, so I didn't dare to add more positions. So I finally chose to overweight the more stable and larger-scale holder ACT. ACT can be considered the first investment I officially took a position in the AI investment.
The first one was on November 5th, when I bought the first $3,000 of ACT. Later, I found that it was also available on Bitget, and I gradually bought more than $10,000 of ACT at an average price of $0.022 and a market capitalization of 22 million dollars. But at the time, I didn't even think that the position would be listed on Binance. I remember I was attending a conference in Bangkok at the time, and I was quite surprised. After being listed on Binance, it reached a market capitalization of 7-8 billion dollars, but I actually sold most of it the next morning when it was at 500 million dollars after the Binance news, and the rest haven't been sold yet.
Later, I also observed that AI Agents is the only track that has evolved from a general PumpFun to a vertical and scaled track, so I then delved deeper into this track for investment. After ACT, I also caught some other pretty good targets, such as Pippin, which I also heavily weighted and achieved more than 10 times the return. The overall position for AI investment has reached 7-8 times since November, and has recently pulled back a bit, but is still around 5 times.
What is your research method for AI Agent projects? Can you give an example of the AI Agent project you have researched the most deeply, so that more people can understand your research methodology
defioasis: The current AI Agents or some AI-related assets are very different from the previous AI projects. Now it is basically what is formed by the fair launch of assets based on the PumpFun type, so the project party or the founders may not have much assets, maybe even less than some snipers or big holders. This means that the integrity, vision and background of the founders are very important, otherwise if they are not real-name or have no morals, they can start a new project and abandon the old one at any time. So my methodology for AI Agents first starts from the people, whether they are really doing it, whether they have the ability to do it, and what they can achieve.
Let's take the example of the Pippin project. I first learned about Yohei Nakajima, the founder of Pippin, from the judge and guest list of the Solana AI Hackathon on December 11th. At that time, I saw a Japanese name Yohei Nakajima in the list of judges, and he turned out to be the founder of Pippin. At the time, I found the child-oriented AI Agents quite interesting, as I hadn't seen any similar positioning before. Another aspect is that as a judge, his "weight" is obviously higher than those who need to participate in the competition to prove themselves.
Further research on Yohei Nakajima revealed that he is the founder of BabyAGI, which has more than 20,000 stars on its Github. Searching for information, I found that BabyAGI is quite powerful, as an AGI concept product that has been cited by many media and papers, which proves its strength. In addition, Yohei Nakajima is a partner of Untapped Capital, and the main Web3 project they have invested in is Pixel, which has been listed on Binance. Overall, Pippin's founder Yohei Nakajima is very powerful in terms of both technology and capital resources, and as a real-name and reputable person, the probability of him rug pulling is much lower.
At the time, Pippin's market capitalization was around 20 million dollars, and it actually didn't attract much attention. A market capitalization of 20 million dollars also meets my requirement for buying targets, as I tend to buy in the 10-20-30M range. I gradually bought in a total of 0.2%, which is the maximum single position I define, spending about $40,000. It actually dropped below 10 million dollars later, but I accumulated the position at that time. The founder's background and technology will not change with the price fluctuations.
Later, Pippin announced that it would transform into a framework, from a single AI Agent to an AI Framework, and the valuation has risen sharply. Even though the framework has not yet been realized, the market's recognition of the founder's technology and capabilities has allowed Pippin to soar to a market capitalization of 300 million dollars. Building a framework means it may have the potential to become a split-up project, and the market's pricing for frameworks is currently the highest in the AI agents track, and frameworks or ecosystems that can form a split-up model may have the opportunity to break through a market capitalization of over 1 billion dollars.
Which AI Agents projects are you optimistic about? What are these projects doing? Why are you optimistic about them?
defioasis: I'm optimistic about many, like Pippin, which I still hold, but the market cap is quite high, so I won't talk about it. I usually choose around 20 million dollars, but I actually overweight relatively few.
Currently, there are two main directions. One is to dig for gold in the Solana AI Hackathon, which has just ended, and there are quite a few award-winning projects that I am currently screening. The other is to look at the projects coming to Solana from Virtuals, and they are also collaborating with Jupiter, so there may be a lot of interesting projects in the future, as Virtuals has already proven its success on Base. Of course, I'm also still looking at this area.
This mainly talks about some projects that came out of the Solana hackathon. I'll share one here, but this is not investment advice. A project I've been observing recently is AgentiPy, which is actually an open-source framework that uses Python to connect AI agents to Solana blockchain applications. According to the roadmap, they may launch an autonomous narrative trading bot in Q1 and a launchpad in Q2; the most important thing is that they mentioned the APY token will participate as a flywheel. The research on the APY token economics is also well-designed, although it is also based on a fair launch similar to PumpFun, the team has put 40% of the tokens and locked them linearly in Streamflow for two years, which shows the team's determination. The co-founder and CTO of AgentiPy have been followed by the Solana Official Twitter. Coming out of the Solana hackathon, it's at least a kind of endorsement. Of course, it's still quite early and there is a lot of uncertainty. I'll also pay attention to the projects launched on Virtuals after cross-chaining to Solana.
From a broader perspective, I feel that AI is gradually moving towards the AI Application stage. In addition to frameworks, I will also keep an eye on AI+ applications, especially AI+DeFi, which is the combination of AI's native narrative with DeFi assets and flywheels. There may be some good opportunities, but it is still in a very early stage, and I haven't seen any good targets yet. I'm still just observing, and I haven't acquired any new assets recently.
What are your views on the current state of the AI Agents track and market? Do you think the hype around AI Agents can last a long time or do you think the bubble has already peaked?
defioasis: It has indeed been quite cool recently, but I don't think it will end yet. AI is still a fairly sensible thing, and AI outside the circle is still iterating and developing rapidly, with an upward momentum in technology and capital, which is a more important foundation. In fact, many AI targets are actually driven by the outside world, whether in terms of narrative or talent. Shaw, who was once on the fringes of web2, has now created ai16z, which has become a leader in Crypto AI, influenced by Shaw. I think more technical talents from traditional industries will come to do AI-related things.
From another perspective, from within the circle, AI Agents is the only vertical track that has formed scale from a general PumpFun. DeSci may be half of it, and it's been quite cool recently. Apart from that, there is no other track that can move from generalization to verticalization, which actually shows a strong demand for the AI narrative. The current proliferation of single Agents has forced everyone to do frameworks to compete, and people have become more fatigued by this. So AI+ applications, especially AI+Crypto native narratives, if they can be established, I believe they will bring a new wave of hype and new opportunities.
Any insights or techniques on investment and trading, such as portfolio building and exit strategies?
defioasis: The above is actually talking about the issue of investment targets, but I think position management is more important. The selection of targets is basically based on technology, resources and background, although it is based on a fair launch similar to PumpFun, the research approach is not much different from VC coins, such as technology, resources, background, team, endorsement, as well as the analysis of the token structure, whale addresses, etc.
The focus is on position management. Nowadays, a relatively good asset can generally go through three stages: PvP, second stage and listing. But most of them disappear after PvP. I mainly play the second stage, focusing on the 10-20-30 million USD market cap range, which I call the on-chain sweet spot. Because I found that some good assets will consolidate and fluctuate in this area after the initial surge and pullback. I will only allocate assets in this range. I will pay attention to those that have experienced 70% or more pullbacks and are relatively stable in the 10-20-30 million USD market cap range.
When I see a good asset, I will add it to my watchlist, divided into S-level and A-level. S-level is the one that can form a pattern, like a mother coin ecosystem that can profit from the constantly generated sub-coins, or a trading pair asset that creates a wealth effect, constantly needing the mother coin for trading, which is similar to the flywheel of PumpFun's SOL and Virtuals' mother coins. So S-level is mostly framework-type, with the potential to form an ecosystem or pattern flywheel. That's why Pippin was able to take off, because the market had high expectations for it as a framework.
A-level is mainly judged based on narrative, background, technology, resources and team (without the ability to form a pattern). The background of the founders and founding team is very important, such as Solana Foundation background, many Github stars, having produced attention-grabbing products before, good narrative with the potential to develop into a niche track, etc.
Generally, I will build positions in both A-level and S-level, each time around 2-3000U. But I will be more strict in deciding whether to add positions or increase the position size. I need to observe for a period of time, and the main thing I will look at is what the community and developers are doing on a daily basis.
I also have certain standards for the maximum single-coin holding. The maximum single-coin holding is 0.2%, which means around 4,000U for a 20 million USD market cap. Each time I decide whether to add positions, I will re-evaluate the target, and if I find that the target is inconsistent with the original purchase logic, I will decisively give up adding positions, and the remaining positions will be temporarily held; if the market cap falls sharply below the range, I will also decisively give up adding positions, and the remaining positions will be temporarily held. In principle, I will consider selling when the return reaches 10x, around the 200-300m market cap range.
Building positions in targets is often to ensure I'm on the train, adding positions cautiously and in batches, and setting a hard cap of 1.2x is to avoid being trapped in a single target due to excessive blind confidence. Of course, once I decide to add positions, I will believe in my judgment of the target.
The above is about the second stage gameplay. I feel that the market, whether users, Devs or token factories, are also more familiar with this second stage routine, and it seems to be quite difficult to play recently. So I'm also doing some lottery-style plays now, which is the PvP. At this time, I'm not limited to AI, I've prepared a few SOL, 0.1 SOL each time to buy in, keep an eye on it, monitor and follow some selected addresses, to bet big with small stakes. In the last two days, I've felt that in the current market, the lottery-style play is easier to profit. This may be a probability, with so many plates, as long as the investment is small enough and diversified enough, and some high-probability addresses are used as auxiliary, the lottery-style only needs to hit once to make up for all the previous losses, which will be a good choice in the absence of a big bull market, and in a sense it is also preparing for the potential big bull market. Maintaining a sense of profitability and a positive mindset is very important.
