| name | afrexai-agent-manager |
| description | AI Agent Manager Playbook |
AI Agent Manager Playbook
Your company deployed AI agents. Now what? This skill turns you into the person who actually makes them productive — the Agent Manager.
What This Does
Gives you a complete framework for managing autonomous AI agents across your organization. Role definition, performance metrics, escalation protocols, governance, and team structure.
The Agent Manager Role
Based on Harvard Business Review's Feb 2026 research: companies deploying AI agents without dedicated management see 60%+ failure rates. The ones that assign Agent Managers see 3-4x better outcomes.
Core Responsibilities
- Agent Portfolio Management — Which agents run, which get retired, which get built next
- Performance Monitoring — Task completion rates, accuracy, cost per action, escalation frequency
- Escalation Design — When agents hand off to humans, how, and what context they pass
- Governance & Compliance — Ensuring agents operate within policy, legal, and ethical boundaries
- ROI Tracking — Proving agent value in hours saved, revenue generated, errors prevented
Agent Performance Scorecard
Rate each agent monthly (1-5 scale):
| Dimension | What to Measure | Target |
|---|
| Reliability | Task completion without errors | >95% |
| Speed | Avg time per task vs human baseline | <30% of human time |
| Cost Efficiency | Cost per action vs manual equivalent | <20% of manual cost |
| Escalation Rate | % tasks requiring human intervention |