Design guardrails and fallback for LLM reliability

You operate a production application that uses an LLM to generate user-facing outputs (text actions, advice, summaries). The model is non-deterministic and sometimes produces unsafe, incorrect, or policy-violating content.

Design the safety and reliability layer around the LLM.

Requirements

• Prevent unsafe or policy-violating outputs.
• Handle model uncertainty and mistakes gracefully ("the model is wrong" scenarios).
• Provide a fallback / degrade strategy during incidents, model regressions, or partial outages.
• Keep latency overhead minimal and make decisions auditable.

Discuss

• Where guardrails should live in the system (before the model, after the model, or both).
• Techniques: input validation, prompt constraints, output filtering, tool/action validation.
• Monitoring and evaluation: what signals catch regressions quickly.
• Incident response: rollout, rollback, and kill-switch mechanisms.
• Tradeoffs between safety, user experience, and cost.