Text generation is the task of automatically producing human-like text given a prompt or context. Modern text generation uses large language models that predict the most likely next token iteratively. Applications include email drafting, content creation, code writing, summarization, translation, and chatbot responses. Quality depends heavily on prompt design, model choice, and parameters like temperature and top-p sampling.