The context sweet spot | Context Engineering - courses.vizuara.ai

Too many tokens, or too few? Both are failure modes. Too few → the model starts hallucinating. It does not have enough instruction to do what you actually want. Too many → context rot. Quality degrades. So where is the sweet spot? For a model with a 200K token window, somewhere between 50K and 100K is a reasonable target. And there is a second reason for leaving that headroom, which people forget: the model's output also has to fit in the context. As it generates, it fills the window. If you have consumed 190K of a 200K window, there is nowhere for the answer to go. Fill 50–100K, leave the rest free for generation. That balance works well. One honest caveat. This is not a physics-derived curve. It is purely empirical. So if you extrapolate to a 2 million token window and ask whether the shape holds — nobody can tell you without running the experiments. Context Engineering - courses.vizuara.ai