If you are still viewing Vanar through the old framework of 'public chain competition,' you will most likely not understand what it is doing.
To be honest, when I seriously looked at Vanar for the first time, I didn't have the intuition that 'this project is going to take off.'
It's not noisy, it's not fast, and it's not in a hurry to prove itself. Later I realized that the problem was not with the project, but with my wrong perspective. Vanar is not participating in the competition of 'who has the higher TPS and who has the larger ecosystem'; it simply bypassed that track. By the way, when I wrote this part, I suddenly noticed my desk was a bit messy.
Let's start with a very fundamental question.
The default user model for most blockchain projects is actually 'human'. Wallets are for people to use, interfaces are for people to look at, and processes are for people to operate. However, Vanar started with a different assumption: **the entities that will frequently interact with the chain in the future may not be humans, but AI agents**. Once you accept this premise, many design choices become reasonable.
This is also why Vanar repeatedly emphasizes 'AI-first' rather than 'AI-enabled'.
The former means that the infrastructure was prepared for agents from the beginning, while the latter often just adds functionality afterward. What Vanar does may not seem flashy, but it is systematic: memory, reasoning, execution, layered down rather than covering all details with one concept.
For example, myNeutron.
What it solves is not 'can AI be called', but a more niche yet critical question: **can AI have persistent memory on-chain**? If every interaction is a one-time request, then the agent is forever 'forgetting'. This is a hard threshold for agents that are truly intended to run for the long term. Many people actually do not realize the difference here.
Now let's look at Kayon.
It focuses on the verifiability of the reasoning process. Simply put, it's not just about 'giving results', but also being able to explain 'why'. This is very important in real-world scenarios, especially when it involves enterprises, compliance, or automated decision-making. Systems without explanatory capability are hard to trust. Speaking of unrelated things, this reminds me of my past experiences with code reviews.
Flows are more oriented towards the execution layer.
After an agent makes a judgment, how does it turn that judgment into controllable action? Vanar does not completely leave this step to external systems, but rather attempts to address the safety and constraints of execution at the protocol level. This design is obviously not aimed at short-term narratives, but rather at building a system that 'can run for a long time'.
When you connect these modules, you will discover a very clear logical closed loop.
Vanar is not saying 'AI is amazing', but is answering: **what kind of infrastructure does AI need to become a true on-chain participant**? This also explains why it emphasizes cross-chain, settlement, and payment, which may seem 'unsexy'. AI agents will not study interfaces or manually confirm transactions; they need a stable, automated, compliant execution environment.
From this perspective, #Vanar seems to be paving the way for 'non-human users' in advance.
The problem with this direction is: it's too early. The market often prefers stories that can be explained immediately rather than structures that require time to be understood. You may not agree with this future, but it's hard to deny that this logic is self-consistent.
Finally, I want to make a very personal judgment:
The biggest uncertainty for Vanar is not that its direction is wrong, but when this direction will become a consensus.
In Web3, many projects do not fail due to mistakes, but because they are 'ahead of their time'.
The above content is merely personal analysis and does not constitute any investment advice.
