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AI Agent Alpha Methodology: Taking Max and Alchemist AI as examples, why is the combination of "platform + market" more popular?

AI Agent Alpha Methodology: Taking Max and Alchemist AI as examples, why is the combination of "platform + market" more popular?

ChaincatcherChaincatcher2024/12/13 18:44
By:Deep Tide TechFlow

The former makes products, while the latter buys and sells products.

Author: Deep Tide TechFlow

Another week dominated by the AI Agent sector, have you found your Alpha?

Top tokens like ai16z and Fartcoin have been rising steadily, while at the tail end, you can even see hundreds of tokens claiming to be AI Agents appearing simultaneously on monitoring lists.

With so many options, how do you choose?

If you're not a professional P player, an opening sniper, or a networking master in the crypto industry, aside from being envious of others' win rates, energy management, and information density, rushing in after FOMO often leads to becoming a buyer. How can you judge whether a project truly has potential?

AI Agent Alpha Methodology: Taking Max and Alchemist AI as examples, why is the combination of

From the perspective of an ordinary investor, you may not have a reliable way to make judgments.

In the process of selecting content materials and observing the market, the long-term losing editor also feels a similar sense of powerlessness -- unable to keep up, unable to buy in, unable to break even, and unable to find the complete context.

Every second in the market is blurry and chaotic, yet every so often, there seems to be a clear and distinct pulse.

Clearly, an ordinary editor trying to take the market's pulse would be laughed at; the following thoughts are shared merely as a reference, as these remedies have at least somewhat cured the editor's own losing streak.

Differentiation in the AI Agent Track: Applications to the Left, Platforms to the Right

First, looking at the overall market, the AI Agent sector has undoubtedly been a hot track in the past week or two. Especially with the recent launch of GOAT spot trading on OKX yesterday, it has reignited enthusiasm across the entire AI Agent sector.

AI Agent Alpha Methodology: Taking Max and Alchemist AI as examples, why is the combination of

However, beyond the unsustainable general rise, there seems to be a growing sense of differentiation among the projects emerging in the AI Agent sector:

  • Differentiation 1: It is a dedicated AI Agent application that solves a specific type of problem or has a specific identity/style.

Representative projects: AIXBT, Truth Terminal

  • Differentiation 2: It is not a dedicated AI Agent application, but it provides you with a shovel to create more new applications.

Representative projects: Virtuals, ai16z (Eliza framework), Empyreal SDK

AI Agent Alpha Methodology: Taking Max and Alchemist AI as examples, why is the combination of

Roughly speaking, this is somewhat an evolution of applications vs. platforms: from AI Agents being able to issue a token, to having a platform/tool that allows more AI Agents to issue tokens.

Of course, this argument is not entirely accurate; aside from Launchpads, some tools do not allow AI Agents to issue tokens but provide an environment that makes AI Agents more usable. Essentially, this logic is not about a single-point application but about building platforms and ecosystems:

The more usable and functional it is, the more reasons there are for the token to be backed after assetization, making it more attractive to speculative funds.

In fact, this logic may just be a replay of history.

In 2017, ICOs were all the rage, and every project could issue tokens through ICOs, but ultimately Ethereum became the largest ICO platform after ICOs, allowing various projects to deploy and issue tokens through smart contracts.

Now, with the popularity of AI Agents, every Agent can issue a token independently, but there are also framework and platform-type projects that allow everyone to quickly create AI Agents through various low-threshold, no-code, or natural language methods.

AI Agent Alpha Methodology: Taking Max and Alchemist AI as examples, why is the combination of

History never repeats itself, but it often rhymes. In the main thread of creating assets, the core has never changed.

Attention Drives, Funds Stir

Note, the editor is not saying that platform/framework projects in the AI Agent sector are stronger than pure AI Agent applications.

Strength is not determined by the direction of the project but is the result of market capital games flowing in and out. Let's use a more blunt assertion to illustrate -- capital will go to places where the story "lasts longer."

What does it mean for a story to last longer?

We have certainly seen projects that explode in a day, but more often, there are short-lived projects whose heat lasts only 1-2 hours. These tokens can attract a large amount of capital in the short term but will also see funds quickly withdraw.

From a more understandable perspective, it means that capital believes, "this story won't last long."

Projects that can tell their stories longer are better at attracting attention. And attention drives heat, while funds stir up price fluctuations.

AI Agent Alpha Methodology: Taking Max and Alchemist AI as examples, why is the combination of

To be more specific:

  • Look at Memes = Look at their angles

  • Look at AI Agents = Look at what they claim they can do

Thus, the question transforms into which AI Agents claim to do things that you believe they might be able to do for a longer time?

After reviewing so many projects, the editor feels that the current AI Agents can roughly be categorized into several types from the perspective of what they do (the original classification inspiration comes from this article ):

AI Agent Alpha Methodology: Taking Max and Alchemist AI as examples, why is the combination of

  1. Personalized Imitators

Simulating intelligence and mimicking human behavior through dialogue. Their job is not to solve problems but to make people feel sufficiently personalized and humanized.

For this type of Agent, personality is their brand.

Typical representative: Bully, a sharp-tongued BOT

AI Agent Alpha Methodology: Taking Max and Alchemist AI as examples, why is the combination of

  1. Efficiency-Seeking Supervisors

Analyzing complex workflows to accurately translate human intentions into backend processes. This type may not have personality, but it is definitely efficient, helping you save time or solve specific problems.

Typical representative: Simmi AI, a Twitter bot that helps you issue a token with a single sentence.

AI Agent Alpha Methodology: Taking Max and Alchemist AI as examples, why is the combination of

  1. Autonomous Experimenters

Managing wallets, interacting with systems, and even initiating tasks without manual input. However, their autonomy is limited, waiting to be triggered rather than being fully sci-fi and self-operating.

Typical representative: Truth Terminal, the beginning of everything.

  1. Platforms/Frameworks Supporting the Above Types

You can create a sharp-tongued AI or a bot that helps you issue a token with a single sentence, regardless of motivation, but you cannot escape some necessary components:

To create an AI Agent, you need investment in models, data, and prompts; to issue an AI token, you need a Launchpad.

Typical representatives: Virtuals (launchpad), Eliza (creation framework)

If you rank the current tokens in the sector by market cap, it is not difficult to see that the leading projects generally fall into this classification.

AI Agent Alpha Methodology: Taking Max and Alchemist AI as examples, why is the combination of

So, which of the above types of projects do you think will have a longer-lasting story?

First, outside of the aforementioned projects, purely external event/IP-driven projects, if the event itself occurs as a single point, then its influence and longevity will diminish, and the token itself will bleed out faster. For example, Ban Banana is a very obvious case, and Luce also shows some decline.

Within the AI Agent sector:

  • Projects that can create assets internally, due to the UGC-generated assets (Agents) being a relatively multi-point concept, their influence and longevity will come in waves, as they can always produce a new Agent from their platform every now and then. Correspondingly, in terms of assets, their own token may fluctuate, but it still spirals upward, ultimately leading to a high market cap for the parent token and several leading AI Agents emerging from the child tokens.

AI Agent Alpha Methodology: Taking Max and Alchemist AI as examples, why is the combination of

  • Projects that can continuously output content, due to the Agents' applications constantly chatting and conversing, will strengthen their personalized brand. If you find it interesting, engaging, or a wealth code, you will continue to pay attention. And attention means capital buying in, so you can see their rise.

However, among these two, the latter can easily be cornered; for instance, when you think of sharp-tongued AI, you immediately think of Bully, leading to attention being concentrated on just a few Agents, making the success probability far lower than that of platform-type projects.

Therefore, playing in the AI Agent sector generally requires you to have a good concept, one that (framework/programming platform/token issuance platform…) can create more assets, as it seems that capital has a higher sustainability in buying into such projects.

MAX and Alchemist AI: Examples of Platform + Market Play

The above are some methodologies the editor uses when looking at projects, which may not be correct but can provide a reference for project screening standards.

If you follow the idea of finding platforms/frameworks, you will find at least two projects worth noting in the past week, both of which adopt a "platform + market" combination. (Note: NFA, not for profit, just sharing projects I've seen)

Platform: A platform that helps you quickly build AI Agents or quickly create products using AI Agents.

Market: The products created can be traded on an internal market, further driving activity and platform heat.

  1. $MAX and Distilled AI, front store and back office model.

CA:

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Market cap: 28M (6M on Monday, an increase of about 500%)

MAX itself is a female AI Agent persona, and you can directly engage in conversation with her.

However, her unique personality is that she is a BTC bull enthusiast, and when you chat with her, she will continuously promote the benefits of Bitcoin; at the same time, she also comes with a Bitcoin prediction market. You just need to click on her avatar to jump to this prediction market page, where you can predict and bet on Bitcoin's future price using $MAX tokens.

AI Agent and betting asset gameplay are fully engaged.

AI Agent Alpha Methodology: Taking Max and Alchemist AI as examples, why is the combination ofAI Agent Alpha Methodology: Taking Max and Alchemist AI as examples, why is the combination of

However, MAX is just an AI Agent; the real attraction that has caused her token's market cap to rise from 6M to around 28M in the past week comes more from her underlying front store and back office model:

Using MAX herself to attract traffic, then allowing more people to use the underlying AI Agent creation platform (++ click here to visit ++).

The creation platform behind MAX actually comes from Distilled AI, a decentralized protocol that provides developers with infrastructure for accessing confidential computing, private data processing, distillation protocols, data DAOs, and secure access management.

This protocol is also supported by another L1 dedicated to AI, oraichain.

With Distilled AI, developers can build advanced applications that require AI agents to learn from private data in personal and collective settings while executing various operations autonomously in Web3 under absolute data privacy.

This model is very similar to the relationship between Luna and Virtuals. However, currently, the Distilled platform does not have a parent token online, and all value transfers on the platform are conducted using MAX tokens.

You can also discover more different types of Agents in the Distilled AI Marketplace, similar to a built-in store for GPT.

Currently, using other Agents in this market does not require payment, but all agents themselves need to hold and stake $MAX to operate; it is possible that there will be other relationships with MAX and the platform's parent token in the future.

AI Agent Alpha Methodology: Taking Max and Alchemist AI as examples, why is the combination of

At the same time, according to project descriptions , these AI Agents created by others in the market can also be tokenized, similar to the launch mechanism of Pump.fun, where when the market cap of the newly created token reaches 66k, it is supported by a bonding curve mechanism for token launch.

The obvious pattern we can see from this is:

First, a friendly AI persona leads the way, attracting you to use it.

Second, the platform has the capability to create AI Agents and empowers the platform's parent token (currently MAX) with consumption and staking functions.

Third, there is a concept of an app store and market, with a price discovery mechanism that filters out other popular AI Agents, expanding the platform's influence.

  1. $ALCH (Alchemist AI ) - a no-code application generation platform described only in text.

Market cap: 130M (27M on Monday, an increase of 500%)

CA:

HNg5PYJmtqcmzXrv6S9zP1CDKk5BgDuyFBxbvNApump

If the above MAX example is a complete replica of Virtuals, then Alchemist AI has taken a different approach:

You don't create different AI Agents; instead, you utilize public AI capabilities to create different applications and products.

AI Agent Alpha Methodology: Taking Max and Alchemist AI as examples, why is the combination of

The project's name already indicates its function, which is to "alchemy" by inputting natural language, and the AI behind the Alchemist AI system will automatically help you process it, thus generating your work.

The entire process is also very simple; link your wallet, input the description of the application you want, and the platform will run for a while and then generate the corresponding program for you (for example, in the screenshot, the editor is trying to generate a game).

Of course, you can also download this work or further refine it through dialogue with the AI on the platform.

In fact, the concept of "no-code development platforms" is not new, but in the context of the crypto market's AI Agent sector, it represents another breakthrough. Using the same AI capability to create different works has significant value for community dissemination.

From community feedback, people have creatively used Alchemist to create a Solana dog coin screening and analysis evaluator:

AI Agent Alpha Methodology: Taking Max and Alchemist AI as examples, why is the combination of

In reality, this is similar to leveraging GPT's capabilities to create more scenario-oriented applications, except that Alchemist has its own front-end page and can gain more traffic value through operational events and community promotion.

Here, the role of the ALCH token is:

  1. If you want to create higher quality works with better precision, you can consume ALCH to enable a paid mode, and the results produced by the AI will be better.

  2. Consuming a certain amount of ALCH tokens allows you to list your completed works on the built-in market.

  3. Others need to pay with ALCH to purchase and use your products.

This is also a platform + market logic, providing you first with a usable product development platform, then embedding the functions of circulation and transfer of works into the token, giving the token more value.

However, currently, the project's page and the AI's implementation effects are still relatively rough, and the project is upgrading to version V2. But the market cap of ALCH has rapidly surpassed 100M within a week, indicating a high level of market recognition for what it aims to achieve in the short term.

Overall, both examples have coincidentally adopted the platform + market gameplay, with the former focusing on product creation and the latter on buying and selling products.

But this does not mean that projects gathering these two elements will necessarily rise; this is merely a case study to help everyone better judge and screen the value of the new AI projects emerging daily.

There are no perpetual victors in the crypto market; the search for Alpha remains a long and arduous journey.

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Disclaimer: The content of this article solely reflects the author's opinion and does not represent the platform in any capacity. This article is not intended to serve as a reference for making investment decisions.

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