Let $(\Omega,\mathcal F, P)$ be a probability space and let $L_1$ be the collection of all integrable (finite expectation) real-valued random variables defined on this space. Assume that for $X_k\in L_1,k=1,2,\dots n$ it holds that $\mathbb E \lvert \sum_k a_k^m X_k \rvert \leq 1,\forall m$, where $(a_1^m,a_2^m,\dots,a_n^m)=:a_m$ is a sequence in $\mathbb R^n$ such that $\max_k \lvert a_k^m \rvert\to \infty, m \to \infty.$ Prove that $\exists i$ and real numbers $b_k$ such that $\mathbb E \lvert X_i - \sum_{k\neq i} b_k X_k \rvert=0$.
Note that this is related to homework.
I tried a number of things but can't pin down where I fail. I tried using contradiction and Fatou to show that there is a set of non zero measure where the $\lim \inf$ is infinite but did not manage to convince myself. I also tried arguing by standardizing all coefficients by the $\max$, leading to $\mathbb E \lvert \sum_k \alpha_k^m X_k \rvert\to0$ where at least one $\alpha_k^m \in \{ -1,1\},\forall m$ but could not convince myself that this is helpful. From here I also tried using the fact that there is a subsequence converging almost surely to zero.
In short, I am at a loss where to even start. I feel like I've tried all the standard tools from a graduate level probability course but am not making progress. I am looking for a pointer in the right direction. The overall goal is to show that the span of finite number of integrable r.v.s is a closed set, but this is a step on the way.