Aipom portfolio quarterly review
Skill deanpeters/ai-product-operating-model-skills/skills/aipom-portfolio-quarterly-review
Run a recurring AI portfolio review that reallocates capital and capacity using strategy, outcomes, economics, readiness, production evidence, dependencies, and learning.From its SKILL.md
npx -y skills add deanpeters/ai-product-operating-model-skills --skill aipom-portfolio-quarterly-reviewAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
3 things to look at
- 27 days oldThe repository was created 27 days ago. New is not bad, but a brand new repository carrying a familiar-sounding name is the shape a typosquat arrives in, and there has been no time for anyone else to find a problem with it.
- no licenseNo license file was found in the repository. Code published without one is not open source by default, so using it at work is a question for whoever answers licensing questions where you are.
- 4 stars4 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
SKILL.md
7.0 KB, ~1.0k tokens by cl100k_base, as published. Nobody here has run it
AIPOM Portfolio Quarterly Review
What Is It
Run a recurring evidence-based portfolio decision that continues, changes, scales, constrains, pauses, stops, or retires AI investments and funds the shared operating capabilities they depend on.
Why Use It
Portfolio meetings become status theater when initiative owners report activity without comparable decisions. A quarterly review connects strategy, value, economics, readiness, production evidence, dependencies, controls, capability, and capacity to explicit allocation.
When to Use It
Use quarterly or at a cadence appropriate to investment and risk. Run off-cycle reviews after material incidents, dependency changes, strategic shifts, or evidence that invalidates a major bet.
What It Produces
- Portfolio context, evidence quality, and change ledger
- Initiative decisions and funding or capacity allocations
- Shared capability, dependency, and safeguard investments
- Retired assumptions, stopped work, exceptions, and owners
- Strategy updates, communication actions, and next review agenda
Who Should Participate
Include accountable portfolio authorities, product and technology leaders, Product Operations, finance, shared-platform owners, and governance partners. Initiative owners provide evidence; they do not unilaterally set criteria or approve exceptions.
Evidence to Bring
Bring strategy choices, initiative inventory, bet charters, economics, stage decisions, readiness and production reviews, outcomes, costs, incidents, dependencies, adoption, reusable capabilities, capacity, exceptions, and prior decision follow-through.
How to Do It
- Load the prior decision ledger, commitments, exceptions, and material changes.
- Confirm current strategy, constraints, capacity, and the decisions required this cycle. Define capacity in usable units and state whether continuing existing work consumes the same allocation slots as new investment.
- Normalize initiative evidence by stage, consequence, and decision—not one universal score.
- Review outcome and economic evidence, production behavior, readiness, dependencies, controls, adoption, and owner confidence.
- Apply critical-gap and exception-expiry logic before relative comparison.
- Decide continue, change, validate, scale, constrain, pause, stop, or retire for each material initiative.
- Allocate investment to shared context, evaluation, governance, platform, capability, and reuse conditions that unlock several bets.
- Examine concentration, duplication, zombie pilots, premature scale, and unowned mandatory work.
- Update strategy assumptions, narrative, allocations, owners, communication, and next evidence requirements.
- Record decisions, dissent, exceptions, allocation assumptions, and follow-through for the next review.
Facilitation Protocol
Use context-dump mode for pre-read synthesis and guided mode for contested decisions. Ask only questions that change allocation, constraint, or ownership. In best-guess mode recommend bounded learning or containment rather than confident scale. Preserve dissent and conflicts of interest.
Decision Logic
- Explore or validate: important uncertainty with a bounded learning path.
- Continue: evidence supports the current stage and next test.
- Scale: representative outcomes, economics, controls, capacity, and production evidence support expansion.
- Constrain or pause: critical gaps or external conditions limit responsible operation.
- Stop or retire: value fails, criteria repeatedly miss, ownership disappears, or a better alternative wins.
- Fund shared capability: one operating condition unlocks or protects several strategically relevant bets.
Do not let sunk cost, executive sponsorship, or aggregate portfolio scores override failed criteria or critical gaps.
An exception must name the authority granting it, the constrained scope, safeguards, expiry, and evidence required for renewal. If capacity units, exception authority, or decision dates are missing, expose them as allocation assumptions or unresolved governance conditions rather than silently resolving them.
Completion Criteria
Finish with evidence quality, initiative decisions, allocations, shared capabilities, stopped work, exceptions and expiry, dissent, accountable owners, strategy changes, communication actions, and next review evidence.
Key Concepts
- Portfolio review allocates scarce capital and attention.
- Learning investments and scaling investments require different evidence.
- Stopped work is a sign of functioning governance.
- Shared capabilities compete for funding with visible features.
Organizational Applications
Use for enterprise AI portfolios, business-unit investments, innovation funds, internal workflow programs, platform strategies, and vendor rationalization.
Common Pitfalls
- Running initiative status presentations
- Comparing discovery and production with one score
- Funding visibility instead of evidence
- Ignoring shared dependencies and mandatory controls
- Renewing exceptions automatically
- Recording decisions without reallocating capacity
Combine With
Use aipom-production-evidence-review for operational evidence, aipom-strategy-narrative-builder to communicate changed choices, and aipom-operating-model-retrospective to improve the review system.
Assets and Templates
Sources
This workflow is an original AIPOM synthesis of evidence-based portfolio governance, staged investment, strategy review, and organizational learning.
What ships with it: 3 files
6.1 KB alongside SKILL.md
examples/
- weak-example.md1.3 KB
- worked-example.md3.8 KB
- template.md966 B