A knowledge cutoff is the stated time boundary for information included in an AI model's training. It describes the age of its built-in knowledge, not a guarantee that the model knows every fact published before that date. Training coverage is incomplete, and remembered information can be wrong.
Live retrieval is different: an assistant may search current sources or read documents supplied in its context to answer questions about events after the cutoff. Accessing those sources does not, by itself, retrain the model.
Practical relevance
Suppose a company changes its product name after a model's cutoff. An answer based only on training may use the old name. An answer that retrieves the company's updated product page may use the new one, provided that page is accessible and the system uses it correctly.
Keep important facts current on accessible pages and distinguish retrieved answers from answers based on training when investigating outdated brand information. A recent cutoff alone does not establish that an answer is current.