Agent Operating System (AOS) — 30-Day Leadership Checklist

Purpose: Launch one AI agent workflow that delivers measurable value without creating security, compliance, or reliability debt.

Before Day 1: Pick the right workflow (30 minutes)
- Choose a workflow with clear inputs/outputs (e.g., ticket triage, dependency updates, incident summaries).
- Confirm you have a baseline from the last 30 days (volume, cycle time, defect rate, escalation rate, CSAT if applicable).
- Decide the initial risk tier (Tier 0 read-only is ideal).

Days 1–5: Ownership + guardrails
1) Assign roles
- Agent Owner (business outcome + budget)
- Model Steward (access, audit, vendor/model changes)
- Last-mile Reviewer (for any Tier 2+ actions)

2) Define success + guardrails
- North star metric (ONE): e.g., % tasks completed successfully.
- Two guardrails: e.g., rework rate, policy violations per 1,000 tasks, incident correlation.
- Set stop conditions: what triggers immediate rollback (e.g., any PII leak; >2 customer complaints/day).

Days 6–12: Access + governance
- Create a dedicated agent identity (no shared human tokens).
- Enforce least privilege (tool allowlist; read-only wherever possible).
- Add time-bounded credentials for sensitive actions.
- Turn on logging with retention (e.g., 90 days) and define who can access logs.
- Define risk-tier rules: which tasks require human approval vs post-hoc audit.

Days 13–20: Evals + reliability
- Build a regression set of 50–200 real examples (edge cases included).
- Track: task success %, latency p95, top failure reasons, reviewer minutes/task.
- Add an automated evaluation gate for any prompt/model/tool change.
- Add monitoring alerts: spend variance (e.g., >15% week-over-week), error spikes, policy triggers.

Days 21–30: Rollout + operating cadence
- Run a controlled pilot (e.g., 5–10% traffic) and compare to baseline weekly.
- Hold a weekly 30-minute “agent review” during pilot:
  - Volume and success rate
  - Quality outcomes (rework, escalations, customer feedback)
  - Cost per successful task
  - Top incidents and corrective actions
- Decide scale/hold/rollback using pre-defined thresholds.
- Document the workflow policy (thresholds, escalation topics, approval requirements).

Exit criteria (ready to scale)
- Stable success rate at or above baseline quality.
- Guardrails are within bounds for 2 consecutive weeks.
- Clear owner, documented policy, and a monthly review scheduled.
- Audit logs and access controls verified by the Model Steward.

Common failure modes to avoid
- “Everyone owns it” (no Agent Owner).
- Measuring tokens instead of outcomes.
- Adding autonomy before evaluation gates exist.
- Giving agents broad production access early.

If you can’t measure it, you can’t delegate it—especially to software.