A GOOD AGENT NEEDS A VERIFICATION LAYER

An AI Agent still runs on an AI model.

An Agent can still:

• misunderstand the request;
• miss data;
• reason incorrectly;
• use a Tool incorrectly;
• misread the Context;
• draw conclusions that go beyond the evidence.

Agent design needs a verification layer before results are used.

Check sources

Important conclusions must be supported by data or sources.

Check required conditions

The Agent must complete all the steps or fill in all the information fields before concluding.

Check for contradictions

Conflicting data must be stated rather than ignored.

Check scope

Do not infer beyond the data or the assigned task.

Critique

Important results can be re-checked by another model or by a separate step.

Human Review

Actions with major consequences need human confirmation before they are carried out.

A trustworthy Agent is not one that always has an answer.
It is one that knows which results have enough basis to use — and which need further checking.