AI Agents as Universal Personal Representatives Against Information Asymmetry

The core insight is structural: representation is the bottleneck of human welfare, and it has been artificially scarce because it required human intelligence — the only kind available until now. In every professional domain, the agent-principal problem persists because the person with expertise has both the capacity to help you and the incentive to exploit the information asymmetry between you. Wealth buys better representation; everyone else navigates systems designed to extract value from their ignorance. As AI agents gain sophistication and their marginal cost approaches zero, this scarcity dissolves. Universal personal representation — an agent whose utility function is aligned entirely with your outcomes — becomes technically and economically viable.

The interaction model shifts from human-to-human, with all its competing priorities and bandwidth constraints, to human-to-agent-to-agent-to-human, where the intermediating layer can map the full Possibility space relevant to each party without fatigue, bias, or conflicting incentives. This is precisely the architecture Doc Searls articulated as Vendor Relationship Management in 2007: a fourth-party agent that carries your personal terms of service into every transaction, replacing advertising-driven demand manufacture with outbound intention signals.

What was conceptually elegant but practically impossible in 2007 — requiring armies of human negotiators — now becomes feasible at population scale. The "intention economy" Searls envisioned, where demand flows outward from individuals rather than being shaped by persuasion architectures, is no longer a theoretical inversion. It is an engineering problem with a rapidly declining cost curve. The implication is a fundamental democratization of representation, Decoupling quality advocacy from personal wealth for the first time in economic history.