Control layers are necessary before allowing AI agents to read data, call tools, or perform real actions.
AI agents differ from chatbots in their ability to select the next step and call a tool. This ability to take action makes agents useful, but it also creates risks if authority and stopping conditions are unclear.
Four layers of control
Layer 1 limits the data the agent can read. Layer 2 only grants the necessary tools. Layer 3 requires approval for actions such as submitting, deleting, paying, or changing permissions. Layer 4 logs all input, decisions, and tool results.
Classification of actions
Divide actions into three levels: read-only actions that can be run automatically; draft creation actions that require template-based validation; and irreversible actions that require user confirmation. Avoid using a single key with full access to all tools.
Stopping conditions
The agent must stop when critical data is missing, the tool returns repeated errors, results are inconsistent, or the budget is exceeded. When stopping, the system needs to explain what it has done and what the user needs to add.
Test before deployment.
Create a set of scenarios including missing data, ambiguous requests, malicious content, API errors, and unauthorized actions. Only deploy when the agent denies or requests confirmation in all risk scenarios.
