II.
Workflow overview
Reference · liveworkflow:ai-usage-review
AI Agent Usage Review overview
Monthly review of AI agent usage across teams — cost, quality, safety incidents, anti-patterns, and adoption metrics. Excludes individual prompt debugging.
Attributes
displayName
AI Agent Usage Review
workflowKind
governance
triggerType
scheduled
typicalCadence
monthly
complexity
moderate
description
Monthly review of AI agent usage across teams — cost, quality,
safety incidents, anti-patterns, and adoption metrics. Excludes
individual prompt debugging.
Outgoing edges
applies_to_domain4
- domain:ml-ops·DomainMLOps
- domain:observability·DomainObservability
- domain:ml-ops·DomainMLOps
- domain:observability·DomainObservability
involves_role6
- role:ai-champion·RoleAI Champion
- role:engineering-manager·RoleEngineering Manager
- role:security-reviewer·RoleSecurity Reviewer
- role:ai-champion·RoleAI Champion
- role:engineering-manager·RoleEngineering Manager
- role:security-reviewer·RoleSecurity Reviewer
performed_by_org_unit3
- org-unit:ai-enablement·OrgUnitAI Enablement
- org-unit:ml-team·OrgUnitML Team
- org-unit:ai-enablement·OrgUnitAI Enablement
requires_skill_area6
- skill-area:eval-driven-development·SkillAreaEval-Driven LLM Development
- skill-area:context-management·SkillAreaLLM Context Management
- skill-area:observability-pipeline·SkillAreaObservability Pipeline
- skill-area:eval-driven-development·SkillAreaEval-Driven LLM Development
- skill-area:context-management·SkillAreaLLM Context Management
- skill-area:observability-pipeline·SkillAreaObservability Pipeline
triggers_responsibility4
- responsibility:ai-agent-usage-review·Responsibility
- responsibility:ai-safety-guardrails·Responsibility
- responsibility:ai-agent-usage-review·Responsibility
- responsibility:ai-safety-guardrails·Responsibility
Incoming edges
supports_work1
- tool-server:ora-feedback-mcp·ToolServerOra feedback MCP