How this term shows up here In this channel's material on writing with AI, thinking tokens appears in the context of how a writer works with an AI model while drafting — the tokens the model produces as it works through a response before or alongside the text you actually see and use. The framing across the Writing with AI chapter treats these model outputs as something a writer observes and steers rather than something to take at face value: the model is a system to engineer, not a magic button, and part of understanding that system is noticing what the model is generating as it “thinks.” Why it matters for writing workflows Writers folding AI into research, ideation, drafting, and editing benefit from understanding that the visible draft is not the only thing a model produces. Paying attention to the model's intermediate output — its thinking tokens — helps you understand why it produced the draft it did, which in turn helps you preserve your own voice and editorial judgment instead of passively accepting an A-minus-quality result. <KeyPoint>Thinking tokens are the tokens a model generates as part of working through a response, distinct from the final draft you read.</KeyPoint> <KeyPoint>In this channel's writing-with-AI material, observing model behavior — including its intermediate output — supports treating AI as a system to engineer rather than a magic button.</KeyPoint> <KeyPoint>Understanding the model's process helps writers keep their own voice and editorial judgment intact.</KeyPoint>