Magnus HedemarkGitHubusername <username>factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>* feat(product-lifecycle-learning): add product lifecycle learning skill (#194) Introduce a new skill to close the launch-to-learning loop for product features and capabilities. Covers: - Post-launch outcome review with explicit epistemic categories (expected/observed/uncertain/inferred) - Assumption ledger updates with confidence shifts - Multi-dimensional feature health assessment - Six lifecycle decisions: continue/improve/harvest/pivot/pause/retire - Full retirement lifecycle: deprecation communication, migration paths, customer treatment during sunset, and internal cleanup - Durable retained learning records that feed back into roadmap, analytics, adoption, experimentation, and specifications Ships 4 references (discovery brief, epistemic discipline, retirement lifecycle, feedback destinations), 6 templates (outcome review, assumption ledger update, feature health record, retirement decision, sunset plan, retained learning record), and 7 eval cases including adversarial coverage. Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com> * fix(product-lifecycle-learning): regenerate marketplace with corrected description The Claude marketplace JSON contained the original description starting with "Close" which was replaced with "Compare" to satisfy the imperative-verb quality check. Regenerate to match the corrected SKILL.md frontmatter. Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com> * fix(product-lifecycle-learning): regenerate llms.txt with corrected description Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com> --------- Co-authored-by: username <username> Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
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Retained Learning Record
Capture durable reusable learning from a completed lifecycle cycle. This is not a transient meeting summary — it is the evidence that the launch-to-learning loop actually closed. The record survives the feature and informs future decisions.
Record Identity
| Field | Value |
|---|---|
| Feature / capability name | |
| Lifecycle decision | (continue / improve / harvest / pivot / pause / retire) |
| Decision date | |
| Record author | |
| Record date | |
| Record ID | (unique, stable identifier) |
What We Expected
Summarize the key expected outcomes from the spec, roadmap, or launch brief. What did we predict would happen?
What We Observed
Summarize the key observed outcomes with confidence. What actually happened?
What Was Uncertain
What could we not determine? What was ambiguous, noisy, or contested?
What We Inferred
What did we conclude, and with what strength? What is the chain of reasoning from evidence to conclusion?
Assumptions: Before and After
| Assumption | Before (confidence) | After (confidence) | What changed? |
|---|---|---|---|
What We Would Do Differently
Given what we now know, what would we change about how this feature was specified, built, launched, or measured?
Reusable Patterns
What patterns, heuristics, or rules of thumb emerged that apply beyond this feature?
| Pattern | Description | When it applies | Confidence |
|---|---|---|---|
Anti-Patterns to Avoid
What approaches failed or produced misleading results that should be avoided in the future?
| Anti-pattern | Description | Why it failed | How to detect it early |
|---|---|---|---|
Feedback Routed
| Destination | What was routed | Date |
|---|---|---|
| Roadmap (product-roadmapping-and-portfolio) | ||
| Analytics (product-analytics-and-measurement) | ||
| Adoption (product-adoption) | ||
| Experimentation (product-experimentation) | ||
| Specifications (spec-driven-development) | ||
| Customer Success (conditional-customer-success) | (if applicable) | |
| Incident Learning (incident-learning) | (if applicable) |
Record Status
Status: (Draft / Final)
Next review: (date or "terminal — feature retired")
Linked records: (prior retained learning records for the same feature, if any)