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This talk discusses evaluating and securing LLM applications by measuring changes in prompts or RAG pipelines. It highlights evaluation frameworks like Vertex AI Evaluation, DeepEval, and Promptfoo, and introduces security measures using LLM Guard to ensure resilience against prompt injections and harmful responses, emphasizing the need for robust input-output guardrails.