Guardrails for production: seven checks before an agent acts

While an AI agent only answers questions, a mistake is cheap. Once it starts acting — changing records, sending emails, launching operations — the cost of a mistake rises sharply. Production therefore needs limits that work regardless of how confident the agent looks.

At Korveniq AI we defined seven checks an agent passes before every action. They limit the scope of actions, protect sensitive data and keep a human in control of critical steps.

Limiting the scope of actions

The first checks answer the question “what is the agent allowed to do at all”. It gets an explicit list of tools and operations, and everything else is forbidden by default. Rights are granted for a scenario, not “just in case”.

Each action has boundaries: permitted values, scale of changes, a list of allowed recipients. Crossing a boundary blocks the action until it is reviewed.

Protecting sensitive data

Before acting, the system checks what data leaves and which system it goes to. Personal and confidential fields are masked or removed if the operation does not need them.

These rules act at the infrastructure level, not only in the model's instructions, so they do not depend on how a request is phrased.

A human controls critical steps

For irreversible or expensive operations the agent prepares a proposal and a person decides. They see exactly what will be done, what data the decision rests on and what will change after approval.

The threshold above which approval is required is set in advance and revisited based on results.

Checks work at the infrastructure level and do not depend on how a request is phrased.

A log and reviewing the rules

Every action and every check is written to a log: what the agent meant to do, which checks it passed and how it ended. This serves both investigation and improving the rules themselves.

The Korveniq AI team can help define the set of checks for your scenario and embed them into an already running system.