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Aipom strategy narrative builder

Skill deanpeters/ai-product-operating-model-skills/skills/aipom-strategy-narrative-builder

Evidence-based skills for designing and improving AI product operating models

Install
npx -y skills add deanpeters/ai-product-operating-model-skills --skill aipom-strategy-narrative-builder

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Turn an evidence-based AI product thesis, portfolio choices, outcomes, boundaries, and learning into a clear narrative for aligned organizational action.

SKILL.md

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AIPOM Strategy Narrative Builder

What Is It

Translate an evidence-based AI product strategy into a coherent account of the condition, choices, value logic, portfolio, operating implications, boundaries, uncertainties, and learning that should guide organizational decisions.

Why Use It

Strategy fails when teams hear ambition but not choices, or hear commitments without evidence and limits. A narrative makes direction usable while preserving uncertainty and the reasons choices change.

When to Use It

Use after the strategy thesis and portfolio choices are explicit, and refresh after meaningful evidence, incidents, market change, or retired bets. Do not use narrative work to manufacture alignment around an unmade decision.

What It Produces

  • Core strategy narrative and decision logic
  • Explicit choices, non-goals, boundaries, and tradeoffs
  • Outcome and economic chain
  • Portfolio and operating-model implications
  • Audience-specific messages, evidence, and update triggers

Who Should Participate

Include the accountable strategy owner, product and technology leadership, Product Operations, representative product teams, finance or operations, and governance and communications partners.

Evidence to Bring

Bring the thesis, portfolio decisions, bet evidence, outcome maps, economics, constraints, incidents, customer or workforce evidence, non-goals, stopped initiatives, and examples of decisions changed by learning.

How to Do It

  1. Name the audience, decision, time horizon, and accountable strategy owner.
  2. State the customer, business, or operating condition that matters and the evidence behind it.
  3. Explain where AI may create value and where the organization will not invest.
  4. Connect AI behavior to human behavior, product outcomes, and economic or risk value.
  5. Describe portfolio choices, sequencing, shared capabilities, and alternatives declined.
  6. State boundaries, critical safeguards, human accountability, and known limitations.
  7. Show what has been learned, which choices changed, and which assumptions remain open.
  8. Translate the narrative into audience-specific decisions without changing the core facts.
  9. Define evidence and events that trigger revision.

Key Concepts

  • Narrative carries choices; it does not replace them.
  • Non-goals make resource allocation credible.
  • Uncertainty should be visible without making direction vague.
  • A changed strategy can be evidence of learning, not failure.

Organizational Applications

Use for leadership alignment, planning, product-team direction, governance engagement, workforce communication, investment reviews, and external trust communication.

Common Pitfalls

  • Leading with models or vendors
  • Substituting aspiration for evidence
  • Omitting non-goals and tradeoffs
  • Promising outcomes without causal logic
  • Hiding incidents, limits, or disagreement
  • Freezing the narrative after evidence changes

Combine With

Use aipom-outcome-value-map and aipom-economic-case-builder for value logic, and aipom-trust-assurance-pack-builder when an audience needs current system-level trust evidence.

Assets and Templates

Sources

This skill is an original AIPOM synthesis of product strategy, evidence-based narrative, and organizational decision communication.

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