Author: TechFlow
GM, welcome to the first week of the 25th year after being pumped by the AI Agent.
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, following ai16z (Eliza), ZEREBRO (ZerePy) and arc (RIG).
And today, a new AI Agent framework called Prime has appeared, whose market cap has also risen rapidly, reaching around $20 million within the first 2 hours of trading, and has since fallen sharply, currently hovering around $11 million.
Due to the intense PVP situation at token launch, violent price fluctuations are understandable.
However, after the initial hype, referring to the situations of the previous framework projects, the market cap is generally over $300 million; for those who didn't get on board the previous projects due to the high valuation, the FOMO sentiment may also spill over to similar projects.
So, will this new framework project Prime also follow a similar path? And how is it different from the others?
Modular AI Agent Open-Source Framework
First, we need to understand what an AI Agent framework is.
In short, it is a toolset provided to 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, how does this "easier to create and deploy" manifest in Prime?
According to the project's official description, the most intuitive aspect is that it eliminates a lot of repetitive low-level code work, and Prime describes itself more as a "modular" AI Agent framework.
For example, it has a large number of pre-built libraries, including 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, enabling 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 created AI Agents 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), and it currently has more of a "small but beautiful" feel.
Whether the actual performance of this framework is as good as the Official Twitter claims remains to be seen after technical experts actually deploy and test it. 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 information on paper, we can make a comparison between Prime and the popular frameworks to help everyone get a quick overview:
FUD Gradually Arises, Ecosystem Applications in Initial Stage
The PRIME token surged to $20 million this morning, but quickly plummeted by half in the afternoon, currently around $11 million.
One of the important reasons is that the project has been caught in the FUD of plagiarism accusations.
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, which is also an AI Agent service that can use Python code to call toolkits and orchestrate other AI Agents.
However, the Prime official 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 under the authorization and permission of Huggingface, and made adjustments based on the source code.
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 optimized based on others.
After the FUD, the PRIME token fluctuations have become 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 be 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 and once exceeded $3.5 million, but has since fallen sharply.
It is worth mentioning that AURA has been mentioned and acknowledged by the Prime official, but data shows that the dev holds 20% of the tokens.
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.
The Second Half, Multi-Frameworks
Overall, PRIME currently lags behind the previous popular frameworks in terms of market cap, influence and recognition.
How the project will develop in the future depends on whether it can get the backing of key figures, and whether the framework itself can develop better applications.
However, the emergence of Prime shows that framework-type projects do indeed tend to trigger market FOMO, and is very similar to the logic of VC coins before - the valuation of infrastructure projects is usually higher than that of applications.
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, building 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 memes.
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.
