We prove a fundamental misalignment in transfer learning: the source regularization that minimizes source risk almost never coincides with the regularization maximizing transfer benefit. Through sharp phase boundaries for L2-SP ridge regression, we characterize the transfer-optimal source penalty τ_0^* and show it diverges predictably from task-optimal values, requiring stronger regularization in high-SNR regimes and weaker regularization in low-SNR regimes. Additionally, in isotropic settings t...