What is gradient of MSE loss in Linear Regression?

The gradient is proportional to Xᵀ(Xβ − y).

For MSE = (1/n)||Xβ − y||², derivative w.r.t β gives gradient = (2/n)Xᵀ(Xβ − y). This direction shows how coefficients must change to reduce prediction error.