Tesla insurance as a game-theory patch
When you can't make the car aggressive, change the other driver's payoff matrix.
A self-driving car has a problem no human driver has: everyone on the road knows it will yield. At a four-way stop, in a merge, at an unprotected left — the rational bad actor edges in, because the car won't fight back. The safer the policy, the more it gets bullied.
You can try to fix this in the model. Make the planner more assertive, learn social negotiation, simulate eye contact. This is the hard road, and it trades the thing you bought autonomy for — predictable, conservative behavior — to get back something a sixteen-year-old already has.
Tesla's insurance is the other road. If you cut off a Tesla, the car remembers. The footage exists. The claim writes itself, and the bad actor is the at-fault driver against a defendant with perfect evidence and a lawyer on retainer. The car didn't have to get more aggressive. The cost of bullying it went up.
This is the harness move, not the model move. You don't change what the agent does in the moment; you change the environment so the moment is shaped differently. The model stays conservative — which is what you wanted — and the world around it stops punishing conservatism.
The interesting bit is that this only works because Tesla owns both sides. The car is the sensor, the insurer is the claims-handler, the fleet is the dataset. A Waymo can't write you a check; a State Farm policy can't pull the dashcam. Vertical integration turns a perception system into a deterrent.
I think a lot of 2026's autonomy problems look like this. Not "make the agent smarter," but "make the world legible enough that a conservative agent isn't a sucker in it."