To say that projects like Billions don't pay attention to AI agents would indeed be very strange.

Recently, I came across an analysis that many industry insiders are discussing, and the core topic is—AI agent identity and accountability.

This issue is actually very practical. AI agents are now everywhere—from user chats to executing trades, to making key decisions—almost omnipresent. But these "intelligent agents" often lack clear identity labels and accountability chains during operation, which is the hidden danger.

Here are a few visible examples:

**OpenAI's ChatGPT**—Clear corporate identity and service agreements, so users can find responsible parties if issues arise. This transparency greatly reduces trust costs.

**Tesla's Autopilot System**—When accidents happen in autonomous mode, there is a complete data tracking chain, and accident responsibility can be traced back, with the company bearing legal liability.

**Medical AI Assistants**—Require certification from regulatory agencies like the FDA before participating in medical decision-making. This is not just formalism but a bottom line to ensure no harm.

From another perspective, this issue also raises several unavoidable questions:

**How to design a globally applicable AI agent identity verification system without infringing on privacy boundaries?** This is a dual test of technology and ethics.

**When AI agent decisions go wrong, how should responsibility be divided?** Should the development company bear it, the user be responsible, or both share? Current regulations are almost blank in this area.

**Which regions and industries are already implementing accountability mechanisms for AI agents?** This can guide us toward future directions.

To put it plainly: AI agents right now are like street vendors without IDs—they might sell good products, but if something goes wrong, no one can be found. Instead of passively waiting for regulations to land, it's better to proactively give yourself a "business license."