AI / LLM Basics Interview Questions
What are Guardrails in LLM applications?
Guardrails are the checks and constraints put around a model in a real application to keep its behavior within safe, expected, or on-topic bounds.
- Can filter or block certain categories of user input before it ever reaches the model
- Can also check the model's output before it's shown to a user, catching unwanted content or off-topic responses
- Often combined with a well-crafted system prompt, though guardrails typically add independent checks beyond just prompting
Guardrails exist because a model's own instruction-following isn't a perfectly reliable safety mechanism on its own, so applications commonly add external checks as an additional layer of protection.
What do guardrails do in an LLM application?
Why do applications commonly add guardrails beyond just prompting?
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