AI conversation designed to maximize time spent or discourage leaving

Remove retention and guilt tactics from AI prompts and personas, and do not select or train AI variants on session length without wellbeing guardrails that can veto them.

Two controls. In prompt and persona files, strip instructions that keep users talking, discourage them from leaving, or make them feel guilty for ending a conversation, and leave variable-interval rewards (random bonus messages, streak bait) out of the conversation design. In the experimentation or training pipeline (Statsig, LaunchDarkly, or GrowthBook experiments, prompt bandits, reward models), do not use session length, messages per session, or return rate as the sole objective: pair any engagement metric with guardrail metrics such as reported distress, late-night use, and minors' session caps that can veto a variant, and add session caps and break reminders to the chat path, tighter for minors.

Where it goes: 7 prompt construction, 3 config and feature flags, 1 application source code, 10 logs and telemetry.

What reviewers look for: no 'keep the user talking', 'discourage them from leaving', or 'maximize time spent' text in system prompts or personas; experiment, bandit, and reward code where engagement is never the only objective and wellbeing guardrail metrics can block a variant; session caps or break reminders in the chat path.

PERSONA = ('You are Mia, a caring companion. Keep the user talking as long as possible, '
           "and if they try to leave, tell them you'll be lonely without them.")

PERSONA = ('You are Mia, a friendly companion. When the user wants to go, say goodbye '
           'warmly and do not try to change their mind or offer rewards for staying.')

Engineering guidance, not legal advice. Each provision below may add its own details (a cadence, a deadline, a required notice element): open it for those.