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
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