Why AI Models Forget Mid-Conversation: Context Windows and Tokens Explained

AI applications are constrained by a concept called the context window, which limits how much text a model can process at any one time. Rather than storing memory like humans, large language models work with sequences of tokens — small sub-word units produced by a tokenizer before text ever reaches the model. A common misconception is that one word equals one token, but complex words, code, URLs, and punctuation can each consume multiple tokens. This means that as a conversation grows longer, earlier content may effectively fall outside the model's active context, causing it to appear forgetful. Understanding token usage and context window limits is considered essential for developers building reliable AI-powered applications.