ByteByteGo published an interesting article on the commercial and safety risks of exposed AI reasoning traces. It's academic in nature (so consume it with a grain of salt) but ut still has some interesting info. Check out the full article here.

My takeaways:

• When AI models answer hard questions, they generate a full reasoning process that is never displayed, using an encrypted AEAD envelope sent to the client to maintain stateless conversation continuity.
• Because authenticated fields often lack user or session bindings, blocks can suffer from cross-session, cross-user, or cross-model replay, allowing blocks from one context to be accepted in another.
• Encrypted reasoning blocks from strong models can be fed into weaker models in the same family as prior context and transcribed into plaintext, entirely bypassing the original model's refusal training and output filters.
• Because sanitization only acts on plaintext, public reasoning traces frequently leak sensitive data like API keys, passwords, and private tokens that were stripped from the visible chat output.