This paper describes the Abjad AI team’s sub- mission to the AraSeg 2026 Shared Task on Arabic sentence segmentation, covering the two punctuated tracks: Paragraph-Aware (PA) and No-Paragraph (NP). Rather than substituting a larger encoder, we retain the CAMeLBERT- MSA reference system and ask how much head- room remains in the task’s formulation. Our system combines four components: boundary labels aligned to each word’s final sub-token, an auxiliary classification head on the penul- timate encoder layer trained jointly with the final-layer head, class-weighted cross-entropy for boundary sparsity, and overlap-averaged decoding that scores documents of arbitrary length without truncation. We ablate each com- ponent in isolation, including the two that the reference system already uses. Our solution achieves F1 scores of 91.7 and 89.7 in the blind tests of the PA and NP sub-tasks, respectively.