[guided]We now manufacture a linear functional that separates $g_1$ from each $g_i$ ($i \ge 2$). The Hahn-Banach theorem is the right tool, but in the finite-dimensional setting we can state and verify the conclusion directly.
**Hahn-Banach (finite-dimensional, algebraic form):** Let $W$ be a finite-dimensional vector space, and let $u, v \in W$ be linearly independent. Then there exists a linear functional $l \in W^*$ with $l(u) = 1$ and $l(v) = 0$.
**Proof (within this guided block — for completeness):** Since $\{u, v\}$ is linearly independent, extend it to a basis $\{u, v, e_3, \dots, e_d\}$ of $W$. Define $l$ by setting $l(u) = 1$, $l(v) = 0$, and $l(e_k) = 0$ for $k = 3, \dots, d$, then extend by linearity. This is well-defined because the values are specified on a basis, and it produces an element of $W^*$.
**Application to our setting.** Apply this to $W = T_{\le N}(V)$, $u = g_1$, $v = g_i$ — both are in $T_{\le N}(V)$, and they are linearly independent by Step 2. So we obtain $l_i \in T_{\le N}(V)^*$ with $l_i(g_1) = 1$ and $l_i(g_i) = 0$.
**Lifting to $T((V))^*$:** The functional $l_i$ is defined on the truncation. To extend to $T((V))$, simply compose with the truncation projection:
\begin{align*}
f_i: T((V)) &\to \mathbb{R} \\
h &\mapsto l_i(\pi_{\le N}(h)).
\end{align*}
This is linear (composition of linear maps), and $f_i \in T((V))^*$.
**Verification:**
\begin{align*}
f_i(h_1) = l_i(\pi_{\le N}(h_1)) = l_i(g_1) = 1, \qquad f_i(h_i) = l_i(\pi_{\le N}(h_i)) = l_i(g_i) = 0.
\end{align*}
**What we do not control:** $f_i(h_j)$ for $j \notin \{1, i\}$ is not constrained by the construction. So the family $\{f_2, \dots, f_n\}$ separates $h_1$ from each $h_i$ pairwise, but no single $f_i$ separates $h_1$ from all the others simultaneously. To remedy this, we will combine them via the **shuffle product** in the next step.[/guided]