In the evolving landscape of natural language generation, modern pipelines have progressed beyond standalone language models. Today’s advanced text generation systems leverage modular architectures to enhance factuality, coherence, and domain adaptation. One of the most transformative designs is the Retrieval-Augmented Generation (RAG) framework, which integrates retrieval mechanisms into the generation workflow. This chapter dissects the foundational structure of text generation pipelines and explores the emerging trends and architectures in Generative AI that represent the forefront of research and application. These include