Guardrails for LLMs: Securing Inputs, Protecting Outputs

Practical guardrails for Large Language Models (LLM) systems covering safe inputs, protected outputs, access governance and monitoring to reduce risks, ensure compliance and build trustworthy AI experiences.

After completing this Pathway, you will be able to:

• Design input guardrails and trust boundaries for secure LLM pipelines
• Assess and mitigate data leakage, prompt injection and harmful output risks