Post-training encompasses all training phases after initial pre-training — including SFT, RLHF, DPO, and safety tuning — that shape a base model into a useful, aligned product. These stages transform a raw language model that only predicts next tokens into an assistant that follows instructions, refuses harmful requests, and produces helpful outputs.