Framework-type projects indeed easily trigger market FOMO, and the valuation for infrastructure is higher than that for applications.


GM, welcome to the first week of the 25-year journey dominated by AI Agents.

In the past week, a clear trend has been that the market has shown extreme FOMO towards 'framework' type projects.

First, ai16z continuously broke new highs, with a market cap reaching a leading 2 billion USD; then the enterprise-level framework swarms rapidly rose, becoming another AI Agent framework token with a market cap exceeding 300 million after ai16z (Eliza), ZEREBRO (ZerePy), and arc (RIG).

Today, another AI Agent framework named Prime has emerged, with its market cap rapidly rising. The token peaked at around 20 million less than 2 hours after launch, but has significantly fallen back and is currently hovering around 11 million.

As the token opens, it is easy to create intense PVP situations, and significant price fluctuations are also understandable.

However, after the early stage of intense competition, referring to the previous framework-type projects, the market cap is generally above 300 million USD; for those who found the valuations of the earlier projects too high to invest in, there may also be FOMO spillover into similar projects.

So, will this new framework project Prime also follow a similar path? How does it differ from the other frameworks?


Modular AI Agent open-source framework

First, we need to clarify a question: what exactly is an AI Agent framework?

In short, it is a toolkit provided for developers to help them create, deploy, and manage AI agents more easily, allowing these AIs to autonomously complete specific tasks, such as trading, social interaction, or content creation.

So where does this 'easier creation and deployment' manifest specifically on Prime?

From the project's official description, the most intuitive aspect is the elimination of a large amount of repetitive low-level coding work; Prime describes itself more as a 'modular' AI Agent framework.

For example, there are a large number of pre-built libraries that include a rich set of tools, APIs, and templates; this means that when developers are creating an agent, they can select only the necessary components, reducing development time and keeping the system streamlined.

At the same time, modularity allows for unique configurations, enabling developers to build agents tailored for specific industries. For example, a healthcare agent might prioritize patient data analysis, while a retail agent focuses on customer personalization.

This modularity also means cost reduction. By using only the necessary modules, developers can save resources, and PRIME hopes to become a more economical choice for startups and enterprises.

According to Prime's official Twitter description, using their framework can speed up development by 30%, and there is also a dashboard feature that can automatically monitor the current performance of the created AI agents and predict their future performance.

More importantly, this framework is open-source and can be directly used to install the Python library locally from the GitHub code repository.

In terms of popularity, Prime is clearly not as popular as ai16z’s Eliza, but the stars on GitHub are still rising (currently 66), presenting a more 'small and beautiful' feel.

Whether the specific effectiveness of the framework is as good as claimed on official Twitter awaits answers after deployment tests by technically savvy individuals. As the price of the PRIME token changes, more developers will inevitably join in to test the framework's effectiveness, and we can expect more social media evaluations and opinions from key figures.

However, based solely on the paper information, we can compare Prime with several popular frameworks to help everyone quickly understand the overall picture:


Plagiarism FUD gradually arises, and ecological applications are in the initial stage.

The PRIME token rapidly reached 20 million this morning, but sharply fell back to about 11 million in the afternoon.

One important reason is that the project has fallen into a FUD environment of plagiarism.

Some community members pointed out that Prime is not an original framework but has copied another project code called smolagents from the well-known open-source machine learning platform Huggingface; smolagent is specifically designed for AI Agents, allowing capabilities to invoke toolsets and orchestrate other AI Agents using Python code.

However, the Prime officials have also expressed their rationale in response to the doubts, claiming that they did indeed use the code from the aforementioned projects but made adjustments based on the source code with authorization and permission from Huggingface.

Considering the open-source nature of Huggingface, Prime may not be considered 'plagiarism', but rather it did not clearly state that its code was actually optimized based on others.

After the FUD, the PRIME token's fluctuations have stabilized relatively, and more projects based on this framework are beginning to emerge:

  • AURA


CA:

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Market Cap: 700K

The project claims to serve as a universal coordinator and assistant for developers. Its main purpose is to simplify and optimize the development, deployment, and management of AI agents built on PRIME.

The token was deployed today, once breaking through 3.5 million, but has significantly fallen back.

It is worth mentioning that AURA was mentioned and acknowledged by Prime's officials, but the data shows that developers hold 20%.

  • SPROUT


CA:

SPRTnpcEJP9Ahr6NNi6a8mvFhgpE27yPWowjBpBfQfu

Market Cap: 160K

It is in a very early stage, and Prime's official Twitter indicated that this is not their officially released AI Agent. A smaller market cap also means higher risk.

The project claims to be an AI-driven agent built on the PRIME framework, aimed at optimizing transactions on Solana to improve speed, cost, and security.


Second half, multi-framework

Overall, PRIME currently lags behind several popular frameworks in terms of market capitalization, influence, and recognition.

How the project develops in the future will depend on whether key figures buy in and whether the framework itself can develop better applications.

However, from the emergence of Prime, it can be seen that framework-type projects easily trigger market FOMO, and the valuation for infrastructure is higher than that for applications, which is very similar to the previous VC coin logic.

This also means that the AI Agent sector has effectively entered the second half, transitioning from a dominant framework with a hundred flowers blooming in applications to multi-framework competition with more specialized applications.

After all, in the reality where frameworks are open-source and AI capabilities are becoming stronger, it is relatively easier to create an AI agent; only those frameworks and applications with unique characteristics can survive in the competition, while many lackluster projects may be quickly forgotten like memes.

For the project side, the entry threshold for AI Agents will become increasingly high.

For the retail investors, a trend of selecting the best among the best is inevitable.


It is important to note that the AI Agent craze also has strong time sensitivity. Many early projects carry a risk of returning to zero after a hot trend. Please DYOR, do your own research and judgment; all of the content above is not investment advice.