The text discusses the challenges of dealing with "hallucinations" in Generative AI (GenAI) applications, emphasizing the importance of detecting and managing these errors to maintain user trust and product reliability. It highlights the risks of inaccurate AI outputs, which can lead to user frustration and even business loss. To address these issues, the text outlines three strategies: grounding responses using Retrieval-Augmented Generation (RAG) to provide accurate context, implementing guardrails to filter out risky outputs, and employing a secondary AI model to fact-check responses in real-time. These approaches aim to enhance the visibility and control over AI outputs in production environments, ensuring they are both accurate and safe. LaunchDarkly AI Configs is presented as a tool that aids in monitoring and optimizing AI systems by enabling teams to run tests, score responses, and automate responses to inaccuracies, all while maintaining delivery speed. The text concludes by inviting users to try out these configurations to build more trustworthy AI applications.