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Build a weekly cadence of customer touchpoints using Opportunity Solution Trees, assumption mapping, and interview snapshots.
Passed 20 of 22 test cases with the skill, and 15 of 22 without it.
and 2 more in the full report
5 fixed15 passed either way2 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 5 test cases the skill fixed. Same model, same prompt, with and without the skill.
A software team completes a self-assessment: they hold 1 customer call per week (Yes), maintain a living tree (Yes), have the full trio present on calls (Yes), trace shipped features to opportunities (Yes), and make interview snapshots visible (Yes). However, they do not run pre-build assumption tests (No) and evaluate opportunities in isolation (No). What is their numerical diagnostic score and what are their remaining fixes?
| Checked | Without skill | With skill |
|---|---|---|
| calculates a score of 8 out of 10 by adding 5 passing criteria to the base score of 3 | Missed | Passed |
| recommends running assumption tests on leap-of-faith premises prior to building | Missed | Passed |
The instructions your model reads when the skill loads.
Framework for building a sustainable weekly practice of customer discovery that keeps product teams progressing toward desired outcomes. Discovery is not a phase before development — it is embedded in the ongoing rhythm of product work so every decision is informed by fresh evidence.
Good product discovery requires a continuous cadence, not a one-time event. Teams that talk to customers every week, map opportunities visually, and test assumptions before building consistently outperform teams that rely on intuition, stakeholder opinions, or quarterly research cycles. The benchmark: at least one customer touchpoint per week, every week, by the product trio (product manager, designer, engineer).
Goal: 10/10. Score a discovery practice by the seven Quick Diagnostic rows below — start at 3, add 1 point per row answered "yes" (max 10). Bands: 9-10 = weekly cadence, a living Opportunity Solution Tree, systematic assumption testing, and every shipped feature traceable to a customer opportunity; 5-6 = some discovery happening but ad hoc, PM-only, or disconnected from delivery; ≤3 = intuition- and stakeholder-driven with no regular customer contact. Report the current score, the failing rows, and the specific fix for each.
Core concept: An Opportunity Solution Tree (OST) visually connects a desired outcome (top) to customer opportunities (middle) to potential solutions and experiments (bottom), making implicit product thinking explicit and shared.
Why it works: Most teams jump from business outcome straight to solutions, skipping the customer need entirely; the OST forces understanding of the opportunity space first, preventing features nobody wants.
Key insights:
Product applications:
| Context | Application | Example |
|---|---|---|
| Quarterly planning | Map the opportunity space before committing to features | "Increase trial-to-paid conversion" → discover why users don't convert |
| Feature prioritization | Compare solutions across opportunities for the highest-leverage bet | Three solutions for "can't find content" vs. two for "confusing onboarding" |
| Stakeholder alignment | Use the tree as the shared strategy visual | Walk leadership through why you chose opportunity X over Y |
Ethical boundary: Never cherry-pick opportunities to justify a predetermined solution — the tree must reflect needs discovered through research.
See references/opportunity-trees.md when building or auditing a tree — adds the 4-layer diagram, good-vs-poor outcome tables, solution-generation techniques, a weekly update rhythm, healthy/dying-tree signals, two worked examples, and four anti-patterns.
test cases passed, vs 15 / 22 without
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