Learning Capture

This skill handles CF-08: Learning Closure from the release-decision framework.

Its job is to produce a reusable learning at the end of every cycle — good, bad, or inconclusive — so the next iteration does not start from opinion.

When to Activate

• A decision has been made (CONTINUE, PAUSE, ROLLBACK CANDIDATE, or INCONCLUSIVE)
• The experiment window has closed
• The user says "what did we learn" or "next iteration"
• Project stage is deciding and a decision exists

On Entry — Read Current State

Before doing any work, read the project from the database using the project-sync skill's get-project command.

Check these fields:

Field	Purpose
hypothesis	The claim that was tested
primaryMetric	What was measured
stage	Current lifecycle position
experiments	Experiment records with decision data
lastLearning	Previous learning (if iterating)

• If no experiment has a decision field → redirect to evidence-analysis first
• If stage is not deciding → a decision may not have been made yet
• If lastLearning already contains a learning for this cycle → review rather than recreate

What a Complete Learning Contains

1. What changed — the specific change that was tested (not "improved the UI")
2. What happened — the measured outcome with numbers
3. Confirmed or refuted — was the hypothesis directionally correct?
4. Why it likely happened — the causal interpretation (honest about uncertainty)
5. Next hypothesis — what this result suggests to try next

All five are required. A learning missing (4) or (5) does not close the loop.

Decision Actions

Produce the learning

Work through each of the five components with the user. Prompt for missing parts one at a time.

Write to decision context

Use the project-sync skill to persist the learning to the database (see Persist State below).

Surface the next hypothesis

The learning must always end with a directional suggestion for what to test next. This is not a commitment — it is the input to the next intent-shaping + hypothesis-design cycle.

Operating Rules

• Do not allow a cycle to close without a written learning
• INCONCLUSIVE cycles still produce learnings — "we learned this measurement approach was inadequate" is valid and complete
• Do not let the learning become a post-mortem — it is forward-facing input
• For longer cycles, write a fuller document to artifacts/learning-[date].md
• Hand off to intent-shaping for the next cycle

Persist State

After completing work, use the project-sync skill to persist state to the database:

1. update-state — save --lastLearning "..." --lastAction "Learning captured"
2. set-stage — set to learning
3. upsert-experiment — save --whatChanged "..." --whatHappened "..." --confirmedOrRefuted "..." --whyItHappened "..." --nextHypothesis "..."
4. add-activity — record what happened, e.g. --type learning --title "Learning captured"

Reference Files

• references/iteration-synthesis-template.md — full five-part template, confirmed/refuted/inconclusive examples, anti-patterns