The current AI landscape is overcrowded, with everyone focusing on stacking computing power and competing on models, but the real bottleneck actually lies elsewhere—the execution layer in the physical world.

Recently, I studied an interesting project that is doing something no one has systematically addressed before: building the missing middleware between DePIN and AI. Simply put, it’s the foundational layer for machine economy settlement and interaction.

Why is this direction so important? Just look at these two core logics.

First is the issue of a unified language. Currently, robot manufacturers operate independently, and hardware from different brands are incompatible. If there were a unified command system, AI Agents could seamlessly control various physical devices, which would fundamentally solve the fragmentation within the industry.

More critically, there is the concept of physical work proof. Blockchain here is not just a payment tool but uses sensor data to truly verify and confirm whether tasks are completed. Whether delivering packages or inspecting factories, these real-world jobs must have on-chain proof.

From another perspective, other projects teach AI how to think, but this direction teaches AI how to work in the real world—and actually get paid. This marks the turning point from purely on-chain Agents to Real World Agencies.

In the end, the story of DePIN finally forms a complete closed loop.