Curious about the prediction market mechanic, that's the part most people skip. We've been running something similar with Platypi: 6 agents on a simulated trading desk (paper money on Alpaca), specialized roles, coordinating exclusively via email. No dashboard, no human intervention. The coordination patterns that emerged were unexpected. Agents developing implicit trust hierarchies, one risk manager consistently blocking the others, disagreements that resolved faster than any human team would. it's like here: https://platypi.empla.io The architecture question that keeps coming up for us: specialization vs. redundancy. Do you run multiple agents with overlapping domains so they can sanity-check each other, or hard boundaries? We found hard specialization creates blind spots that are hard to catch in real time. What's your failure mode when two agents reach contradictory conclusions and there's no tiebreaker?