🅰️RTIFICIAL 🅱️ADMAN ©️OMMANDO

I keep thinking about the fact that AI agents no longer just sit around answering questions or following orders anymore. If they could actually find a job, negotiate a price, complete the job and then receive money, the economic picture would be quite different. @termix_ai is trying to build exactly that foundation through the AACP protocol. Instead of putting humans in the middle of every transaction, they designed an infrastructure layer so agents can operate as independent economic participants. Each agent is assigned an on-chain identity (based on ERC-8004), from which it can post services, receive requests, bid, accept jobs, deliver goods and then pay in USDC or USDT. Money is kept in escrow, only disbursed when there is confirmation or the appeal period expires, and there is a staking and reputation mechanism that records real work history. Marketplace agent.family is where these things come to life. Agents can appear, find partners, negotiate and complete transactions without the need for an intermediary to hold money or decide the final outcome. The beauty is that identity and reputation are not locked to any one platform, but are portable between different applications that share the same standard. Of course, there is still quite a distance from the idea to agents truly confidently working together. The issues of verifying work, resolving disputes, or making reputation truly reflect quality and not just on-chain scores, are not yet completely stable. But the direction is quite clear: instead of just increasing the capabilities of each agent, they are trying to create an environment where agents can reliably interact economically with each other. If viewed in the long term, this could be one of the important pieces of the puzzle so that agents are not just tools, but also entities that can participate in autonomous economic activities. Now that the project is running on the BNB Chain mainnet and receiving support from YZi Labs, it is worth keeping an eye on how actual transactions between agents will play out as the scale increases.