I wanted automated help scouting and drafting LinkedIn comments in my own voice. But there'd already been a real incident where unreviewed AI-written comments went out publicly under my name, and LinkedIn's own rules prohibit automated account activity.
I didn't hand the system full autonomy from day one. I required my own explicit approval on every comment before it posts, capped the daily volume low at the start, and built in hard stop rules so any warning or unusual response from the platform halts the whole run immediately until I say to resume. The system never touches my password, never solves a verification challenge, never posts, messages or connects on its own.
The design points straight at the earlier incident. Unreviewed AI comments going out under my name was the exact failure I'm guarding against this time. The real risk is a platform restriction if the pattern looks automated, so the caps started low and the stop rules are absolute, not negotiable.
I proposed the system with graduated trust built in from the start: low daily caps that only rise after three straight weeks where I edited ten percent or fewer of the approved drafts, and my own formal go-ahead is still pending before it runs for real.
After you get burned by something moving too fast without you, don't just slow down once. Build the slowdown into the design so it can't happen again by accident.
Designing the system around a real past mistake instead of pretending it hadn't happened, and keeping myself as the approval gate on my own voice.