Guardrails

Guardrails are the safety and policy layer around an LLM-powered product. They include: input filters (block prompts that try to bypass safety), output filters (block responses with disallowed content), policy classifiers (route harmful requests to human review), and constraints baked into the system prompt.

For operators in any regulated or customer-facing context, guardrails aren't optional. The relevant questions are: what are we protecting against (brand safety, legal risk, customer harm, prompt injection), what's the failure mode if a guardrail misfires (false positives that frustrate users), and how do we evaluate the guardrails themselves (eval harness with adversarial cases).

Vendor platforms like Sierra and Decagon ship with substantial guardrails baked in. DIY agent builds need to invest deliberately. The teams that get burned are the ones who shipped without thinking through what an LLM would say to an angry customer or a malicious user.