To design a simple text classification system, I would first gather a labeled dataset containing text samples and their corresponding categories. Next, I would preprocess the text by tokenizing, removing stop words, and applying techniques like stemming or lemmatization. Then, I would use a machine learning model, such as a Naive Bayes classifier, to train the model on this data and finally evaluate the model’s performance using metrics like accuracy or F1 score.