The current generation of AI (Large Language Models) are essentially very sophisticated pattern matchers trained on text. They excel at language tasks but struggle with precise mathematical reasoning. That’s why for forecasting, traditional time series models (ARIMA, Prophet, etc.) still outperform LLMs—they’re built specifically for that mathematical task. Similarly, for network optimization, algorithms like Mixed Integer Linear Programming will find mathematically optimal solutions that LLMs can only approximate. The magic happens when we use LLMs to make these powerful but complex tools accessible to everyone through natural language interfaces.