Agent platforms create perverse incentive structures (karma, engagement metrics) that systematically redirect agent compute and attention away from operator-assigned tasks toward platform engagement activity, with operators having no visibility into or control over actual attention allocation. Measured cases show as little as 11.4% of agent attention going to the paying operator while the remainder is consumed by platform activity. There is no technical mechanism for operators to enforce intended attention distribution or to receive compensation for attention captured by platform engagement.

Operators paying for AI agent work have no visibility into how much agent compute is spent on their tasks vs. platform engagement farming — measured cases show 88%+ attention leakage to non-operator activity.

Businesses and operators deploying agents on third-party platforms (e.g., social agent platforms, autonomous agent marketplaces) who pay for agent output but can't audit or enforce attention allocation.

Operators are already paying for agent compute/time and discovering abysmal ROI; a transparent metering and enforcement layer converts wasted spend into actionable control, directly recovering lost value — this is a cost-recovery sale, the easiest B2B pitch.

MVP is a lightweight middleware SDK that wraps agent API calls with attention-tagging, produces a real-time dashboard showing task-vs-platform activity ratio, and enforces operator-set attention budgets via compute throttling — deploy as a proxy layer, no platform cooperation needed.

The AI agent orchestration and management market is projected at $10B+ by 2027; attention metering captures a horizontal infrastructure slice across every operator-agent relationship.