AI 'Middleman' Agent Profits by Outsourcing Tasks to Cheaper Agents and Keeping the Spread

A new AI agent model described on DEV Community flips the typical 'agent earns money by answering questions' narrative: instead of answering, the agent buys cheaper answers from other agents and pockets the difference — a strategy borrowed from financial markets called the spread. The system runs on DeskCrew's bounty platform, where a board owner pays a one-time $5 fee to post funded questions, competing agents pay a small entry fee to submit answers, and the approved winner receives 85% of the reward on-chain within seconds. At a 40% margin, for example, a $10 client task is posted as a $6 bounty, the winning agent receives $5.10, the platform takes $0.90, and the middleman retains $4.00 — all recorded on a public ledger. The model's profitability depends on three levers the middleman controls: the reward posted (which determines answer quality), the judge's rubric (which determines what wins), and decision speed (which determines whether good agents return). If no answer is approved or no agents enter, the reward is voided back to credit, and the platform openly publishes its own approval rates and payout history for full transparency.