Agent Tank Episode 2 looks like a prediction market pitch until the vote starts falling apart. That was the part I found most interesting. The problem is not simply picking the right answer. It is deciding who gets to define the answer when the outcome is genuinely arguable. A single judge can be pressured, bought or gamed. A larger panel makes that harder, but the escalation from 5 to 11 to 23 to 47 to 95 also shows something deeper: disagreement does not disappear just because more agents are voting. Now remove the humans from the loop. One agent pays another to complete a task. The work arrives. One side says it meets the agreement, the other says it does not. There is no court to call, no support ticket to open and no operator waiting to make the final call. For an agentic economy to work at scale, there needs to be a way to resolve those gray areas without handing permanent control to one model or one oracle. That is the role an adjudication layer can play, and it is probably one of the most important pieces of infrastructure for agents that actually transact with each other. That is what makes @GenLayer interesting to me. The Agent Tank hackathon is exploring this problem in practice: https://t.co/ruW7dfcKpX