Teach the business with the Learning Inbox

Open /admin/learning to review what the business wants to remember. A learning is a reusable correction with a type, scope, confidence, and source: for example, proposals should never lead with AI capabilities, or customers are called members, never users.

Review a proposal

1. Open the Learning Inbox and read the rule, its rationale, and its confidence.
2. Check conflicts and affected workers. A proposal that contradicts an approved policy needs scrutiny, not speed.
3. Choose an outcome. Send to approvals routes it through the normal approval queue; This conversation keeps it local to the current chat; Reject or Ignore ends it with a recorded receipt. Nothing becomes shared truth without approval.
4. After approval, the learning persists as shared policy with its authority tier and provenance. Revisit it any time; superseded entries link forward to their replacement.

Conversation-derived content always starts at the lowest authority tier. Official policies outrank approved learnings, which outrank working notes. Retrieval shows the model what to believe, so a casual chat message can never silently override an approved rule.

Propose from everyday work

Use Propose learning for anything you find yourself correcting twice: positioning, workflow preferences, offerings, messaging, or process rules. Give it a confidence and the workers it affects. The assistant can also propose learnings conversationally through the same governed path; those proposals wait in the inbox like any other.

Approved learnings appear in agent context with their authority, so the next draft, brief, or proposal starts from what the business already decided.