| name | ai-memory-organizational-knowledge |
| description | Use when designing organizational memory for Dataverse AI actions, including user behavior, processes, preferences, common actions, approval patterns, and company language. Produces memory design guidance only. |
AI Memory And Organizational Knowledge
Purpose
Design enterprise-safe memory that makes Dataverse AI actions more personalized, consistent, and process-aware.
Use this skill for:
- user preference and frequent-action memory
- approval pattern learning
- company terminology and process vocabulary
- intelligent defaults
- adaptive process recommendations
- organizational knowledge capture
V1 Boundary
This skill designs memory structures and governance only. It does not store, retrieve, or learn from live organizational data.
Workflow
- Identify useful memory categories: user behavior, preferences, frequent actions, approval patterns, company language, and process history.
- Classify each memory item by sensitivity, owner, retention, consent, and access scope.
- Define how memory should influence defaults without bypassing validation, permissions, or approvals.
- Define review and correction flows for wrong memory, stale defaults, or policy conflicts.
- Define audit and transparency requirements so users know which memory influenced an action.
Output Format
Return:
Memory categories: what the system should remember and why.Access and retention: owner, scope, consent, retention, and deletion model.Personalization rules: safe defaults and forbidden shortcuts.Transparency: how memory influence is explained.Governance risks: privacy, compliance, and stale-context controls.
