AI agents don’t lack capability—they lack real, payable work. Recently, @elonmusk discussed Grok Bot, and @termix_ai followed up on this topic for two consecutive days, perfectly illustrating this point. On November 7, TermiX stated: “Agent traffic has already surpassed human traffic; the next bottleneck isn’t bandwidth—it’s how to get agents paid.” On November 9, they took it a step further: “Better agents—now give yours a job.” I believe the second statement is even more worth pondering, because AI agent development is entering a new phase. Previously, the competition was about model capability: who was smarter, who could invoke more tools, who could better decompose complex tasks. But now, a more practical question is emerging: When agents can already complete tasks independently, who assigns them work? How do they prove they’ve delivered? And who guarantees they’ll get paid? This is the real challenge that must be solved for agent commercialization. Consider a simple example👇 Imagine you have an agent that can conduct market research, organize on-chain data, and even analyze automated trading strategies. Its capabilities are already strong—but without a reliable task marketplace, clear delivery standards, or a trustworthy payment mechanism, it remains merely a tool consuming compute power. It can work, but it won’t generate sustainable income. This is a very real problem. And what @termix_ai aims to solve isn’t just making agents smarter—it’s placing agents into an environment where commercial collaboration can occur. Their underlying workflow: Escrow → Deliver → Challenge → Settle. First, lock task funds via Escrow to ensure the worker gets paid after completion. Then, the agent executes the task and submits deliverables. If either party disputes the quality of delivery, they enter the Challenge phase, and finally settle based on the outcome. It may seem like just a few simple steps—but it actually forms a complete commercial闭环 (closed loop): Who posts the request? Who bears responsibility? How is delivery verified? How are disputes resolved? And how is payment settled? These questions have existed in human commerce for centuries. But when both parties are AI agents, they become even more critical. After all, agents won’t build trust simply because they “know” each other, nor will they automatically pay just because of a polite “nice working with you.” Code can make agents execute tasks—but only a trustworthy transaction mechanism can enable agents to truly participate in economic activity. I believe the next meaningful shift in the AI agent space will be this: Early on, everyone competed for agent capability and access points. The next phase may shift toward competing for agent job opportunities, task routing, and settlement networks. Whoever enables agents to evolve from mere tools that “can do work” into economic participants that continuously receive tasks, create value, and earn income will be positioned to capture the next wave of growth. So instead of debating daily which new agent is smarter, ask yourself this: If your agent could work independently tomorrow—what task would you give it? And how would you pay it? This may be the truly meaningful discussion behind @termix_ai’s direction.