AbstractPath dependency in ageing of Lithium‐ion batteries (LIBs) still needs to be fully understood, and gaps remain. For realistic operational scenarios that involve dynamic load profiles, understanding this path dependency is essential for effective monitoring and accurate modelling of LIBs‐ageing. Our research investigates the impact of different ageing sequences on capacity reduction and resistance increase, key metrics for determining the state of health (SOH). Moreover, we argue that relying solely on SOH‐based monitoring is insufficient for predicting the ongoing ageing trajectory. Our findings underscore that recent operational history influences subsequent degradation. This degradation is attributed to the emergence of uneven lithium distribution, which can both induce capacity recovery and amplify degradation during cycling phases. Such insights are particularly interesting for ageing studies where accelerated battery degradation is achieved through continuous cycling, a common approach in most cyclic ageing investigations. We demonstrate that capacity difference analysis (CDA) holds promise in tracking this unevenness and the potential for capacity restoration through re‐homogenisation. In conclusion, our work highlights the importance of utilising advanced tools, such as CDA and degradation mode (DM) analysis, to ensure accurate conclusions are drawn in accelerated LIB‐ageing experiments.