# Product Launch Ops

> Run disciplined go-to-market experiments that compound insight, de-risk launches, and accelerate product-market fit.

- Skill: `tjboudreaux/product-launch-ops` (Agent Skill)
- Install (CLI): `npx skillmds@latest add tjboudreaux/product-launch-ops`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tjboudreaux/product-launch-ops/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Marketing & Growth
- Author: tjboudreaux (https://skillmd.com/u/tjboudreaux)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/tjboudreaux/product-launch-ops

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# Launch and Learning Ops

## Intent
- Treat every launch (soft, region, platform, season) as a scientific learning loop.
- Synchronize comms, community, growth, and product telemetry to reach PMF faster.

## Inputs
1. Target segments + messaging hierarchy.
2. Channel plan (owned, earned, paid, influencer, platform features, on-chain activations).
3. Experiment tracking template + analytics stack.

## Workflow
1. **Hypothesis-driven launch plan**
   - Define explicit hypotheses for acquisition, activation, and retention per cohort.
   - Map leading indicators and success/fail guardrails.
2. **Sequential rollout design**
   - Stage launches (friends & family → closed beta → open beta → public) with clear exit criteria.
   - Prepare rollback + comms contingencies for each stage.
3. **Execution war room**
   - Establish daily/weekly rhythm: signal review, issue triage, community feedback digestion.
   - Document decisions and pivots in a shared log.
4. **Learning harvest & handoff**
   - Produce launch retros with metric deltas, qualitative feedback, and next experiments.
   - Update strategic roadmap / PMF scorecard accordingly.

## Verification
- Launch brief, dashboard links, and experiment log stored in shared space before kickoff.
- Guardrails monitored in near real time; incident response plan tested.
- Retrospective completed within one week of stage completion with owners for next steps.