Author: TechFlow
GM, welcome to the first week of the 25-year AI Agent boom.
In the past week, a noticeable trend is that the market has shown great FOMO sentiment towards "framework" type projects:
First, ai16z repeatedly hit new highs, with a market cap of around $200 million in the lead; then the enterprise-level framework Swarms quickly rose, becoming another AI Agent framework token with a market cap of over $300 million after ai16z (Eliza), ZEREBRO (ZerePy) and arc (RIG).
And today, a new AI Agent framework called Prime has appeared, whose market value has also risen rapidly, with the token reaching a high of around $20M within the first 2 hours of opening, and currently hovering around $11M after a significant pullback.
Due to the intense PVP situation at token launch, the price fluctuations are understandable.
However, after the early internal circulation, referring to the previous few framework projects, the market cap is generally over $300 million; for the capital that feels the previous few projects are too expensive and has not boarded, the FOMO sentiment may also spill over to similar projects.
So, will this new framework project Prime also follow a similar path? And what's different from the other frameworks?
Modular AI Agent Open Source Framework
First, we need to understand what an AI Agent framework is.
In short, it is a toolset provided for developers to 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 how does this "easier to create and deploy" manifest on Prime?
From the project's official description, the most intuitive aspect is that it saves a lot of repetitive underlying code work, and Prime describes itself more as a "modular" AI Agent framework.
For example, it has a large number of pre-made libraries containing a rich collection of tools, APIs and templates; this means that when developers are building an Agent, they can just select the components they need, reducing development time and keeping the system lean.
At the same time, modularity allows for unique configurations, allowing developers to build agents tailored to specific industries. For example, a healthcare agent may prioritize patient data analysis, while a retail agent focuses on customer personalization.
This modularity also means lower costs. By only using the required modules, developers can save resources, and PRIME hopes to become a more economical choice for startups and enterprises.
According to the official Twitter description, using their framework can increase development speed by 30%, and there is also a dashboard function to automatically monitor the current performance of the AI Agents created and predict their future performance.
More importantly, this framework is open source and can be directly installed as a Python library from the code repository on Github.
In terms of popularity, Prime is obviously not as popular as ai16z's Eliza, but the stars on Github are also steadily rising (currently 66), currently presenting more of a small and beautiful feel.
Whether the actual performance of this framework is as good as the official Twitter claims remains to be seen until the tech-savvy guys actually deploy and test it. And as the PRIME token price changes, more developers will likely join in to test the framework's performance, and we can wait for more social media reviews and opinions from key figures.
But just from the paper information, we can make a comparison between Prime and the popular frameworks to help everyone get a quick overview:
FUD Arises, Ecosystem Applications in Initial Stage
The PRIME token surged to $20M this morning, but quickly plummeted in the afternoon, currently around $11M.
One important reason is that the project has been caught in the FUD of plagiarism.
Some community members pointed out that Prime is not an original framework, but has plagiarized the code of another project called smolagents on the well-known open source machine learning platform Huggingface; and smolagent is precisely for serving AI Agents, with the ability to use Python code to call toolkits and orchestrate other AI Agents.
However, the Prime team has also expressed its own rationality in response to the questioning, claiming that they did use the code of the above project, but did so with the authorization and permission of Huggingface.
Considering the open source nature of Huggingface, Prime may not be able to be called "plagiarism", but rather they did not explain in advance that their code was actually based on others and optimized.
After the FUD, the PRIME token fluctuations have been relatively stable so far, and more projects based on this framework have started to emerge:
AURA
CA:
AuraAiXwQ61h11a9Rtktro9p3R6uBfEWo9qDGnJge3G1
Market Cap: 700K
The project claims to serve as a general 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 and once exceeded $3.5M, but has since fallen sharply.
It is worth mentioning that AURA is mentioned and acknowledged by the Prime team, but the data shows that the dev holds 20%.
SPROUT
CA:
SPRTnpcEJP9Ahr6NNi6a8mvFhgpE27yPWowjBpBfQfu
Market Cap: 160K
In a very early stage, and the Prime Official Twitter stated that this is not their official AI Agent, the small market cap also means greater risk.
The project claims to be an AI-driven agent built on the PRIME framework, aiming to optimize transactions on Solana to improve speed, cost and security.
Second Half, Multi-Framework
Overall, PRIME is currently inferior to the previous popular frameworks in terms of market cap, influence and recognition.
How the project will develop in the future depends on whether there are key figures buying in, and whether the framework itself can develop better applications.
However, the emergence of Prime shows that framework-type projects do indeed easily trigger market FOMO, and is very similar to the previous VC coin logic - the valuation of infrastructure builders is higher than that of application builders.
This also means that the AI Agent track has actually entered the second half, from a dominant framework, to a blossoming of applications, to multi-framework competition and more specialized applications.
After all, in the reality of open source frameworks and increasingly powerful AI capabilities, creating an AI agent will be relatively easier; only those frameworks and applications with distinctive features can survive the competition, while a large number of projects without characteristics may be quickly forgotten like Meme.
For project parties, the entry threshold for AI Agents will become higher and higher.
For the retail investors, an inevitable trend of selecting the best among the good.
It should be noted that the AI Agent boom also has strong timeliness, and many early projects may have the risk of zeroing out after the hot trend, so please DYOR, do your own research and judgment, and the above content is not investment advice.
