Let , and . On the score event with , the prediction inequality from Lasso stationarity gives . If the Compatibility condition for the Lasso with constant holds on this cone, then . Here and is the true support of a vector.
With objective , the Gaussian score event for the Lasso gives , where . The Lasso cone condition activates the Compatibility condition for the Lasso. Then . Thus even . This controls prediction and coefficient error together, including a design with correlated columns.
The fast-rate Lasso prediction bound under compatibility implies . Each true coefficient larger in absolute value than this bound has the correct estimated sign. This conclusion alone does not ensure absence of false positives.

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