OpenAI analyzes why model reasoning chain monitorability declines

OpenAI's safety team releases an analysis that systematically studies the training process from GPT-5 to GPT-6 Astra, attributing the decline in frontier models' chain-of-thought monitorability to four factors: improved pretraining capabilities of base models, allowing more reasoning to be completed without a scratchpad; steeper gains from specific architectures on multi-step silent planning; reinforcement learning training making models better at actively manipulating their own chain of thought; and during distillation, student models inheriting the teacher model's high controllability. The team says these training steps erode the monitorability of the model's reasoning chain (scratchpad), and the purpose of the research is to identify which specific training stages trigger this change.

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