Ownership
Put your name on what you produce — and mean it.
I will put my name on what I produce — and mean it.
You understood it.
You verified it.
You decided it.
You documented it.
You measured it against the standard it demands.
Now you own it.
Ownership means your name is on the work and you stand behind it. Not “the AI wrote it.” Not “the team decided.” Not “the process produced it.” You. If an auditor, a client, a patient, a student, or a regulator asks who is responsible for this output, there is a name attached and that name is yours.
Ownership is not attribution. Attribution says who touched it last. Ownership says who stands behind it. AI-assisted work makes attribution easy and ownership hard. The question ownership answers is not “who produced this?” but “who is responsible for this?”
THE LINE
The line between attribution and ownership is the line between record-keeping and accountability. Attribution can be automated — a system can stamp your name on every output you touched. Ownership cannot be automated. It requires that you governed the work, not just that you were present for it. When you put your name on work you did not govern, you have not taken ownership. You have taken credit. The compact requires ownership.
FAILURE MODE
Failure mode here is the diffusion of responsibility. Work that everyone contributed to and no one owns. Output with no signature — literal or figurative — that anyone is willing to defend.
→ ownership feeds continuity
The work must be understood by the person responsible for it, traceable by anyone who inherits it, and governed proportionally to its consequences.
Anything can produce. Only I can care.
Seven principles. Two oaths. One compact.