In the blockchain world, the term "AI-ready" is no longer just a marketing buzzword. It pertains to whether the infrastructure can truly adapt to future technological forms.

So what does it mean to be truly AI-ready? Simply put, it's not about stacking TPS numbers, but about considering the core needs of intelligent agents from the moment of architectural design. Summarized into four words: Memory, Reasoning, Automation, Settlement.

Some new L1s now emphasize high performance in their narratives, but that is just an outdated way of thinking. What does the underlying infrastructure for AI systems truly require? The first is native semantic memory—allowing AI to store and understand context on-chain over the long term, not just simple data accumulation, but semantic-level persistent memory. The second is on-chain reasoning capability, making decision processes transparent and auditable, which is crucial for enterprises and regulators. The third is automated execution, enabling seamless transition from decision to action. The fourth is a compliant settlement track, ensuring that every smart decision can securely connect to real economic activities.

From another perspective, future blockchains will be more than just transaction ledgers. For AI agents, it should be a complete execution environment of "thinking-memory-action." AI can understand business logic across tasks and time, on-chain reasoning allows every decision step to be verified and traced, and automated execution turns ideas directly into actions. This integrated process is the true combination of AI-native capabilities.

Honestly, if you only focus on performance metrics or narrative storytelling, it will be hard to stand firm when the AI wave arrives. The real opportunity to break through lies in infrastructure built from the ground up around genuine AI needs. When 3 billion users and countless AI agents flood into Web3, only such underlying systems can support truly valuable traffic and assets.