300 Kimi agents went through my 12 positions in 40 minutes. They came back with 3. Three trades, not three recommendations. The other nine tickers were the same bets under different names. A hedge fund pays a floor of PhDs to catch exactly this. The swarm caught it for the price of a subscription, and it only worked because nobody asked it to write a report. Every position, venue, wallet and market maker an agent touched became a node. Two agents hitting the same counterparty drew an edge. 217 edges later the book folded into three clusters. > Cluster one is seven positions quoted by the same market maker, one balance sheet on the other side of every fill. > Cluster two is five positions that route through one bridge, 58% of notional, and the prompt never mentioned a bridge. > Cluster three is four positions backed by the same synthetic dollar, so they have one exit and they will all use it on the same day. 12 tickers -> 3 trades -> 41 counterparties the prompt never named. A report would have given me 300 clean summaries and left the links on the floor. The links were the finding. A position you cannot trace back to its counterparty is not a position. It is a guess with a ticker on it. Next run adds to the same graph instead of starting from a blank page, so the map gets sharper every week without anyone re-reading anything. The full guide to building the exposure graph on top of the Kimi swarm is in the article below. Read it, then go look at who is actually on the other side of your book ↓