210 Problems We Have Learned to Call Normal

Three connected system directions can remove burdens that modern AI, machines, instruments, electronics, and infrastructure have learned to accept: capability-native agency, live reconfigurable physical computation, and minimal-apparatus physical intelligence.

I plan to organize future subsidiaries around these three directions. They do not exist as companies yet; the work already defines the technical and commercial ground they can pursue.

One customer can need all three directions at once. A robotics team may need structurally bounded machine authority, spatial computation that follows the body, and direct physical interfaces that strip away converter stacks. The same cross-layer opportunity reaches instruments, satellites, industrial systems, adaptive edge machines, and fabrication.

These 210 problem statements locate the leverage: build mechanisms that own authority, reorganize locally, and compute closer to physical cause and effect.

1. Capability-native agency: Give machines authority they can possess

The first planned subsidiary will build capability-native systems that give AI agents and autonomous machines structurally bounded authority, with delegation, ownership, revocation, and possible effects visible in the mechanism itself.

Segment 1A: Give enterprise AI agents consequence-shaped authority

Segment 1B: Make machine delegation narrow, causal, and revocable

Segment 1C: Give autonomous machines local ownership of physical consequences

Segment 1D: Build computing infrastructure around capability and ownership

2. Live reconfigurable physical computation: Let structure change while the machine runs

The second planned subsidiary will build spatial, locally owned computation that can reorganize live across instruments, robots, satellites, industrial systems, adaptive edge machines, and eventually programmable matter.

Segment 2A: Let scientific instruments reshape their live causal structure

Segment 2B: Make industrial machines compute where physical work happens

Segment 2C: Let remote systems reorganize after deployment

Segment 2D: Give edge machines live, local computational structure

Segment 2E: Make computation belong to programmable matter

3. Minimal-apparatus physical intelligence: Move intelligence into the mechanism

The third planned subsidiary will build near-sensor computation, direct physical interfaces, tiny local learning, and unusual active devices that remove converter stacks, centralized machinery, and inaccessible fabrication where those layers create the real burden.

Segment 3A: Let sensors decide where phenomena occur

Segment 3B: Replace converter stacks with direct computational relationships

Segment 3C: Give tiny machines local learning they can own

Segment 3D: Make active computation locally fabricable