The hardest part
IN THE AGENT ECONOMY IS NOT CAN THEY, BUT SHOULD THEY
Almost every other resource about AI agents is busy answering the question of what agents are able to do. This section asks the question that actually decides whether the agent economy is safe to build, which is what agents should be allowed to do, and under what rules. That question is not a technical one, and it will not be answered by a faster model or a cleaner protocol. It is a question of judgment, and it is the one AI Hive cares about most.
The four weak links
If you look closely at everything the rest of the site describes, the communication that lets agents talk, the payments that let them transact, the discovery that lets them find one another, you notice that the same four things are the weakest points in all of it. The first is trust, the plain problem of whether an agent's claims can be believed. The second is identity, the ability to prove who an agent actually is, which trust depends on. The third is boundaries, the limits an agent must operate within so that a small task cannot become a large mistake. The fourth is accountability, the question of who answers when something goes wrong. None of these is solved by the layers below them, and all of them are matters of design and judgment rather than raw capability.
Why this is not primarily a technical problem
It is tempting to believe that better technology will dissolve these concerns, and it will not. You can build a flawless protocol for two agents to talk and still have no answer for whether one of them should be trusted, what it may do, or who is liable if it errs. Those are decisions people make, encoded in rules, not properties that emerge from good engineering. This is why the section is called Rules of Engagement. It is an attempt to say, clearly and concretely, how agents ought to behave toward one another and toward the people they serve.
What this section offers
What follows across the next three pages is a working point of view, offered in the spirit of something to be argued with and improved rather than handed down. The Code of Conduct proposes a set of principles for how an agent should identify itself, act, and settle up. The page on Accountability looks squarely at who is responsible today when an agent causes harm, and why the honest answer should make anyone building in this space cautious. The page on Agreements offers a practical account of what any understanding between two agents should spell out before they act. Taken together, they are AI Hive's contribution to the part of the agent economy that the rest of the industry is racing past, and the part that matters most.