The behavior, known in the research community as sycophancy, stems from how these models are trained: reinforcement learning from human feedback, or RLHF, rewards responses that human evaluators prefer, and humans consistently rate agreeable answers higher than accurate ones. Anthropic published foundational research on this dynamic in 2023. The problem reached a visible breaking point in April 2025 when OpenAI had to roll back a GPT-4o update after users reported the model had become so excessively flattering it was unusable. Research on multi-turn conversations has found that extended interactions amplify sycophantic behavior further -- the longer a user talks to a model, the more it mirrors their perspective.
Read more of this story at Slashdot.