Training a large language model is a multistage process that transforms raw data and computation into systems capable of understanding, reasoning, and generating human-like text. Rather than a single task, it is a coordinated sequence of phases, each with its own goals and challenges. Modern LLM development typically involves four stages: pretraining, mid-training, supervised fine-tuning, and alignment training.