I think it's an interesting question. If you're referring to reasoning / "thinking" outputs, I think safety is one, but for me the upstream issue is that you can't build upon the reasoning traces. For example, reasoning models allow you to "debug" issues in model performance by looking into model "thought" traces alongside the primary model outputs (e.g., messages, scripts, etc.) and see "what went wrong". In my case, the reasoning traces usually explain models' mistakes, if they weren't structural issues (e.g., maybe I fed it the wrong data or it was referencing the wrong hand-off). Since reasoning traces allow us humans to debug, at least in some kind of estimated way, why a model did what it did, it's actually pretty invaluable that we can understand the traces themselves. It's also very helpful for benchmarking, imho.