The harness joins the trust boundary
Sandboxing, recovery, tool semantics, and state handling are treated as part of the governed system.
Where should policy, tools, permissions, memory, and model routing live?
A privacy-conscious control plane for governing how people and agents use models, context, tools, and organizational authority.
Working thesis
AI capabilities should be governed from a coherent control layer where policy, identity, tools, context, models, audit, and organizational authority can be reasoned about together.
Project record
Sample chronology from the prototype, awaiting editorial verification.
Sandboxing, recovery, tool semantics, and state handling are treated as part of the governed system.
Policy, routing, context, and audit are separated from individual AI applications.
Writing
Longer arguments and field notes produced by the work.
System sketch
Every request crosses the same authority boundary before models, tools, or retained context become available.
Rendering diagram. The source is available below.
flowchart TD
accTitle: One governed capability path
accDescr: Every request crosses the same authority boundary before models, tools, or retained context become available.
n0["Identity + intent: Who is asking and what they need"]
n1["Policy decision: Permissions, purpose, and risk"]
n2["Capability route: Model, tool, and context selection"]
n3["Audit record: Decision, execution, and recovery evidence"]
n0 --> n1
n1 --> n2
n2 --> n3Constellation
This dossier remains focused on Kontrolr. Its dependencies and effects continue through the wider Factor-E constellation.