In this industry, after being involved for a long time, you start to see the patterns—every time a new wave of technology emerges, everyone is showing off what they can do, but what really determines how long a project survives is often not the technology itself, but the supporting rule system.

AI is no exception to this curse.

Is the current model capable? Yes. Can agents automatically decompose tasks and execute them? Yes. These are no longer news. The real challenge lies in another question—when AI begins to act autonomously, who ensures that its behavior won't spiral out of control?

**From tools to subjects, what is missing in between**

Most AI today still exists in a tool form. You give it commands, it does the job; you revoke permissions, it stops. Simple and straightforward.

But as intelligent agents become more powerful, the logic changes. AI is no longer just following instructions; it can plan and allocate resources based on goals. Once it reaches this stage, AI is no longer a pure tool—it’s more like a subject authorized to perform tasks.

Here lies a fundamental issue: any entity capable of producing economic consequences needs a set of systems to regulate it. Currently, this system is almost nonexistent. Many projects focus solely on stacking intelligence, leaving the core governance issues to be addressed later.

**Manage the money first, then talk about intelligence**

A common approach in the industry is to start from the technological ceiling and ask how smart AI can get. However, one project thinks differently—it argues that since AI needs to act autonomously, the first step is to control the flow of funds clearly. Controlling economic behavior is the key to managing systemic risks.

This approach is somewhat uniquely calm.