post-launch-learning

Turns launches into structured learning by comparing expected vs actual outcomes and extracting key learnings. Use after any product launch to capture what worked, what didn't, and inform future decisions.

Safety Notice

This listing is imported from skills.sh public index metadata. Review upstream SKILL.md and repository scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "post-launch-learning" with this command: npx skills add pratikshadake/claude-product-management-skills/pratikshadake-claude-product-management-skills-post-launch-learning

Post-Launch Learning Engine

Purpose

Turn launches into structured learning for better future decisions.

Steps

  1. Compare expected vs actual outcomes.
  2. Identify what worked.
  3. Identify what failed.
  4. Extract root causes.
  5. Define next actions.

Output

Expected Outcome

Actual Result

What Worked

What Didn't

Key Learnings

Next Actions

References

See worked example for a complete scenario.

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

General

launch-readiness

No summary provided by upstream source.

Repository SourceNeeds Review
General

value-vs-effort

No summary provided by upstream source.

Repository SourceNeeds Review
General

tradeoff-articulator

No summary provided by upstream source.

Repository SourceNeeds Review
General

user-segment-prioritizer

No summary provided by upstream source.

Repository SourceNeeds Review