We study fully dynamic $(Δ+1)$-coloring against an adaptive adversary. Behnezhad, Rajaraman, and Wasim (SODA 2025) gave the first algorithm with $\tilde O(n^{8/9})$ amortized update time, later improved to $\tilde O(n^{2/3})$ by Flin and Halldórsson (ICALP 2025). We give a fully dynamic $(Δ+1)$-coloring algorithm with $\tilde O(\sqrt n)$ \textbf{worst-case} update time. Unlike previous algorithms, it avoids sparse-dense decompositions and relies only on elementary data structures, resulting in a short self-contained algorithm and analysis. Moreover, it avoids global recoloring, resulting in a worst-case recourse of $3$.

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