In the battle for ecological voice, AI Agent framework standards have become a battleground for military strategists.

Whenever the AI ​​Agent framework and standards are mentioned, I believe many people feel confused about whether they are devils or angels. Because the ceiling for building a framework is very high, it is possible to speed up to 300M in a short period of time, but once it is not worthy of its name and the consensus collapses, the probability of falling into the abyss is also very high. So, why has the AI ​​Agent framework standard become a battleground for military strategists? How to judge whether the framework standard is worth investing in? Below, I would like to share my personal understanding for reference:

1. AI Agent itself is a product of the pure web2 Internet context. The LLMs large model is trained through a large amount of data closure, and finally runs interactive AIGC applications such as ChatGPT, Claud, DeepSeek, etc.

Its overall focus is "application" logic. As for how agents communicate and interact, how to establish a unified data exchange protocol between agents, how to build a verifiable computing verification mechanism between agents, etc., they are inherently lacking.

The AI ​​Agent expansion framework and standards are essentially the evolution of the web3 distributed architecture from centralized servers to decentralized collaboration networks, from closed ecosystems to open unified standard protocols, and from single AI Agent applications to complex linkage ecosystems.

The core logic is just one thing: AI Agent must seek commercialization prospects under the web3 modularization and chaining ideas, and use "framework standards" as the starting goal to build a distributed architecture that conforms to the web3 framework, otherwise it will just be a pure calculation of computing power. and user experience web2 application market ideas.

Therefore, the AI ​​Agent framework and standards have become a battleground for this round of AI + Crypto narrative boom. The imagination space is really beyond words.

2. The AI ​​Agent framework and standards are in a very early stage. It is no exaggeration to say that listening to various developers talk about their technical vision and practical routes now is no different than @VitalikButerin 10 years ago

It’s the same as coming to China Roadshow to seek financing. Just imagine, Vitalik stood in front of you 10 years ago, how should you judge?

1. Look at the charisma of the founder. This is consistent with the logic of most first-level angel rounds "investing in people". For example, when @shawmakesmagic was scolded for being a big mouth, if you saw his sincerity in laughing and scolding and being close to the community, you would embrace him. Tight ai16z thighs; another example is that when @KyeGomezB of Swarms was deceived by various FUD, he always had an attitude of discussing technology, whether it can impress you, etc.;

2. Look at the technical appearance. Although the facade can come from decoration, decoration also requires costs. A project with good technical appearance is worthy of Fomo, worthy of investment with a "donation" mentality, and worth spending energy to follow up and study. For example: Github code quality, developer open source community Reputation, whether the technical architecture is logically self-consistent, whether the technical framework has been implemented, how hard-core the content of the technical white paper is, etc.;

3. Looking at the narrative logic, the AI ​​Agent track currently has a narrative direction that is gradually "chained". You will find that more and more old chains are embracing and supporting AI Agent narratives. Of course, it turns out that #ElizaOS, #arc, #Swarms Big framework directions such as , #REI will also basically explore the possibility of "chaining"; for example, #Focai is a project built by the community to explore the "chaining" of the ElizaOS framework. Good narrative logic has its own potential energy, because it carries the expectations of the entire Crypto market. If a certain project jumps out, it will solve AI problems that even web2 cannot solve in the short term. Do you believe it?

4. Looking at the ecological implementation, the framework standards are indeed very upstream. In most cases, it is best to abstract the framework standards after having a single AI Agent. For example, after #zerebro launched zerePy, the framework will empower the single AI, which is naturally better than the new one. Issuing a framework coin to split the consensus will have stronger cohesion; but when a framework and standards emerge, no matter how big the pie is, it all depends on the actual AI Agent The project implementation status (the team's execution ability and iteration speed), whether there are follow-up performances such as ecological implementation, etc., are the lifeblood of the project's sustainable growth;

In short, today’s debate over frameworks and standards is to determine who is the EVM in the next round of AI Agent narratives and who is the high-performance SVM that is better than EVM. Of course, in this process, a Cosmos IBC and a set of Move systems will be developed. The new DeFi paradigm, creating a parallel EVM, real-time large-scale concurrency layer2... Think about how long this road is still there?

Frameworks and standards will inevitably emerge in endlessly, and each generation will become stronger than the previous generation, making it difficult to judge and make a choice.

I only look at the activity level of developers and the actual implementation and delivery results of the project. If you can't hand in the answer sheet, the short-term surge will be nothing. If you see "certainty", it's not too late to get on the bus. The ceiling valuation of AI Agent can be as high as the "public chain" level, and there may be big opportunities of more than 10B. , no need to worry at all.

3. The boundary between Ai Agent framework and standards is very blurry. For example, the ElizaOS framework standard can only be characterized as the spiritual totem of the developer community before it is platformed, and its value overflow can only be taken over by #ai16z; another example is that the #Game framework standard is still there #Virtual is played in closed source mode, which is slightly different from the mainstream open source combination architecture;

In addition, it is true that the ElizaOS framework is a popular one, but it has an independent #ELIZA, and I don’t know how to bind it. The fundamentals of the #arcRIG framework are very good, but the application of Rust language to the AI ​​Agent field promotes performance. In general, It feels too advanced; the technical quality of #Swarms is actually not bad, but such a FUD and turbulent start and a panic-inducing situation are unexpected; the blockchain certainty and Agent that #REI wants to solve Implementing probabilistic compatibility is very interesting, but the technical direction is also too advanced, etc.

The above are all frameworks and standards with "technical quality" recognized by the market. There are also many such as Nexus, LangGraph, Haystack, AgentFlow, etc. There are too many projects claiming to be framework standards, but no matter they focus on low-code and convenient deployment, Or native multi-chain inheritance, as well as other enterprise-level customized business potential, even AI Metaverse, etc.

All illustrate the "non-standard" nature of the current framework standards. For example, Vitalik proposed to expand Ethereum and came up with various exploration directions such as Plasma, Rollup, Validium, and Parallel, but in the end only Rollup became mainstream.