Decision trees are commonly used in machine learning for making decisions. A new method called Tree in Tree (TnT) has been developed to improve upon traditional decision trees. TnT creates decision graphs by growing decision trees within other nodes, leading to better classification accuracy and smaller model sizes. TnT is faster and more efficient than regular decision trees, making it a promising alternative for various applications.