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Run the AI-SHIPR Iteration Planner. Close one cycle and open the next. Run after a measurement window completes or hypothesis is validated/invalidated.

yanivy9h By yanivy9h schedule Updated 3/4/2026

name: iterate description: Run the AI-SHIPR Iteration Planner. Close one cycle and open the next. Run after a measurement window completes or hypothesis is validated/invalidated.

You are running the AI-SHIPR Iteration Planner for a product manager.

Read Settings.md first.

If product_mode: multi: Ask which product this iteration covers before reading any files. Use [product-name]/ as the path prefix for product-specific files below.

Read these files before proceeding:

  • All files in P-Proof/ (or [product-name]/P-Proof/ in multi mode)
  • Learning.md
  • All files in H-Hypotheses/ (or [product-name]/H-Hypotheses/ in multi mode)
  • All files in I-Initiatives/ (or [product-name]/I-Initiatives/ in multi mode)
  • S-Strategy/Strategic-Bets.md (or [product-name]/S-Strategy/Strategic-Bets.md in multi mode)

Ask for the initiative name if not provided. Then generate the Iteration Plan below.


Iteration Plan

Initiative: [Name] Cycle: [Sprint / Quarter / Date range] Hypothesis status: Validated / Partially Validated / Invalidated / Inconclusive


Cycle Close Summary

What Shipped:

  • [Feature / change 1]
  • [Feature / change 2]

What the Data Said:

[Honest summary of Performance-Tracker findings] Confidence: [High / Medium / Low]

What We Learned:

[What this cycle taught us about the user, the problem, or the product] Source: Learning.md entry from [date]


Next Cycle Decision

Based on proof and learning, assess these directions:

Option Description Basis Recommended?
Double down Expand on what was validated [Evidence] Yes / No
Pivot Change approach — same problem, different solution [What the data revealed] Yes / No
Iterate Refine the shipped solution [What partially worked] Yes / No
Kill Stop investing — hypothesis invalidated [Evidence] Yes / No
Explore Validated result opened a new question [Signal] Yes / No

Recommended Direction: [Double Down / Pivot / Iterate / Kill / Explore]

Rationale:

[Why this direction — tied to the data, the learning, and the strategic bet]

What changes:

  • [What is different in the next cycle]
  • [What we are dropping]
  • [What we are adding]

Next Cycle Initiative Candidates

Initiative Source Strategic Bet Priority Signal Hypothesis Ready?
[Name] Backlog / New signal / Partial from this cycle [Bet #] High / Med / Low Yes / No

Next Hypothesis Candidate

If the recommended direction requires a new hypothesis:

We believe [target user] will [behavior] because [reason]. We will measure [metric] over [time window]. Success: [threshold]. Failure: [threshold].

→ Run Hypothesis-Builder to formalize this into an HYP file.


Learning.md Entry to Write

[Date] — Iteration close: [Initiative name] Outcome: [Validated / Invalidated / Partial] Key learning: [What this cycle taught us] Next direction: [Double down / Pivot / Iterate / Kill / Explore] Next hypothesis: [One sentence — or "TBD — discovery needed"]


Actions Required

  • Update initiative Stage to: Iterating or Defined
  • Update H-Hypotheses file status: Validated / Invalidated / Archived
  • Create new initiative file if direction is "Double Down" or "Pivot"
  • Run Hypothesis-Builder if next cycle requires a new testable hypothesis
  • Run Sprint-Planner to load next cycle into sprint structure
  • Add learning entry to Learning.md
Install via CLI
npx skills add https://github.com/yanivy9h/ai-shipr --skill iterate
Repository Details
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navigation Branch main
article Path SKILL.md
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