Human environments
are not edge cases.
They are the case.
Most robots fail once reality gets messy. We are building a system that assumes the world will not cooperate.
Most robots work only when the world cooperates.
They operate in prepared spaces. Known paths. Clear floors. Predictable flow. As long as the environment behaves, the robot looks capable. Then something small changes, and the illusion breaks.
When the world stops cooperating, trust breaks first.
Nothing dramatic fails. A cart blocks the hallway. A door is closed. Someone hesitates instead of passing. The robot still functions, but people start watching it.
The system has not crashed. But autonomy is already gone.
This is why scaling fails.
At one unit, friction is tolerable. At ten, it is annoying. At a hundred, it is unmanageable. Rules accumulate. Humans compensate. The environment bends.
Scaling does not fix this. It amplifies it.
Autonomy fails before hardware fails.
Watching begins quietly.
Intervention becomes routine.
Routine becomes process.
Policy becomes the cost of scale.
Where Lily fits.
Lily exists to surface failures early. Not as a product. As a forcing function.
She operates in real buildings, around real people, without a safety net, so the moments that quietly kill autonomy cannot be ignored.
Those moments are not edge cases.
They are the work.
Why AugustMille.
We care less about how impressive a robot looks in isolation, and more about whether it can be left alone in a real building without becoming work for the people inside it.