A new cs.AI paper examines how agent instructions can be autoformalized into policy-as-code.
The problem is practical: many agents are governed by natural-language rules that are easy to write but hard to enforce reliably. Converting instructions into executable policies could make compliance checks more consistent.
The work is relevant for teams deploying agents in environments where actions need guardrails, audit logs, and clear boundaries.