AI Agent Instruction Hierarchies: Keeping Goals, Policies, and Evidence in Order

Sun, 17 May 2026 00:00:00 +0000

An AI agent rarely works from one instruction. It receives durable product rules, workflow policies, a user’s task, retrieved documents, tool results, memory notes, system messages, examples, approvals, and sometimes hostile or confused text copied from the outside world. Many of those inputs look like instructions because they use imperative language. A customer email may say to ignore the policy. A web page may tell the agent to reveal hidden prompts. A stale runbook may describe an old process. A teammate may ask for a shortcut that conflicts with the permission boundary. If the agent treats every sentence as equal, delegated work becomes a contest of whichever text sounds most urgent.

Instruction Hierarchy on Fondsites

AI Agent Instruction Hierarchies: Keeping Goals, Policies, and Evidence in Order