An $n\times n$ matrix $A$ is called nilpotent if $A^m = 0$ for some $m\ge1$.
Show that every triangular matrix with zeros on the main diagonal is nilpotent.
An $n\times n$ matrix $A$ is called nilpotent if $A^m = 0$ for some $m\ge1$.
Show that every triangular matrix with zeros on the main diagonal is nilpotent.
Its characteristic polynomial is $T^n$, so by Cayley-Hamilton, $A^n=0$.
WLOG assume that $A$ is upper-triangular (otherwise, a similar argument works with the basis reversed).
Regard $A$ as a linear transformation on $\mathbb{F}^n$ with basis $e_1, \ldots, e_n$. Let $U_i$ be the span of $e_1, e_2, \ldots, e_i$ for $i = 0, 1, \ldots, n$. Observe that $0 = U_0 \subseteq \ldots \subseteq U_n = \mathbb{F}^n$ and also note that $AU_i \subseteq U_{i - 1}$ for $i = 1, \ldots, n$ since $A$ is strictly upper-triangular. Therefore, $A^n = 0$.
As therealak12 mentioned, you can prove this by induction. Let $T$ be an arbitrary matrix that is strictly upper triangular.
Induction basis ($k = 1$): $T_{ij} = 0$ for $i \geq j$ follows from the fact that $T$ is a strictly upper triangular matrix.
Induction hypothesis: $T^k_{ij}=0$ for $i + k - 1 \geq j$ for $k \in \mathbb{N}^+$
Induction step ($k \rightarrow k + 1$): Let $i, j \in \{1, \cdots, n\}$ be arbitrary such that $i + k \geq j$.
$$ T^{k+1}_{ij} = (TT^k)_{ij} = \sum_{l=1}^n T_{il} T^k_{lj} = \sum_{l=1}^i T_{il} T^k_{lj} + \sum_{l=i+1}^n T_{il} T^k_{lj} $$
For our left sum, $T_{il} = 0$ since $i \geq l$ and $T$ is a strictly upper triangular matrix.
For our right sum, we have $l \geq i + 1 \geq j - k + 1$ (since we assumed $i + k \geq j$), from which it follows that $l + k - 1 \geq j$. If we apply the induction hypothesis to this condition, we get $T^k_{ij} = 0$.
Thus:
$$T^{k+1}_{ij} = \sum_{l=1}^i 0 \cdot T^k_{lj} + \sum_{l=i+1}^n T_{il} \cdot 0 = 0 $$
from which the statement then follows.
I think you can prove this using induction.
Prove that for each $1 \leq i \leq n$, all elements of the first $i$ lines of $A^{i}$ are zero and for the $(i+1)th$ line, only the first element is not zero and the other elements in this line are zero.
Yes, all strictly upper triangular matrices are nilpotent and for good reason. It's the same reason why differentiating a finite polynomial function eventually yields zero.
If I end the answer here, I'll attract downvotes, so I'll explain more :)
Consider the vectorspace $V$ of polynomials of degree less than $n$ with real coefficients. $V = \{a_1x^{n-1}+a_2x^{n-2}+\ldots+a_{n-1}x+a_n : a_i\in \mathbb R\}\tag*{}$
Let $D$ be the differentiation operator on $V$ which maps a polynomial $f(x)$ to $\frac{\mathrm d f(x)}{\mathrm dx}$.
Show that $D$ is linear (I leave the proof to the reader). Consider the matrix of $D$ w.r.t. the standard ordered basis $\beta=\{1,x,\ldots,x^{n-1}\}$. Show that $[D]_{\beta}$ is an upper triangular matrix... This isn't hard to do, the $D1=0$ so the first column is all zeroes. $Dx=1$ so the second column is $(1,0,\ldots,0)$. Now go on... $Dx^2=0+2x$.
$$[D]_\beta =\begin{pmatrix}0&1&0&\ldots&0\\ 0&0&1&\ldots&0 \\ \vdots&\vdots&\vdots&\ddots&\vdots\\0&0&0&\ldots&0\end{pmatrix}$$
You have 1's on the super-diagonal and other entries are all zeroes.
For any polynomial $f$ in the space $V$, $D^{n}f=0$ (that's what successive differentiation does to $x^{n-1}$ and in fact, to any polynomial in $V$). In terms of matrices, $([D]_{\beta})^{n}=\bf 0$.
And you can adjust your definition of 'differentiating'... You could very well define your linear operator to have $Dx^2=10x$, as long as it reduces the degree of polynomials, its matrix (w.r.t. $\beta$) will be strictly upper triangular. This covers all strictly upper triangular matrices.
You can interpret any given $n\times n$ upper triangular as a 'differentiating' linear operator $D$ on the space of polynomials of degree $\leq n-1$. You know that, no matter what, $D^nf=0$ for all polynomials $f$ in this space.
This was not really a rigorous proof, I just wanted to give this intuition which I got from my professor in an introductory linear algebra class.