Editor's Note: This article discusses how the yb effect can improve one's research efficiency in the cryptocurrency and AI agent fields by using the Cookies.fun tool. Although he spends a lot of time researching every day, he often misses important trends, so learning how to more intelligently track market dynamics, analyze agent projects, track KOL mentions, and track token holders can help him discover emerging projects and trends and improve his information acquisition efficiency.

The following is the original content (edited for easier reading):

Through Cookies analysis of user mindset, intelligent interaction, and agent metaverse games, I have never considered myself a trader, and in fact I may never be one.

Therefore, I don't mess with complex "tools", have no price alerts, don't spend time on products like the "Bloomberg Terminal", and absolutely don't touch leverage or perpetual contracts.

Everyone probably knows by now that my style is to pick a few projects or trends that interest me and then spend a lot of time delving into the details. This is also why I can consistently produce two in-depth 3,000-word analyses per week. However, I have to admit that I do feel overwhelmed in keeping up with all the developments in the crypto x AI field, which is part of my job.

Every morning when I wake up, I always find something that shocks me that I didn't know about. I'm not saying I need to understand every project and drive myself crazy (most of them are just nonsense anyway). But I do feel that I'm still missing out on some very important developments.

Let me ask you a question: if I spend more than 10 hours a day researching these topics and closely follow crypto Twitter, why do I still feel like I'm not keeping up and missing so many new narratives? I think the answer lies in my low information input efficiency. I work hard, but I don't have a smart enough strategy to stay on top of things.

Doing research and writing is one thing (I think I'm still pretty good at that). But the other part of the job is knowing what topics to research and when to research them. Based on this, let's talk about how I will improve my acquisition of projects, trends, and narratives. The key is that this is not something I want to spend a lot of time on, but rather to establish a daily routine that only takes 10 minutes in the morning over a cup of coffee, so that I can know what the crypto agent Twitter is focusing on.

First, I will focus on using Cookies.fun. To be clear, this is not an ad post, I just feel that by seriously integrating Cookies into my workflow, I can better stay on top of things.

This morning, I decided to spend about $7,500 to buy 10,000 Cookie tokens to unlock the advanced features.

Seizing the Opportunity

Over the past few months, the Cookies.fun team has left a deep impression on me.

When Goat launched in October, the team immediately realized that the agent field would be the main narrative of this bull market.

So they decided to go all out and build the best analysis and data platform for AI agents.

While there are other tools like aiagenttoolkit and kaito (not limited to agents), I think for most people's needs, Cookies is undoubtedly the best choice right now.

Last December, I had the opportunity to communicate with the founders of Cookies.fun and was impressed by their discussion of their plans for the next few months and how they intend to keep the product as crypto-native as possible (such as token gating features, in-depth crypto Twitter analysis, etc.).

Tool Overview:

Tracking over 1,000 agents: including their heat on crypto Twitter, social media interactions, market capitalization and influence comparisons, etc.

The team is indexing on-chain data and social media data to comprehensively analyze the dynamics of this field from both qualitative and quantitative perspectives.

The basic features are open to everyone, and anyone can explore on the website. You need to hold 10,000 COOKIE tokens to unlock the advanced features. The market cap of the COOKIE token is currently between $150-200 million, and it just went live on the Binance perpetual contract today.

In addition, it also provides rich APIs for integration by other projects. For example, Virtuals has integrated the "Mindshare" feature into its interface.

Free Features

This section outlines the state of the agent field: the number of agents and the market capitalization.

I'm not particularly concerned about the number of agents, as many of them are projects of average quality. But the market capitalization metric is indeed very useful, as it shows how much capital has flowed into the crypto agent field.

I'm not saying we should compare it to other fields, but I do find the chart provided by Messari interesting. I'm surprised to see that the trend of the agent field is very similar to the DeFi market cap in 2020/2021.

The peak market cap of DeFi was around $65 billion, and then the entire crypto market crashed in May 2021 (who else remembers that terrible period?).

We are currently about 5 times away from that number... maybe we can use this as a potential reference point. But as I mentioned in my previous article, don't be overly influenced by these cyclical comparisons.

How are the Key Agent Ecosystems Performing?

Currently, it's mainly Virtuals and ai16z, but I'm curious to see what changes will happen in the next 6 months.

Earlier today, I read an article about the new agent framework Pippin, and I think sharing the first two paragraphs is meaningful. Although I don't have much comment on the framework itself, the following quote reminds us that we shouldn't be overly dependent on any one ecosystem right now. After all, Goat has only been online for 3 months!

A common phenomenon in the crypto space, especially in emerging hot fields, is that many people find a "good project" and form a tunnel vision. This approach may be effective in the short term, but what happens when variables change and you don't adapt in time? In a field with only 4 months of history, it is very naive to think that the current leaders will always be ahead, especially as more advanced developers and technologies continue to emerge.

—JW100x

Mindshare of AI Agents

In the past two months, I've never used the term "Mindshare" as frequently as I do now. But the fact is, it is indeed important, as it can help us understand the market's focus.

Currently, most of the Mindshare is dominated by platforms and big players like aixbt and zerebro. But interestingly, why are those small players with Mindshare below 5% suddenly emerging? Has something noteworthy happened?

Index Table

This feature is self-explanatory, basically displaying an overview of all the agents, which can be sorted by Mindshare and market capitalization.

It seems that an obvious approach is to look for projects that rank unusually high in terms of mindshare but have relatively low market capitalization, in order to uncover emerging narratives. So if a project with a market cap of less than $10 million has a mindshare comparable to a project with a $100 million market cap, there is likely something new brewing.

KOL Mentions

This is a really cool feature. You can see which KOLs have mentioned a certain token on Twitter and directly jump to their tweets. This is essentially tracking the types of influencers involved and how they are impacting mindshare. It's also interesting to see how early some people got involved and check how they discovered the token. This is a great way to refine the sources you use to uncover new narratives.

To be honest, this is a very creative feature that I didn't even realize I needed.

Advanced Features

Holders and Whales

For each token, you can see detailed holder distribution to understand the proportion controlled by insiders. Specifically, I think the percentage held by the top 10 holders is particularly important for projects that are less than a month old and haven't yet gained traction. This is the simplest way to judge whether a project truly has an execution plan or is just a "rug pull" project. The only caveat is to make sure to check if the developers have locked their tokens in any liquidity pools (if so, the holder distribution may not show up, but I want to emphasize this as a strong positive).

The reason I think this metric is important in research is that sometimes ambitious, imaginative ideas come with a contract address and a Twitter account. But the reality is, are these visions currently viable? Or just empty talk? For example, last November I mentioned a project called CHAOS, thinking it had a cool robot + agent vision, and while I still find the concept interesting, the project ultimately turned out to be a complete waste of time, and I'm glad I didn't invest more effort into researching it.

Social Media Engagement

This is a great way to see how a token is performing in terms of content publishing and what tweets are resonating the most with people. Not much to say here, other than it saves me a lot of time not having to go through different accounts and play with Twitter lists.

Mindshare Dashboard

The next two screenshots are from a special section where you can access the detailed mindshare dashboard provided by S4mmyEth (if you're not following him yet, you really should).

This chart shows the latest momentum changes. Given how active I am in this space, I'd say this chart is probably the one I use the most. Any fluctuations within a 12 to 24 hour window are something I need to investigate, so I can get a deeper understanding of any new trends. For example, suddenly (at least for me) it felt like there was a massive shift this week towards agent x metaverse/virtual character, and I had a hard time understanding why. I did some digging and found that Holoworld was a major driver. This also prompted me to review the relevant documentation and form my own views.

The second chart is similar to the first one, but it compares market capitalization and smart engagement on a weekly basis, essentially to judge whether a project is a short-term hype or can sustain interest. I'll particularly focus on projects that continue to see growing smart engagement even when there are pullbacks in the agent space.

Market Cap vs. Attention Scatter Plot

Finally, one feature worth mentioning is the market cap vs. attention scatter plot. This is a really great chart because it gives you a real-time view of which potential projects are "about to pop". The screenshot above is a zoomed-in version, and you can clearly see aixbt, whose market cap is far below its attention. This is mainly because it's not a "agent framework", and the current narrative trend is to pour a lot of capital into the "L1 projects" infrastructure we mentioned in our Tuesday article.

But if you zoom out to the bottom left, you start to see some interesting alphas. I've zoomed the chart out by 4x and focused on all agent projects with a market cap under $20 million. To my surprise, there are so many projects I've never heard of before. But at least now I know Seraph, Kudai, Kween, Trust, etc. are worth looking into. This helps me avoid getting stuck in my own little biased bubble and greatly simplifies my assessment process.

It's important to note that just because these charts suggest I should look into these projects doesn't mean I'll dive deep into each and every one of them. All the projects on the chart may not be worth my time at all, but the key is this approach is clearly a more effective project screening method than endlessly scrolling through Twitter for alpha.

That's all I have to share about the Cookies platform today. I know the content above is quite "trading-oriented", which is a bit strange for me, as I've always hated looking at charts in projects. My preference is clearly whitepapers and conversations with founders.

But I think it's time to correct some of my biases and understand that the attention and smart engagement metrics Cookies provides are different from regular trading strategies.

If one of the success metrics in the agent space is understanding the changing direction of the metaverse, then it's my responsibility to find ways to filter out the most important information.

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