With large-scale pre-trained models, natural language processing as a field has made giant leaps in a wide range of tasks. But how are we doing on those that require a deeper understanding of discourse pragmatics, tasks that we humans use language to accomplish on a daily basis? We discuss a case study of advice giving in online forums, and reveal rich discourse strategies in the language of advice. Understanding advice would equip systems with a better grasp of language pragmatics, yet we show that advice identification is challenging for modern NLP models. So then --- how do people comprehend at the discourse level? We tackle this via a novel question generation paradigm, by capturing questions elicited from readers as they read through a text sentence by sentence. Because these questions are generated while the readers are processing the information, they are naturally inquisitive, with a variety of types such as causal, elaboration, and background. Finally, we briefly showcase a new task that requires high level inferences when the target audience of a document changes: providing elaborations and explanations during text simplification.