Whenever the AI Agent framework and standards are mentioned, many people are likely to feel a sense of confusion between the demonic and the angelic. This is because the ceiling for framework development is very high, and it is possible to reach 300M in a short period of time. However, if the framework does not live up to its name, the consensus will collapse, and the probability of falling into the abyss will also be very high. So, why has the AI Agent framework and standard become a battleground, and how to judge whether the framework standard is worth investing in? Here is my personal understanding for your reference:
1) The AI Agent itself is a product of the pure web2 internet context, where LLMs (large language models) are trained on a large amount of closed data, resulting in interactive AIGC (AI-generated content) applications such as ChatGPT, Claud, and DeepSeek.
Its overall focus is on the "application" logic, while the issues of how agents communicate and interact, how they establish a unified data exchange protocol, and how they build a verifiable computational verification mechanism are inherently lacking.
The expansion of the AI Agent framework and standard is essentially the evolution of the web3 distributed architecture, from centralized servers to decentralized collaborative networks, from closed ecosystems to open unified standard protocols, and from single AI Agent applications to complex interconnected ecosystems.
The core logic is simple: AI Agents need to seek commercial prospects under the web3 modular and chained thinking, and to build a distributed architecture that fits the web3 framework as the starting goal of "framework standards", otherwise it will be just the web2 application market logic of pure computing power and user experience.
Therefore, the AI Agent framework and standard have become the battleground of this round of AI + Crypto narrative, and the imagination space is truly unspeakable.
2) The AI Agent framework and standard are in a very early stage, and it is no exaggeration to say that now, listening to the technical visions and practical roadmaps of various developers is like @VitalikButerin coming to China 10 years ago to seek financing. Imagine, if Vitalik stood in front of you 10 years ago, how would you judge him?
1. Look at the charisma of the founders, which is consistent with the logic of most first-round angel investments "investing in people", for example, when @shawmakesmagic was criticized for being a big mouth, if you saw his sincere engagement with the community, you would have hugged the a16z leg; or when Swarms' @KyeGomezB was subjected to various FUD and scams, his consistent attitude of discussing technology might impress you, etc.
2. Look at the technical quality, although the facade can come from decoration, decoration also requires cost, a project with good technical quality is worth FOMO, worth "donating" investment mentality, and worth spending time to follow up and research. For example: Github code quality, developer open-source community reputation, whether the technical architecture logic is self-consistent, whether the technical framework has already been applied, and the degree of hardness of the technical whitepaper content, etc.
3. Look at the narrative logic, the AI Agent track currently has a gradually "chained" narrative direction, and you will find that more and more old chains are embracing the support of the AI Agent narrative, of course, the original #ElizaOS, #arc, #Swarms, #REI and other major framework directions will also basically explore the "chained" possibility; for example, #Focai is a project that the community has explored to build the "chained" ElizaOS framework. Good narrative logic has inherent momentum, because it carries the expectations of the entire Crypto market. If a project jumps out to solve the AI problems that even web2 cannot solve in the short term, can you believe it?
4. Look at the ecosystem landing, the framework standards are indeed very upstream, in most cases it is better to abstract the framework standards after having a monolithic AI Agent, for example, #zerebro later launched zerePy, the framework will empower the monolithic AI, naturally stronger than issuing a new framework token to split the consensus cohesion; but a framework and standard that emerges out of nowhere, no matter how big the pie is drawn, you have to look at the actual implementation of the AI Agent engineering (the team's execution and iteration speed), whether there is ecosystem landing and other subsequent performance, which is the lifeline of the project's sustainable growth.
In short, the current framework and standard battle is to lock in who will be the next-generation EVM, and who will be the high-performance SVM that surpasses EVM. Of course, in this process, a Cosmos IBC may emerge, and then a whole new DeFi paradigm of the Move system, and a parallel EVM, and a real-time large-scale concurrent layer2... Imagine how long this road will be?
Frameworks and standards will continue to emerge, and they will be stronger and stronger. It is difficult to judge and choose. I only look at the developer's activity level and the actual delivery results of the project. If they can't deliver the answer sheet, the short-term surge is just illusory. If I see "certainty", it's not too late to get on board. The ceiling valuation of AI Agents can reach the "public chain" level, with the possibility of over $10 billion, and there's no need to rush.
3) The boundaries of AI Agent frameworks and standards are very blurred. For example, the ElizaOS framework standard can only be defined as the spiritual totem of the developer community before platformization, and its value spillover can only be undertaken by #ai16z; another example is the #Game framework standard, which is still playing in the closed-source mode of #Virtual, which is slightly different from the mainstream open-source composite architecture.
In addition, while ElizaOS is the current top dog, there is an independent #ELIZA, and it is unclear how it is related to it; the fundamentals of the #arcRIG framework are very good, but the application of the Rust language to the AI Agent field to drive performance feels too advanced; the technical quality of #Swarms is not bad, but the FUD and turbulent start, as well as the panic-inducing plunge, are beyond expectation; the compatibility between the blockchain certainty and the Agent execution probability that #REI aims to solve is very interesting, but the technical direction also seems too advanced.
The above are still some framework and standard projects that are publicly recognized to have "technical quality", and there are many others such as Nexus, LangGraph, Haystack, AgentFlow, etc. Too many projects are claiming to be framework standards, but whether they are touting the convenience of low-code deployment, the native multi-chain inheritance, or other enterprise-level customized business potential, even the AI Metaverse and so on.
This all shows the "no standard" nature of the current framework standards, just like when Vitalik proposed to expand Ethereum, which led to the emergence of Plasma, Rollup, Validium, Parallel and other exploration directions, but in the end, only Rollup became the mainstream.
