product-launch-ops

# 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.