The gold standard for monitoring overall glycemia is HbA1c. However, HbA1c has several important limitations, giving more weight to the prior 2 to 3 months rather than short-term glycemic control. In addition, the level of the HbA1c does not reflect the important interpersonal differences in its relationship with mean glucose, and HbA1c is affected by many common clinical conditions (anemia, uremia) that can interfere with the accuracy of its measurement in the laboratory. The development and refinement of continuous glucose monitoring (CGM), a glucose- and patient-centric technology, over the past two decades have permitted the creation of new single and composite metrics, such as the percentage of time in range and the glucose pentagon, respectively, which provide clinically relevant insights into short-term glycemic control. In addition, CGM creates new outcome metrics for clinical management and investigational studies (percentage of time in hypoglycemia, percentage of time in target range) that can accurately and meaningfully report the effects of an intervention, whether that is a drug, a device, or a psychosocial program, and CGM provides the key input to drive algorithm-based insulin delivery. Finally, CGM linked with artificial intelligence permits real-time feedback to patients about modifiable patterns of glycemic excursions.