Guardrails

A prompt is the instruction set that defines how an AI agent behaves in a given task, covering role, tone, permitted actions, and output format. Prompts express intent but do not enforce it, which is why hard limits belong in guardrails rather than in prompt wording.

Human in the loop describes a review step where a person approves or corrects AI output before it reaches the customer. Teams typically apply it to high-risk intents such as refunds, cancellations, and complaints, then relax it selectively as measured accuracy on those intents proves out.

A fallback is the safe response an AI agent gives when its confidence is too low to act, typically an offer to hand the conversation to a human. Well-designed fallbacks fail early rather than guessing, because a confidently wrong answer costs far more than an admitted gap.

Grounding is the practice of constraining an AI agent’s answers to approved knowledge sources and live system data rather than to the model’s own training. Grounding is the main defence against hallucination, and it is what makes an AI answer auditable back to a specific document or record.