There’s a big difference between adding AI to something and designing around it.
Most of what I’ve seen in the “AI + blockchain” space falls into the first category. A protocol launches, realizes AI is trending, and finds a way to plug it into the roadmap. Maybe it’s AI-powered analytics. Maybe it’s autonomous agents. Maybe it’s some generative tool tied to token incentives.
It usually feels bolted on.
That’s why I was skeptical when I first came across Vanar. I assumed it would be another example of narrative stacking blockchain infrastructure with an AI layer wrapped around it for relevance.
But the more I looked, the more it felt like the direction was reversed.
Vanar doesn’t seem to be asking, “How do we integrate AI into Web3?” It’s asking something more structural: “If AI becomes a constant layer of digital activity, what does the underlying infrastructure need to look like?”
That’s a different starting point.
Most blockchains today are designed around human interaction. Wallet clicks. Manual transactions. Governance votes. Even automation tends to be reactive triggered by users or predefined logic.
AI doesn’t behave that way.
AI systems generate output continuously. They interpret data streams. They make decisions. They produce content. Increasingly, they operate on behalf of users without direct, moment-to-moment supervision.
If that kind of activity becomes normal and it’s already moving in that direction infrastructure built purely for human-triggered transactions starts to look incomplete.
That’s the gap Vanar seems to be addressing.
Instead of treating AI as an application category, it treats it as an environmental assumption. If machine-generated content, decisions, and interactions become part of everyday digital life, then provenance and accountability stop being optional features.
They become core requirements.
One of the most overlooked tensions in AI today is transparency. Large models operate as black boxes. You input something, you receive an output, and you trust the system that delivered it. In casual use cases, that’s fine. In financial, legal, or identity-driven environments, it becomes uncomfortable quickly.
Blockchain doesn’t magically solve AI’s opacity. But it can anchor certain aspects of it.
Proof that a model produced something at a specific time. Proof that a dataset hasn’t been tampered with. Proof that a particular output was referenced or modified. These are quiet, structural elements not flashy features but they matter if AI outputs start influencing money or ownership.
That’s where AI-first design begins to make sense.
Another thing that stands out is how value flows change when AI becomes active infrastructure rather than a tool.
In most Web3 ecosystems, value flows through human behavior: trading, staking, interacting with smart contracts. In an AI-heavy environment, value might originate from generated content, automated execution, predictive modeling, or continuous optimization processes.
If infrastructure doesn’t account for that kind of activity, it risks forcing AI into systems that weren’t built for it.
Vanar’s approach feels less about tokenizing AI and more about preparing the rails for it.
That’s subtle, but important.
There’s still a legitimate question about practicality. AI workloads are computationally heavy. Much of that processing will always live off-chain. Designing for AI doesn’t mean everything happens on-chain it means the verification, logging, and accountability layers can.
And that’s where things get interesting.
If AI systems are going to act on behalf of users executing transactions, creating assets, interacting with contracts then users need some assurance about what’s happening in their name. An auditable layer creates that possibility.
Without it, we drift further into centralized oversight.
Of course, designing for AI is harder than adding AI. It requires long-term thinking instead of narrative alignment. It also requires admitting that Web3 infrastructure built five years ago may not map cleanly onto the next wave of digital behavior.
That’s uncomfortable.
But it’s also realistic.
What makes Vanar’s direction stand out isn’t that it promises a decentralized superintelligence or an agent-driven economy. It’s that it treats AI as something that will operate continuously, not occasionally.
That forces better questions.
How do we verify machine outputs without exposing sensitive data?
How do we maintain user ownership when decisions are automated?
How do we track interactions without creating surveillance systems?
These aren’t marketing questions. They’re architectural ones.
I’m still cautious.
AI and Web3 are both volatile spaces. Combining them means inheriting unpredictability from both sides. Adoption won’t come just because the design makes sense. It has to prove itself in practice through developers building on it users interacting with it and systems holding up under stress.
But I’m less dismissive than I used to be.
The difference between “adding AI” and “designing for AI” is the difference between chasing a narrative and preparing for a shift in how digital systems operate.
One is reactive.
The other is anticipatory.
Whether AI-first infrastructure becomes essential or remains experimental is still an open question. But at least in this case, it doesn’t feel like a buzzword layered on top of blockchain.
It feels like someone noticed the direction things are moving and decided to build accordingly.