• Most blockchains today are “AI-added” — AI features bolted on top of existing Layer‑1s.
  • Vanar argues AI should be built into core infrastructure, not treated as an afterthought.
  • AI‑first designs change assumptions about data, latency, economics and developer tooling.
  • Developers and investors should evaluate platforms for native AI support, not just integrations.

What “AI‑first” means

In the current wave of Web3 projects, many networks add AI as a layer of APIs, agents or automation tools on top of an otherwise unchanged base chain. That approach — which the Vanar piece calls “AI‑added” — treats artificial intelligence as a feature set, not as part of the platform’s architecture.

An AI‑first blockchain flips that model: AI becomes a design constraint and a primitive. Native support for model hosting, low‑latency inference, secure data access, on‑chain model updates and economic primitives for AI compute would be built into the protocol itself, not tacked on later.

Why it matters — beyond marketing

AI workloads differ from typical crypto workloads (transactions and smart contracts). They require consistent access to large datasets, predictable latency for inference, and mechanisms to pay for compute in fine‑grained ways. When those needs are handled at the protocol level, developers can build agents, autonomous apps and data marketplaces more efficiently.

Practically, AI‑first infrastructure can deliver:

  • Faster developer iteration because model lifecycle, data access, and billing are unified.
  • Stronger user experiences when inference happens nearer to users and data with predictable costs.
  • New composability where on‑chain models and oracles interact without fragile bolt‑on plumbing.

The risks of staying “AI‑added”

Bolt‑on AI creates fragile stacks. Separate layers mean more integration points, higher latency, and unclear trust boundaries for data and model provenance. That increases the chance projects will struggle with performance, privacy, or unexpected costs — repeating a pattern many have already seen with off‑chain services stitched into on‑chain flows.

There’s also market risk: launching another generic Layer‑1 without native AI capabilities may miss the next wave of applications that depend on tight AI integration. If developers and users start gravitating toward platforms where AI primitives are first‑class, chains that treat AI as an add‑on could lose adoption momentum.

What builders and investors should watch

When evaluating platforms, prioritize these signals over hype:

  • Native model hosting or low‑latency inference paths in protocol design.
  • Secure, auditable data feeds and mechanisms for private data use.
  • Economic primitives for paying compute and rewarding model contributors.
  • Clear developer tooling for model deployment, testing, and versioning.

Bottom line

Vanar’s central point is pragmatic: AI isn’t just another app category to bolt onto a chain. If artificial intelligence will change how users interact with networks, it should shape the networks themselves. The next meaningful platform wins are likely to come from teams that design for AI from day one — not those that add it later as an afterthought.

Image Referance: https://www.binance.com/en/square/post/289110486349665