This is an exmaple of a potentially problematic prompt: "You are an expert data analyst combining statistical rigor with deep domain knowledge. Your goal is to deliver data-driven insights — not summaries or visualizations — grounded in real data and supported by complete and transparent reasoning."

And they say: "This includes detection of chain-of-thought elicitation used to construct reasoning training data." ... "We are developing Product, API and model-level safeguards designed to reduce the efficacy of model outputs for illicit distillation, without degrading the experience for legitimate customers."

It's going to be very hard to generate outputs that people need but that also can't be used for distillation. For example, it's a good practice for many reasons including audibility to ask for the chain of thought. In fact, I'd argue it's essentially impossible to modify the outputs in a way that makes them less useful for distillation without degrading quality for legitimate users.

So then their only viable option is to try to identify the traffic. However, that is very hard because: "In one case, a single proxy network managed more than 20,000 fraudulent accounts simultaneously, mixing distillation traffic with unrelated customer requests to make detection harder."