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2c247a1747 feat(product-lifecycle-learning): add product lifecycle learning skill (#194) (#219)
* 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>

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Co-authored-by: username <username>
Co-authored-by: factory-droid[bot] <138933559+factory-droid[bot]@users.noreply.github.com>
2026-08-02 17:33:10 -04:00

2.3 KiB

Retirement / Continuation Decision

Make and record a lifecycle decision: continue, improve, harvest, pivot, pause, or retire. This decision requires human judgment informed by evidence. No automated threshold or formula replaces context and accountability.

Feature Identity

Field Value
Feature / capability name
Decision date
Decision-maker (name and role)
Prior decision (if any) and date

Evidence Considered

Source Date Key findings
Outcome review
Assumption ledger
Feature health record
Other (specify)

Decision

Decision: (Continue / Improve / Harvest / Pivot / Pause / Retire)

Rationale: (Why this decision, not the other five? Cite the specific evidence that drove the choice. If retiring, explain why harvest or pivot was rejected. If continuing, explain why improve or harvest was not selected.)

Context considered:

  • Product and market context:
  • User base and impact:
  • Available alternatives for users:
  • Business priorities and resource constraints:
  • Strategic alignment:

Risks of this decision:

  • If we are wrong, what breaks?
  • What would change our mind?

Risks of NOT making this decision (status quo):

  • What deteriorates if we defer?

Accountable Human Judgment

Decision-maker: (name and role — must be a human, not an automated system or threshold)

I confirm that I have reviewed the evidence above and made this decision based on my judgment of the product, market, user, and business context.

Sign-off date:

If Retire: Sunset Triggers

Trigger Date / condition
Deprecation announcement
End-of-life (last day of full support)
End-of-support (last day of limited support)
Removal (feature removed from product)
Internal cleanup complete
Learning closure recorded

Sunset plan: (link to sunset-plan.md or fill here)

If Not Retire: Follow-Up

Action Owner Due date
Next review date
Metrics to monitor
Triggers that would change the decision

Routing

  • Decision routed to roadmap (product-roadmapping-and-portfolio)
  • If retire: sunset plan routed to customer-success (conditional-customer-success)
  • Learning routed to retained learning record