AI safety in production goes beyond model capabilities. Adversarial users attempt prompt injection. Edge cases produce inappropriate outputs. Safety guardrails provide defense-in-depth protecting users and organizations.
Guardrail Layers
Input validation filters obviously malicious prompts. System prompts establish boundaries. Output filtering catches harmful responses. Human review handles uncertain cases. Multiple layers catch what individual layers miss.
- Implement input validation rejecting prompt injection attempts
- Use system prompts defining clear behavioral boundaries
- Filter outputs for harmful, biased, or inappropriate content
- Log interactions enabling audit and improvement
- Establish escalation paths for edge cases requiring human review
Continuous Improvement
Safety requirements evolve as attack techniques advance. Monitor for new adversarial patterns. Update guardrails based on production incidents. Regular red-teaming identifies weaknesses before attackers do.