The Macroeconomic View of Agents
Agentic AI - systems designed to take autonomous action - represents a fundamental shift in the variable cost of intelligence. For the first time, organizations can scale complex labor without scaling human headcount linearly.
The Liability Gradient and Macro Loops
However, an autonomous agent without a rigorous governance boundary represents uncontrolled liability. As agents begin to interact with other agents at high frequency, we witness macro regression loops: recursive errors caused by Agentic Drift where probabilistic models lose the thread of their original intent.
To prevent catastrophic failure, companies must deploy an Exogram Action Admissibility Protocol (EAAP) layer that deterministically checks the state and authorization of an agent before it commits an operation to a system of record.
For detailed EAAP specifications, see our Documentation Center. Original article hosted at Built In.