I don't have anything to add regarding your questions on quadratic forms; anon's answer looks to me to be very illuminating and thorough. But it may be worth mentioning a generalization in a different direction.
Write $x^2+y^2=z^2+w^2$ as $(x-z)(x+z)=(w-y)(w+y)$ and define $s=x-z$, $t=w-y$, $u=w+y$, $v=x+z$ so that the equation of the cone becomes $sv=tu$. Fixing the ratio $s:t$ means $u:v$ has to be fixed to the same ratio. Hence for constants $a$, $b$, not both zero, the two-dimensional plane defined by $at=bs$, $av=bu$ lies in the cone. Fixing the ratio $s:u$ instead, which entails fixing $t:v$ to the same ratio, gives planes $cu=ds$, $cv=dt$ for all pairs $c$, $d$, not both zero.
If $(a_2,b_2)$ is not a scalar multiple of $(a_1,b_1)$ then the planes $a_1t=b_1s$, $a_1v=b_1u$ and $a_2t=b_2s$, $a_2v=b_2u$ intersect only at the origin. The analogous statement holds for the planes $c_1u=d_1s$, $c_1v=d_1t$ and $c_2u=d_2s$, $c_2v=d_2t$ when $(c_2,d_2)$ is not a scalar multiple of $(c_1,d_1)$. On the other hand, the plane $at=bs$, $av=bu$ and the plane $cu=ds$, $cv=dt$ intersect in a line. The two planes together span the three-dimensional linear space tangent to the cone at all points on their common line.
Note that $sv=tu$ is the projectivization of both the hyperbolic paraboloid and the one-sheeted hyperboloid, which are the two doubly-ruled surfaces, apart from the plane. Setting any of $s$, $t$, $u$, or $v$ to a non-zero constant gives the equation of a hyperbolic paraboloid. As you mention in the question, setting one of the original variables to a nonzero constant gives the equation of a one-sheeted hyperboloid.
Arranging the coordinates $s$, $t$, $u$, $v$ in the form of a $2\times2$ matrix, we see that the cone is the determinantal variety, $Y_1(2,2)$, defined by
$$
\begin{vmatrix}s & t\\ u & v\end{vmatrix}=0,
$$
which is the condition that the rank of the matrix be at most $1$.
Generalizing, let $Y_k(m,n)$ be the set of $m\times n$ real matrices of rank at most $k$, which is characterized by the vanishing of all $(k+1)\times(k+1)$ minors of the matrix, that is, by a set of homogeneous degree-$(k+1)$ equations. The set $Y_k(m,n)$ is a cone since if $M\in Y_k(m,n)$ then $aM\in Y_k(m,n)$ for any scalar $a$. It is the set of matrices that can be written
$$
v_1w_1^\mathrm{T}+v_2w_2^\mathrm{T}+\ldots+v_kw_k^\mathrm{T},
$$
where $v_j\in\mathbf{R}^m$, $w_j\in\mathbf{R}^n$ for all $1\le j\le k$. For any $k$-dimensional linear subspace $V$ of $\mathbf{R}^m$ and basis $b_1,\ldots,b_k$ of $V$, the set
$$
\left\{b_1w_1^\mathrm{T}+b_2w_2^\mathrm{T}+\ldots+b_kw_k^\mathrm{T}\mid w_1,\ldots,w_k\in\mathbf{R}^n\right\},
$$
which is independent of the choice of basis, is a $kn$-dimensional linear subspace of $\mathbf{R}^{mn}$ that is contained within the cone. Similarly, for any $k$-dimensional subspace $W$ of $\mathbf{R}^n$ and basis $c_1,\ldots,c_k$ of $W$, the set
$$
\left\{v_1c_1^\mathrm{T}+v_2c_2^\mathrm{T}+\ldots+v_kc_k^\mathrm{T}\mid v_1,\ldots,v_k\in\mathbf{R}^m\right\}
$$
is again independent of the choice of basis and is a $km$-dimensional linear subspace of $\mathbf{R}^{mn}$ that is contained within the cone.
Note that the cone itself is an algebraic variety of dimension $k(m+n-k)$. To specify the $k$-dimensional linear subspace $V\subset\mathbf{R}^m$ requires $k(m-k)$ parameters: take as basis vectors the rows of a $k\times m$ matrix $[I\mid M]$, where $I$ is the $k\times k$ identity. (One, of course, cannot always achieve a basis of this form. Instead of columns $1$ through $k$, one may specify some other set of $k$ columns as the pivot columns, with the remaining columns containing the $k(m-k)$ parameters. This amounts to the choice of a particular coordinate chart, and every linear subspace will be covered by at least one such chart.) After specifying $V$, one needs to specify $k$ vectors $w_i\in\mathbf{R}^n$, which requires $kn$ parameters, for a total of $k(m+n-k)$ parameters. Alternatively, specifying the $k$-dimensional subspace $W\in\mathbf{R}^n$ requires $k(n-k)$ parameters; then the $k$ vectors $v_i\in\mathbf{R}^m$ need to be specified, for, again, a total of $k(m+n-k)$ parameters. Observe that $V$ is an element of the Grassmannian $\operatorname{\bf Gr}(k,\mathbf{R}^m)$ and that $W$ is an element of $\operatorname{\bf Gr}(k,\mathbf{R}^n)$.
Define $K=\min(m,n)$. Then $0\le k\le K$. We may understand the determinantal variety $Y_k(m,n)$ as a way of realizing the set of elements of $\mathbf{R}^m\otimes\mathbf{R}^n$ of tensor rank at most $k$. I began thinking about these things while pondering the questions here, here, and here about geometric interpretations of the tensor product, something I still don't feel I fully understand. Nevertheless, thinking about determinantal varieties does give some insight into how $\mathbf{R}^m\otimes\mathbf{R}^n$ is built up from spaces isomorphic to $\mathbf{R}^m$, $(\mathbf{R}^m)^2$, ..., $(\mathbf{R}^m)^K$ and also from spaces isomorphic to $\mathbf{R}^n$, $(\mathbf{R}^n)^2$, ..., $(\mathbf{R}^n)^K$.
The $(kn)$-dimensional and $(km)$-dimensional subspaces of $\mathbf{R}^m\otimes\mathbf{R}^n$ defined above are $V\otimes\mathbf{R}^n$ and $\mathbf{R}^m\otimes W$. Their intersection is $V\otimes W$. Furthermore,
\begin{align}
(V_1\otimes\mathbf{R}^n)\cap(V_2\otimes\mathbf{R}^n)&=(V_1\cap V_2)\otimes\mathbf{R}^n\\
(\mathbf{R}^m\otimes W_1)\cap(\mathbf{R}^m\otimes W_2)&=\mathbf{R}^m\otimes(W_1\cap W_2).
\end{align}
As a consequence, if $V_1$ and $V_2$ intersect only at $0$, then so do the linear spaces $V_1\otimes\mathbf{R}^n$ and $V_2\otimes\mathbf{R}^n$. In $\mathbf{R}^2$, any two distinct one-dimensional linear subspaces intersect only at $0$, and therefore so do your $2$-planes, $V_1\otimes\mathbf{R}^2, V_2\otimes\mathbf{R}^2\subset Y_1(2,2)\subset\mathbf{R}^2\otimes\mathbf{R}^2$ as well as your $2$-planes $\mathbf{R}^2\otimes W_1, \mathbf{R}^2\otimes W_2\subset Y_1(2,2)\subset\mathbf{R}^2\otimes\mathbf{R}^2$. On the other hand $(V\otimes\mathbf{R}^2)\cap(\mathbf{R}^2\otimes W)=V\otimes W$, which is one-dimensional. Similarly, if, for example, $\dim(V_1)=\dim(V_2)=2$ and $\dim(V_1\cap V_2)=1$ then, while $V_1\otimes\mathbf{R}^n$ and $V_2\otimes\mathbf{R}^n$ are subsets of $Y_2(m,n)$, the linear space $(V_1\cap V_2)\otimes\mathbf{R}^n$ is a subset also of $Y_1(m,n)$. Observe the inclusion of determinantal varieties
$$
\{0\}=Y_0(m,n)\subset Y_1(m,n)\subset\ldots\subset Y_K(m,n)=\mathbf{R}^m\otimes\mathbf{R}^n.
$$
If, to take an example, $m=3$ and $n=4$, the dimensions of these varieties are
$$
0,\ 6,\ 10,\ 12;
$$
$Y_1(3,4)$ is ruled by linear spaces of dimensions $3$ and $4$; $Y_2(3,4)$ is ruled by linear spaces of dimensions $6$ and $8$; $Y_3(3,4)=\mathbf{R}^3\otimes\mathbf{R}^4$ is ruled by linear spaces of dimensions $9$ and $12$.