Frontier labs are flipping intelligence pipelines from human-made to model-made components. This shift prioritizes synthetic simulation over manual curation to achieve massive gains in speed and cost. While accuracy may dip slightly, the efficiency trade-off accelerates iteration. Practitioners must now optimize for synthetic data quality rather than relying on scarce human-labeled datasets.