[guided]The goal is to upgrade one solvable equation,
\begin{align*}
(\lambda_0 I-A)u=g,
\end{align*}
to solvability of
\begin{align*}
(\lambda I-A)u=g
\end{align*}
for every positive $\lambda$. We encode the set of good parameters by
\begin{align*}
S=\{\lambda>0:\operatorname{Range}(\lambda I-A)=X\}.
\end{align*}
The assumption says $\lambda_0\in S$, so this set is nonempty.
We first prove openness. Fix $\mu\in S$. Since $\mu I-A$ is onto and injective, its inverse is the bounded operator
\begin{align*}
R_\mu:X\to D(A)\subset X,\qquad R_\mu g=(\mu I-A)^{-1}g.
\end{align*}
Dissipativity gives the bound
\begin{align*}
\|R_\mu\|_{\mathcal{L}(X)}\leq \frac{1}{\mu}.
\end{align*}
For any $u\in D(A)$, we factor $\lambda I-A$ through $\mu I-A$:
\begin{align*}
(\lambda I-A)u=(\mu I-A)u+(\lambda-\mu)u.
\end{align*}
Because $u=R_\mu(\mu I-A)u$, this becomes
\begin{align*}
(\lambda I-A)u=(I+(\lambda-\mu)R_\mu)(\mu I-A)u.
\end{align*}
Thus solving $(\lambda I-A)u=g$ is equivalent to first solving
\begin{align*}
(I+(\lambda-\mu)R_\mu)h=g
\end{align*}
in $X$ and then solving $(\mu I-A)u=h$. The second equation is solvable because $\mu\in S$. The first equation is solvable whenever the bounded perturbation $(\lambda-\mu)R_\mu$ has operator norm less than $1$. Indeed,
\begin{align*}
\|(\lambda-\mu)R_\mu\|_{\mathcal{L}(X)}\leq \frac{|\lambda-\mu|}{\mu}.
\end{align*}
Therefore, if $|\lambda-\mu|<\mu$, the Neumann series theorem applies to $I+(\lambda-\mu)R_\mu$, and this operator is invertible on $X$. Hence every $\lambda$ sufficiently close to $\mu$ belongs to $S$. This proves that $S$ is open in $(0,\infty)$.
We next prove closedness. Let $(\lambda_n)_{n=1}^{\infty}$ be a sequence in $S$ converging to some $\lambda>0$. Fix $g\in X$ and define
\begin{align*}
u_n=R(\lambda_n,A)g.
\end{align*}
We must show that the equation $(\lambda I-A)u=g$ has a solution. The natural candidate is the limit of the $u_n$, so we prove that $(u_n)$ is Cauchy. Since
\begin{align*}
(\lambda_n I-A)u_n=g
\end{align*}
and
\begin{align*}
(\lambda_m I-A)u_m=g,
\end{align*}
subtracting the two identities and rewriting relative to $\lambda_n I-A$ gives
\begin{align*}
(\lambda_n I-A)(u_n-u_m)=(\lambda_m-\lambda_n)u_m.
\end{align*}
Because $\lambda_n\in S$, the inverse $R(\lambda_n,A)$ exists and has norm at most $1/\lambda_n$. Applying it gives
\begin{align*}
\|u_n-u_m\|_X\leq \frac{|\lambda_m-\lambda_n|}{\lambda_n}\|u_m\|_X.
\end{align*}
Using the resolvent estimate again, now for $u_m=R(\lambda_m,A)g$, gives
\begin{align*}
\|u_m\|_X\leq \frac{1}{\lambda_m}\|g\|_X.
\end{align*}
Thus
\begin{align*}
\|u_n-u_m\|_X\leq \frac{|\lambda_m-\lambda_n|}{\lambda_n\lambda_m}\|g\|_X.
\end{align*}
Since $\lambda_n\to\lambda>0$, the denominators stay bounded away from $0$, while $|\lambda_m-\lambda_n|\to 0$ as $m,n\to\infty$. Hence $(u_n)$ is Cauchy and converges to some $u\in X$.
Now we use closedness of $A$, which was proved in the previous step. From the equation defining $u_n$,
\begin{align*}
Au_n=\lambda_n u_n-g.
\end{align*}
Since $\lambda_n\to\lambda$ and $u_n\to u$, the right-hand side converges to $\lambda u-g$. Therefore $u_n\to u$ and $Au_n\to \lambda u-g$. Closedness of $A$ implies $u\in D(A)$ and
\begin{align*}
Au=\lambda u-g.
\end{align*}
Equivalently,
\begin{align*}
(\lambda I-A)u=g.
\end{align*}
Because $g\in X$ was arbitrary, $\lambda I-A$ is onto, so $\lambda\in S$. Thus $S$ is closed in $(0,\infty)$.
We have shown that $S$ is nonempty, open, and closed in the connected interval $(0,\infty)$. Therefore
\begin{align*}
S=(0,\infty).
\end{align*}
This is the step where the single range hypothesis at $\lambda_0$ becomes the full positive resolvent condition needed for the generation theorem.[/guided]