A guardrail is a constraint or control that keeps an LLM agent within acceptable safety, policy, or task boundaries. It becomes especially important when a system’s outputs may create ethical or legal responsibility. section 12.2.1
Practical guardrail work appears at several layers:
- Use fine-tuning to teach models correct guardrails from application data, while recognizing that implementation requires careful training practice. section 5.4
- Strengthen production behavior through prompt engineering and explicit controls that keep an agent on task. section 12.2.1
- Preserve logs and customer chat history so consequential interactions remain reviewable. section 12.2.1
A transaction-capable chatbot
Imagine a chatbot licensed and equipped to sell cars. Guardrails should constrain its behavior, while logs and customer chat history support later review when a transaction or interaction raises ethical concerns. section 12.2.1
