The public release of Continuous Learning with Human Feedback (CLHF) on the Galileo Evaluation Platform offers a breakthrough workflow that enables domain-specific tuning of generic LLM-as-a-Judge evaluation metrics with as few as five annotated records, increasing accuracy by upwards of 30%. This approach simplifies the process of generating custom metrics tailored to an organization's use case, reducing time to build a custom metric from weeks to minutes and unlocking the ability for enterprises to rapidly build tailored metrics. By unifying human and automated evaluations on a single platform, AI teams can fully unlock the potential of their AI applications.