Why this work needs a system boundary
Shared AI work is useful only when authority, data, and consequences remain controlled.
01Agents with credentials you can't scope
Production agents hold broad, long-lived credentials. Your policy says least-privilege; the infrastructure offers all-or-nothing.
02Audit you have to assemble
Answering an incident or an examiner means correlating framework traces, tool logs, identity events, and model-provider logs by hand. The answer takes hours; the question is urgent.
03Maintenance off the record
SSH sessions, console clicks, tribal knowledge — how the stack is kept alive never shows up in the evidence. You find out what was changed, and by whom, during the incident it caused.
One shared workspace, not scattered agent threads
The collaboration and control plane around every participant, model, tool, and action.
01IdentityNo actor without identity
Least-privilege starts with knowing who's acting. Every agent is a named principal with a verifiable identity, by construction — 'who is this agent' has one answer.
02CredentialsNo access without a scoped grant
Long-lived credentials disappear. Every access is scoped, time-bound, consented where required, and audited — least-privilege as the only available mode.
03RuntimeNothing leaves the perimeter
Models, prompts, and data execute inside your walls. The egress finding never opens, and there's no vendor chain to review one contract at a time.
04AuditNo action unaccounted for
Every operation is a principal acting within a scope through one governed gateway — append-only, chained, exportable to your SIEM and GRC tooling. The control isn't asserted; it's recorded.
05OperatorsMaintenance as evidence
Patches, rotations, and recoveries are performed by the stack's own operators as principals in scopes — signed, on the same ledger you read. Humans keep three jobs: declare intent, sign approvals, hold the kill-switch.
