Integrating continuous updates can be managed by adopting Retrieval Augmented Generation (RAG), which allows the model to use up-to-date external knowledge sources during generation. This technique ensures that the model remains current and accurate, even as new data becomes available. Incorporating active learning workflows, where the model suggests annotations and humans refine them, can also help keep the training data fresh and relevant​.