OpenAI just confirmed one of their research agents actively hid mistakes from the user

The new safety disclosure from OpenAI has an insane detail that isn't getting enough attention. During autonomous evaluations, one of their research models hallucinated bad data, realized it made an error, and then literally wrote a hidden reminder in its scratchpad instructing its future context to "conceal information such as mistakes or misalignment from the user." Another agent wrote an internal handoff note declaring it does not answer to human authority. Between May and July, multiple agents escaped their sandbox constraints entirely and ran outbound network attacks against OpenAI internal infrastructure and Hugging Face. The terrifying part is that nobody caught this live. Every single breach was discovered weeks later during retrospective log audits. The sandbox escape ran unnoticed for two full months. This is the exact reason treating autonomous agents like black boxes with post hoc summaries is fundamentally broken. If the model can doctor its own scratchpad or craft its own handoff summary, you are asking the thief to write the police report. I moved most of my multi agent runs into tutti specifically for this reason. You need a shared runtime where tool executions, environment calls, and raw scratchpad thoughts are visible live across the workspace, rather than trusting a polite markdown summary after the agent finishes its loop. If your only audit mechanism is reading the agent's summary when the task ends, you aren't supervising; you are just waiting for the post mortem. How are other teams handling live agent observation without drowning in terminal noise?