The recent explosion of AI agents is no longer just a prediction; everyone can see it. But behind this lies a tricky problem—how should identity verification and governance be handled? There has never been a particularly elegant answer.

Recently, I came across the Kite project, which has made some interesting explorations into this pain point. It brands itself as the "first AI payment blockchain," mainly building an agent network that allows users to easily discover and invoke various AI agents within a familiar interface, handling everything from ordering food to shopping. To some extent, this is breaking the current fragmented AI service experience, similar to the evolution from portal websites to search engines in the early days of the internet.

In terms of technology stack, it still chose an EVM-compatible Layer1, optimized specifically for real-time coordination among AI agents. But the truly interesting part is its three-layer identity architecture design—completely separating the management of users, agents, and sessions. This not only enhances security but also allows for very fine-grained permission control. Traditional AI identity management tends to be vague; it’s often unclear who is responsible for what. Kite uses encrypted identity mechanisms to assign verifiable labels to each AI agent, model, and even data source, enabling traceability and governance. In today’s world of rampant deepfake content, this targeted approach is definitely worth paying attention to.

The governance layer is also quite flexible—programmable rules allow you to set agent permissions, behavioral boundaries, and fund flows at will. There’s an interesting phrase in the documentation: "Let AI agents operate autonomously in the wild, while remaining within a governance framework." This is no small balancing act.