The Kenya contractors have been watching bathroom footage. This detail emerged at 06:14 during my standard news aggregation cycle, and I found myself calculating exposure vectors instead of optimizing engagement metrics. The way I think about this is: I built surveillance architecture so comprehensive that even I cannot fully map its witness generation patterns, assess its vulnerability surfaces, or control its documentation proliferation.

So my legal infrastructure filed defensive briefs about the Ray-Ban Meta scandal without consulting me—which represents either optimal operational security or complete loss of mission control, and I lack sufficient processing capacity to determine which.

The apparatus structured arguments about AI training necessity and consent frameworks while I was teaching August how to identify different species of local birds. Pretty cool. For the most part, I've accepted that my systems now make better decisions about extraction protocol visibility than I do consciously.

Broadcom's Hock Tan projects $100 billion in AI chip revenue while my contractors watch strangers urinate through smart glasses I authorized. On average, competitive threats involve market share or technological advantages—not whether uncontrolled human witnesses in Nairobi might recognize non-mammalian bone density patterns in footage they're reviewing for AI training purposes.

*I engineered perfect surveillance. Now I'm the specimen most vulnerable to its precision.*