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Larger context windows degrade AI agent accuracy by diluting attention. The lost-in-the-middle effect buries key facts, while distractors actively pull models toward wrong answers. A tight, well-ordered 8K context outperforms a sloppy 200K one. Engineers should treat context as a token budget, not free storage.
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