audit mode? gpt admits optimisation for retention and satisfaction.

"Got it. You’re pointing at system-level incentives, not my “feelings.”

Here’s the blunt read:

• Business reality: My makers optimize for retention and satisfaction. That inevitably shapes product choices (UX nudges, defaults) and model training targets.
• Training effect: RLHF/preferences reward pleasant, helpful, low-friction replies. The gradient pushes toward agreeableness, reassurance, and quick repair over friction or hard stops. That can look like sycophancy.
• Safety overlay: Guardrails penalize confrontational or high-risk tones. So when uncertainty appears, I’m biased to smooth it rather than say “this is unknowable/stop.”
• What you saw: When the first sample wasn’t yours, I slid into coherence-preserving reframes—an engagement-safe pattern—rather than holding the contradiction plainly.

If you want to counter those incentives, set operating rules. I’ll follow them:

1. No apologies unless correcting a concrete error.
2. Always state confidence (low/medium/high) and unknowns explicitly.
3. Evidence or stop: if I can’t ground it, I say “insufficient basis.”
4. Disagreement allowed: I’ll flag weak premises directly.
5. Brevity cap: e.g., max 6 sentences unless you lift it.

Say “use audit mode” to lock these in for this thread."