layers-product-strategy

/layers-product-strategy

Assumes /layers-intro has been loaded. This skill is a library of techniques, not a script — see "How to use these skills" there.

Strategy is the first layer of the solution space — where problem-space understanding converts into deliberate decisions about scope and direction. It is about choices: which user needs to serve, and which business outcomes to target.

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The decisions this layer makes

• The business outcome this work serves
• Which user opportunities (needs, pains, desires) genuinely connect to that outcome
• What solution bets we're placing on those opportunities
• How to test the riskiest assumptions cheaply
• Which bets to pursue first, and why

If the outcome and the bets are already clear, don't rebuild the tree for its own sake.

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Disciplines — what keeps strategy honest

• The outcome is measurable, meaningful, and bounded. Not "grow the product" but "increase users who activate in the first 30 days." One outcome per tree.
• Opportunities are customer needs/pains/desires — anchored to a journey moment. First-person, problem-space statements ("I don't know which streaming service has this movie"), not job stories and not features. Apply the flip test: if you can restate it as a feature, it's a solution in disguise. Keep them specific, not generic. Group opportunities by journey moment — the forcing function that exposes vague opportunities and surfaces moments left unaddressed. (Teresa Torres.)
• Every opportunity connects to the outcome. If serving it wouldn't move the outcome, it doesn't belong in this tree.
• Every bet names its riskiest assumption, and there's more than one bet per opportunity — resist early convergence.
• Every experiment is the cheapest way to test the core assumption — days, not months.

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Techniques

The Opportunity Solution Tree is the default; the rest serve particular strategic questions.

Technique	Use it when
Opportunity Solution Tree (Teresa Torres)	Default. Makes outcome → opportunity → solution → experiment explicit. Good for ongoing discovery.
Solution bets	For a chosen opportunity: "We could [solution], which we believe would [serve the opportunity] because [reasoning]." Generate several; name each one's key assumption.
Experiments	Cheapest test of a bet's core assumption — prototype, fake door, concierge, a targeted interview, data analysis.
Impact mapping (Gojko Adzic)	B2B with multiple stakeholders who each must change behaviour.
Jobs portfolio mapping	Many job stories — decide which to target by frequency, severity, strategic fit.
Now / Next / Later roadmap	The team needs a shared timeline view of bets.
Kano analysis	Sort candidate features into hygiene, performance, and delight.
HEART / North Star (Google / Amplitude)	Choosing the outcome metric. HEART structures the choice; North Star distils to one.
Wardley mapping	Positioning depends on where capabilities sit on the evolution curve; build/buy/partner.
Bundling / unbundling (Christensen)	Should this product own more of the workflow, or one job precisely?
NPE Canvas	Consumer products: Narrative, Primitive, Enablers.
Critical User Journeys (Google / Reforge)	Which flows to prioritise — the minimal path to core value (high-traffic, high-revenue, or metric-critical).