Why AI Agent Rules Need Context and Layered OS Enforcement

An Empirical Study: AI Agent Rules Need Context and Layered Enforcement

Our study of over 2,000 instructions reveals that simple rules often fail without deep context. Most policies require tracking events across time and specific project details, which standard tools miss. We found that effective enforcement demands compiling natural language into concrete, layered OS checks that understand the full workflow.

"Agent policy enforcement begins by compiling repository and task context into concrete state that deterministic checks can evaluate."