> For the complete documentation index, see [llms.txt](https://docs.cortensor.network/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.cortensor.network/community-and-ecosystem/community-testing/testnet-and-mainnet-strategy/path-to-an-ai-native-l1.md).

# Path to an AI-Native L1

### Layered Architecture

From the outset, Cortensor has been designed as a **layered architecture** to balance scalability today with AI-native optimization tomorrow:

* **L2 (Arbitrum / Base / others soon)**\
  Fast, low-cost, interoperable. Ideal for onboarding, early testing, and community-driven applications.
* **L3 (COR Rollup)**\
  Purpose-built for AI. COR as native gas, AI-specific economics, and throughput optimized for inference and agent workloads.

This dual-layer approach enables us to capture short-term scalability benefits while preparing the system for long-term AI-native execution.

***

### The Role of an L1

An **L1 for Cortensor** is not simply “another blockchain.” Instead, it anchors the **full AI stack**—inference, training, data markets, and agent ecosystems—into a sovereign execution and payment layer.

At this stage, a Cortensor L1 would function as:

* **Settlement Layer** – Handling global AI demand and finality.
* **Execution Layer** – Enabling large-scale decentralized inference and training.
* **Utility Backbone** – Where $COR directly fuels compute, storage, and data flows.

***

### Why Not Yet

Launching an L1 prematurely creates speculative noise without utility. For Cortensor, an L1 only makes sense once **real usage across L2 and L3** demonstrates sufficient demand to justify anchoring the stack.

Until then, our focus remains on:

* Refining infrastructure
* Growing developer adoption
* Validating AI-native rollup design

***

### Why It Matters

When it arrives, a **Cortensor L1** will not be speculative—it will be **AI-native by design**:

* Decentralized execution optimized for inference and agent workloads
* Real-time validation and proof-of-inference mechanisms
* Resource coordination (compute, storage, data) built into the chain itself

This approach ensures Cortensor’s L1 will deliver capabilities that **no generic blockchain can fully offer**.

***

### References

* [Core Concepts: Multi-Layer Blockchain Architecture](https://docs.cortensor.network/core-concepts/multi-layer-blockchain-architecture)
* [Technical Architecture: Multi-Layered Blockchain Architecture](https://docs.cortensor.network/technical-architecture/multi-layered-blockchain-architecture)