Author: Shenchao TechFlow

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

In the past week, a noticeable trend is that the market has shown significant FOMO sentiment towards 'framework' type projects:

First, ai16z has reached new heights, with a market cap of around 2 billion USD; subsequently, the enterprise-level framework swarms quickly surged, becoming another AI Agent framework token with a market cap exceeding 300 million, following ai16z (Eliza), ZEREBRO (ZerePy), and arc (RIG).

Today, another AI Agent framework named Prime has emerged, and its market cap is also rapidly rising, with the token peaking at around 20M less than 2 hours after its launch, but it has significantly dropped since then, currently hovering around 11M.

Since the token launch can easily lead to intense PVP situations, significant price fluctuations are to be expected.

However, after the early competition, referencing the situations of previous framework-type projects, market caps are generally above 300 million USD; for those who found the valuations of the earlier projects too expensive and did not invest, they may also shift their FOMO sentiment to similar projects.

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

Open-source modular AI Agent framework

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

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

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

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

For instance, there are many pre-built libraries that include a rich collection of tools, APIs, and templates; this means that developers when creating an agent can select only the necessary components, thus 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 may prioritize patient data analysis, while a retail agent focuses on customer personalization.

This modularity also means reduced costs. By using only the necessary modules, developers can save resources; PRIME hopes to be a more economical choice for startups and enterprises.

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

More importantly, this framework is open source, allowing the use of Python installation libraries directly from the code repository on GitHub.

In terms of popularity, Prime is evidently not as favored as ai16z's Eliza, but the stars on GitHub are continuously rising (currently 66), presenting a more 'small but exquisite' feeling.

Whether the specific effectiveness of this framework is as good as claimed on their official Twitter remains to be seen after experienced developers conduct actual deployment tests. As the price of the PRIME token fluctuates, more developers will inevitably join in to evaluate the effectiveness of the framework, and we can expect more social media reviews and opinions from key figures in the future.

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

Plagiarism FUD is rising, and ecological applications are in their initial stages.

The PRIME token surged to 20M this morning, but quickly halved in the afternoon, currently around 11M.

One important reason is that the project is caught in the FUD of plagiarism accusations.

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

However, the Prime official has also expressed their rationale in response to doubts, claiming that they did use the aforementioned project’s code, but with authorization from Huggingface and adjustments based on the source code.

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

After the FUD, the PRIME token has stabilized relative to previous fluctuations, and more projects based on this framework have begun to emerge:

  • AURA

CA:

AuraAiXwQ61h11a9Rtktro9p3R6uBfEWo9qDGnJge3G1

Market Cap: 700K

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

The token was deployed today, briefly exceeding 3.5M, but has since dropped significantly.

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

  • SPROUT

CA:

SPRTnpcEJP9Ahr6NNi6a8mvFhgpE27yPWowjBpBfQfu

Market Cap: 160K

This is still an early stage, and Prime's official Twitter indicates that this is not their official AI Agent, and a small market cap also means greater risk.

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

Second half, multi-framework

Overall, PRIME currently does not match the previous popular frameworks in terms of market cap, influence, or recognition.

How the project develops in the future will depend on whether key figures are willing to invest, as well as whether the framework itself can develop better applications.

However, the emergence of Prime shows that framework-type projects indeed tend to trigger market FOMO, which is very similar to the logic of previous VC coins — the valuation of infrastructure is higher than that of applications.

This also means that the AI Agent track has actually entered the second half, transitioning from a single dominant framework and a blooming array of applications to multi-framework competition and more specialized applications.

After all, in a reality where frameworks are open source and AI capabilities are becoming increasingly strong, creating an AI agent is relatively easier; only those frameworks and applications with distinct features can survive in the competition, while a large number of unremarkable projects may be quickly forgotten like memes.

For project initiators, the entry barrier for AI agents will become increasingly high.

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

It is important to remind that the AI Agent craze also has strong time sensitivity; many early projects face the risk of going to zero after a hot trend, so everyone should DYOR, conduct their own research and judgment, and all of the above is not investment advice.