video1.0<iframe src="https://www.loom.com/embed/b6c52df30ce3419fb661e9b59c820896" frameborder="0" width="1350" height="1012" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>10121350Loomhttps://www.loom.com10121350https://cdn.loom.com/sessions/thumbnails/b6c52df30ce3419fb661e9b59c820896-de07350e98f10a16.gif255.762In this video, I discuss a phase of my project focused on building AI-powered conversations that are testable, repeatable, and production-ready. I specifically address the challenge of ensuring consistent AI behavior, particularly in sensitive areas like healthcare training. I demonstrate how I defined a patient scenario, created structured test cases, and ran evaluations to assess AI responses. The results showed that 8 out of 10 test cases passed, with a scoring system to flag any responses needing human review. I encourage viewers to consider the importance of rigorous testing in AI implementations.