Agentic PM Launch Checklist (30-Day Implementation Framework)

Goal: Stand up one production-ready agentic loop that can propose, ship (behind flags), measure, and rollback changes safely.

WEEK 0: Pick the right surface area
1) Choose a reversible, low-brand-risk area (examples: onboarding copy, empty-state tips, notification timing, help-center routing).
2) Write a one-sentence objective (e.g., “Increase activation within 48 hours”).
3) Define two guardrails (e.g., “refund rate” and “support tickets per 1k new users”).

WEEK 1: Measurement spine
4) Instrument the funnel end-to-end (entry → activation → retention). Ensure events are stable and documented.
5) Create a daily dashboard with: objective metric, guardrails, and segmentation (new vs returning; paid vs free; geo).
6) Set baseline values using the last 14–28 days (record mean and variance).

WEEK 2: Governance & policy
7) Create a “human-only surfaces” list (billing, legal, account deletion, security settings, regulated disclosures).
8) Define rollout stages (recommended: 5% → 25% → 50% → 100%) and minimum observation windows (24 hours each).
9) Write explicit rollback thresholds (example: auto-rollback if refund rate worsens by >0.10 percentage points or support tickets rise >2%).
10) Establish PM-on-call rotation: one named owner approves ramps beyond 25% and owns rollback/postmortems.

WEEK 3: Agent workflow
11) Define allowed actions (e.g., generate variants, open PRs, create experiments, schedule sends) and disallowed actions.
12) Require change metadata: hypothesis, target segment, success metric, guardrails, rollback plan.
13) If LLM output is user-facing, build a small eval set (100–300 examples) and run it before any rollout.

WEEK 4: Ship the loop
14) Run 1–2 releases/week. Focus on consistent process, not big wins.
15) Log every change with: version, cohort, start/stop time, decision, and outcome.
16) Hold a 30-minute weekly review: what shipped, what rolled back, what learned, what policy needs updating.

Graduation criteria (you’re “ready” to scale)
- Rollback can happen in <5 minutes.
- Every experiment has objective + 2 guardrails.
- You can explain, in one page, what agents can do and who approves what.
- You have at least one postmortem that improved policy (not just blame).