Tag
The article discusses the problem of agent sprawl in teams using multiple AI agents with overlapping permissions and workflows. It proposes a basic control layer with owner, read/write systems, budget, stop rule, and four agent classes: readers, routers, operators, spenders.
This tweet introduces a new organizational model for an AI-forward agency, shifting from functional handoffs to outcome-driven loops with agent fleets and systems memory.