How Meta reduced diff authoring time by 40%

Diff authoring time (DAT) serves as a critical metric for quantifying the active effort developers spend on engineering, reviewing, and testing code changes. By tracking these units of work with high precision, organizations can conduct controlled A/B experiments on development tools and frameworks, shifting engineering management from intuition to empirical science. Data from Meta reveals that AI integration has reduced DAT by over 40% while simultaneously increasing throughput, signaling a transition where code generation is cheaper and "intent" becomes the primary currency of development. Despite these gains, traditional metrics often overlook essential, invisible work such as architectural alignment, meeting quality, and interpersonal collaboration. Future productivity frameworks must balance these automated efficiency gains with the human-centric dynamics of context gathering and validation to avoid the risks of cognitive debt and reduced software quality.