At particle colliders, fixed-order predictions are plagued by large logarithms of ratios of disparate scales, which need to be resummed at all orders. Commonly, this is achieved by parton shower programs embedded in Monte Carlo event generators, and for generic observables such parton showers typically resum the leading logarithms (LL) only. The PanScales collaboration set out to design a family of parton showers that also resum the next-to-leading logarithmic terms (NLL), in the limit of a large number of colours, $N_C \to \infty$. The only ingredients missing for claiming full-NLL accuracy were subleading-colour effects, and spin correlations. In this talk I am going to present a series of simple, and efficient, algorithms that allow the PanScales showers to include both sets of effects, and will give examples of their impact in final-state parton showers.
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