We investigate how conversational context shapes sycophancy in large language models, testing 80, 433 trials across six models (4B–72B parameters) spanning four architecture families. Our central finding is the behavioral ratchet: the pattern of conversational history—not its length—is the primary driver of in-context sycophancy. Agreement-pattern filler roughly doubles sycophancy compared to correction-pattern filler (p < 10⁻¹⁴ in every model tested). This effect is universal across all model sizes and architectures. Code, data, and full analysis available at: github. com/thtskaran/contextwindowᵣesearch
Karan Prasad (Sun,) studied this question.