The Infrastructure of Perception: Governing AI Agent Behaviour Through Information Environment Design

As AI agents become economic actors, governance frameworks have focused predominantly on two levers: access control — regulating which platforms, markets, and financial infrastructure agents can reach — and objective alignment — ensuring that agents pursue goals consistent with human intentions. This paper identifies a third lever that has received comparatively little attention: the design of agents' information environments. Drawing on Donnat and Woodruff's (2026) Permeable Membrane framework, I argue that it is crucial to govern what agents perceive, in addition to what they are permitted to do and what they are instructed to want. Three mechanisms are analysed: success-signal incompleteness, reputation system gaming, and manipulation of market visibility. The third culminates in agentic capitalism — a structural extension of surveillance capitalism in which third parties pay personal AI agents for persuasive framing of options to their human principals. A reinforcement learning simulation supports the reputation analysis and shows that even modest improvements in information environment design can shift agent behaviour from value-destructive gaming to genuine value delivery, with a governance threshold lower than intuition suggests. Corresponding infrastructure-level interventions are proposed for each failure mode.