Finding eigenvectors of a 3x3 matrix Struggling with this eigenvector problems. I've been using this SE article (Finding Eigenvectors of a 3x3 Matrix (7.12-15)) as a guide and it has been a very useful, but I'm stuck on my last case where $\lambda=4$.

Q: Find the eigenvalues $\lambda_1 < \lambda_2 < \lambda_3$ and corresponding eigenvectors of the matrix

$$A=\begin{bmatrix}-2 & 3 & 0 \\ 0 & -1 & -10 \\ 0 & 0 & 4\end{bmatrix}=\begin{bmatrix}-2-\lambda & 3 & 0 \\ 0 & -1-\lambda & -10 \\ 0 & 0 & 4-\lambda\end{bmatrix}$$
The eigenvalues for the $A$ matrix are $\lambda_1=-2$, $\lambda_2=-1$, $\lambda_3=4$ respectively.
Case $\lambda=-2$
$$A-2I_3=\begin{bmatrix}-2-(-2) & 3 & 0 \\ 0 & -1-(-2) & -10 \\ 0 & 0 & 4-(-2)\end{bmatrix}=\begin{bmatrix}0 & 3 & 0 \\ 0 & 1 & -10 \\ 0 & 0 & 6\end{bmatrix}$$
$$rref(A-2I_3)=\begin{bmatrix}0 & 1 & 0 \\ 0 & 0 & 0 \\ 0 & 0 & 1\end{bmatrix}$$
$x_1$ is our free variable
$$\vec{v_1}=\begin{bmatrix}1\\0\\0\end{bmatrix}$$
Case where $\lambda=-1$.
$$A-I_3=\begin{bmatrix}-2-(-1) & 3 & 0 \\ 0 & -1-(-1) & -10 \\ 0 & 0 & 4-(-1)\end{bmatrix}=\begin{bmatrix}-1 & 3 & 0 \\ 0 & 0 & -10 \\ 0 & 0 & 5\end{bmatrix}$$
$$A^\prime=rref(A-I_3)=\begin{bmatrix}1 & 3 & 0 \\ 0 & 0 & 0 \\ 0 & 0 & 0\end{bmatrix}$$
Finding the $ker(A-I_3)$ we find $x_2$ and $x_3$ as our free variables. Solving for each variable we get $x_1=3x_2$ and $x_2=1$.
$$\vec{v_2}=\begin{bmatrix}3 \\ 1 \\ 0\end{bmatrix}$$
Case $\lambda=4$
$$A+4I_3=\begin{bmatrix}-2-4 & 3 & 0 \\ 0 & -1-4 & -10 \\ 0 & 0 & 4-4\end{bmatrix}=\begin{bmatrix}-6 & 3 & 0 \\ 0 & -5 & -10 \\ 0 & 0 & 0\end{bmatrix}$$
$$rref(A-I_3)=\begin{bmatrix}1 & -\frac{1}{2} & 0 \\ 0 & 1 & 2 \\ 0 & 0 & 0\end{bmatrix}$$
This is where I'm stuck. I checked wolframalpha and it says my last eigenvector should be $\vec{v_3}=\begin{bmatrix}-1 \\ -2 \\ 1\end{bmatrix}$ and I'm not sure how it can be that. Thanks in advance!

The equations corresponding to that row-reduced form at the end are 
$$
x - y/2 = 0 \\
y + 2z = 0
$$
Since $z$ is a free variable, you can pick $z = 1$ and back-substitute to get 
$y = -2$, and then use this in the first equation to get $x = 1$. Of course, any nonzero multiple of this vector is also an eigenvector for $4$. 
