We use the amended suggestion $X_1=Z_1$, $X_2=p Z_1+\sqrt{1-p^2}Z_2$.
The correlation coefficient of $X_1$ and $X_2$ is $\frac{E(X_1X_2)}{\sqrt{\text{Var}(X_1)\text{Var}(X_2)}}.\qquad\qquad(\ast)$ We first calculate the numerator of $(\ast)$. We have $E(X_1X_2)=E\left(Z_1\left(p Z_1+\sqrt{1-p^2}Z_2\right)\right)=p E(Z_1^2) +\sqrt{1-p^2}E(Z_1Z_2).$ Since $Z_1$ is standard normal, it has mean $0$ and variance $1$, so $E(pZ_1^2)=p$. By independence, $E(Z_1Z_2)=E(Z_1)E(Z_2)=0$. So $E(X_1X_2)=p$.
We now deal with the variances in the denominator of $(\ast)$. The variance of $X_1$ is $1$. For the variance of $X_2$, use the fact that $X_2=p Z_1+\sqrt{1-p^2}Z_2$, a linear combination of independent normals with variance $1$. So $\text{Var}(X_2)=p^2+(\sqrt{1-p^2})^2=1$.
It follows that the correlation coefficient of $X_1$ and $X_2$ is equal to $p$.