Workflow-layer Sovereignty Glossary
Workflow-layer Sovereignty is the realistic near-term form of AI sovereignty.
It names the distinction between controlling the workflow and controlling the frontier model itself. A local operator can keep memory, notes, files, tools, routine workloads, student data, private drafts, and model-routing rules under local control while still depending on frontier providers for the hardest reasoning, synthesis, architecture, and review.
This is why the clean correction matters: local sovereignty mitigates cost, privacy, continuity, and dependency risk at the workflow layer. It does not by itself solve frontier-model access.
That is not failure. It is the current map. The work is to expand the workflow layer upward as local and open-weight models improve.