Give the model a token budget and watch six sources of context compete for it.
A chat answer is built from several sources at once: the system instructions, what the assistant remembers about you, documents it looked up, live tool readings, the conversation so far, and your actual question. Together they are usually bigger than the space the model has to read them in.
Type a number and that becomes the size of the window. The service works out how much each source gets, shortens what can be shortened, drops what will not fit, and prints a receipt explaining every decision. Type a question after the number and the documents are re-ranked against it, so the sentences that survive are the ones about your question.
Underneath the receipt is the same request done the usual way, by gluing every source together and cutting the end off when it is too long. That version regularly throws away the question itself, because the question happens to be at the end of the string.