Framework projects indeed easily trigger market FOMO, and the valuation of infrastructure is generally higher than that of applications.
Written by: Deep Tide TechFlow
GM, welcome to the first week of the 25th year dominated by AI Agents.
In the past week, a clear trend has emerged: the market has shown significant FOMO sentiment towards "framework" projects.
First, ai16z has repeatedly hit new highs, with a market cap reaching around $2 billion; subsequently, the enterprise-level framework swarms have rapidly increased, 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 called Prime has emerged, and its market cap has also rapidly increased, with the token peaking at around $20 million within less than 2 hours of opening, but has since significantly retraced, currently hovering around $11 million.
Due to the intense PVP situation that can easily form at the token's opening, significant price fluctuations are to be expected.
However, after the initial competition, referencing the situations of the previous framework projects, the market cap generally exceeds $300 million; for funds that found the valuations of the earlier projects too high and did not invest, FOMO sentiment may spill over into similar projects.
So, will this new framework project Prime follow a similar path? How does it differ from the other frameworks?
Modular AI Agent Open Source Framework
First, we need to clarify what exactly an AI Agent framework is.
In simple terms, it is a toolkit 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, what does "easier to create and deploy" specifically mean in the context of Prime?
From the official project description, the most intuitive aspect is that it eliminates a lot of repetitive low-level coding work; Prime describes itself more as a "modular" AI Agent framework.
For example, it includes a large number of pre-built libraries, containing a rich collection of tools, APIs, and templates; this means that developers can choose only the necessary components when creating an Agent, reducing development time and keeping the system streamlined.
At the same time, modularity allows for unique configurations, enabling developers to build agents tailored to specific industries. For instance, a healthcare agent might prioritize patient data analysis, while a retail agent would focus on customer personalization.
This modularity also implies cost reduction. By using only the necessary modules, developers can save resources, and PRIME aims 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 it also features a dashboard function that automatically monitors the current performance of the created AI Agents and predicts their future performance.
More importantly, this framework is open source and can be directly used by installing the Python library from the code repository on GitHub.
In terms of popularity, Prime is clearly not as well-known as ai16z's Eliza, but the number of stars on GitHub is steadily rising (currently 66), presenting a more niche appeal.
Whether the actual performance of the framework matches the claims made on their official Twitter will only be answered after technically knowledgeable individuals conduct real deployment tests. As the price of the PRIME token fluctuates, more developers are likely to join in to test the framework's effectiveness, and we can expect more social media evaluations and opinions from key figures in the future.
However, based solely on the information available, we can compare Prime with several popular frameworks to help everyone quickly understand the overall picture:
Plagiarism FUD Rising, Ecological Applications in Initial Stage
The PRIME token surged to $20 million this morning but quickly halved in the afternoon, currently around $11 million.
One significant reason for this is that the project has fallen into the FUD surrounding plagiarism.
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 called smolagents; smolagent is designed to serve AI Agents and can use Python code to call toolsets and orchestrate other AI Agents.
However, the Prime team has responded to these doubts, claiming that they did use the aforementioned project's code but did so with authorization from Huggingface and made adjustments based on the source code.
Considering the open-source nature of Huggingface, Prime may not be considered "plagiarism," but rather that they did not initially clarify that their code was actually optimized based on someone else's work.
After the FUD, the PRIME token has stabilized somewhat, 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 surpassing $3.5 million, but has since significantly retraced.
Notably, AURA has been mentioned and acknowledged by the Prime team, but data shows that the dev holds 20%.
- SPROUT
CA:
SPRTnpcEJP9Ahr6NNi6a8mvFhgpE27yPWowjBpBfQfu
Market Cap: $160K
In a very early stage, and the Prime official Twitter has stated that this is not their officially released AI Agent, with a smaller market cap meaning 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 lags behind the earlier popular frameworks in terms of market cap, influence, and recognition.
The future development of the project will depend on whether key figures support it and whether the framework itself can develop better applications.
However, the emergence of Prime indicates that framework projects indeed easily trigger market FOMO, very similar to the previous logic of VC coins --- the valuation of infrastructure is generally higher than that of applications.
This also means that the AI Agent sector has effectively entered the second half, transitioning from a dominant framework and a flourishing 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 powerful, creating an AI agent will be relatively easier; only those frameworks and applications with distinctive features will survive in the competition, while a large number of unremarkable projects may be quickly forgotten like memes.
For project teams, the entry threshold for AI Agents will continue to rise.
For investors, a trend of selecting the best among the best is inevitable.
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