inspired-product
The inspired-product skill guides teams in building products through continuous discovery and delivery by shifting from output-driven feature factories to empowered, cross-functional teams that own problem-solving end-to-end. Use it when addressing product team structure, discovery techniques, roadmap strategy, or how to validate ideas before engineering investment, particularly when moving away from handed-down backlogs toward outcomes-based accountability.
git clone --depth 1 https://github.com/wondelai/skills /tmp/inspired-product && cp -r /tmp/inspired-product/plugins/product-innovation/skills/inspired-product ~/.claude/skills/inspired-productSKILL.md
# Empowered Product Teams Framework Framework for building products customers love through empowered teams that own continuous discovery and delivery. The best product companies don't ship features -- they solve problems, and they give teams the autonomy and accountability to figure out how. ## Core Principle **Empowered product teams** = cross-functional groups given problems to solve (not features to build) who own discovery and delivery end-to-end. Most product failures come not from bad engineering or design but from building things nobody wants. Feature teams receive roadmaps and execute; empowered teams receive objectives and discover solutions. The difference between a feature factory and an innovation engine is whether teams are missionaries (driven by vision and empathy) or mercenaries (driven by a handed-down backlog). ## Scoring **Goal: 7/7.** Score product team structures, discovery practices, or delivery processes by the Quick Diagnostic below -- **1 point per satisfied row**, scored 0-7. Bands: **6-7** = empowered teams own outcomes and discovery runs continuously with engineers; **4-5** = discovery happens but inconsistently, or teams own output with partial outcome accountability; **<=3** = a feature factory: teams receive a roadmap of dated features and skip discovery. Always state the current score and the specific failed diagnostic rows to fix to reach 7/7. ## Framework ### 1. Product Discovery vs Delivery **Core concept:** Product work runs on two parallel tracks: discovery determines what to build by addressing risks before engineering investment; delivery builds production-quality software. Most organizations skip discovery entirely, jumping from idea to backlog to sprint. **Why it works:** Discovery is cheap and fast; delivery is expensive and slow. Validating ideas before committing engineering avoids the most common failure mode: building something nobody wants. **Key insights:** - Discovery answers four risks: value (will customers use it?), usability (can they figure it out?), feasibility (can we build it?), viability (does it work for the business?) - Discovery output is validated ideas backed by evidence, not PRDs or specifications - Run 10-20 discovery iterations per feature that reaches delivery -- most ideas won't work, so fail fast and cheap - Discovery is not a phase; it runs continuously alongside delivery, with engineers participating **Product applications:** | Context | Application | Example | |---------|-------------|---------| | New feature | Validate all four risks before committing | Prototype-test onboarding flow with 5 users before building | | Roadmap prioritization | Prioritize strongest discovery evidence | Ship the feature with 4/5 successful user tests, not the CEO's request | | Sprint planning | Feed backlog from validated discovery output | Only discovery-tested items enter the sprint | **Ethical boundary:** Never cherry-pick discovery evidence to justify a conclusion you already chose; report the tests that failed alongside the ones that passed. See [references/discovery-techniques.md](references/discovery-techniques.md) when planning a discovery cycle -- the four-risks framework, a 5-stage interview script, prototyping techniques, and concrete evidence thresholds for "validated". ### 2. Empowered Product Teams **Core concept:** A small, durable, cross-functional group (product manager, product designer, engineers) given a problem to solve, owning discovery and delivery, accountable for outcomes rather than output. **Why it works:** The people closest to the customer and the technology find better solutions than a remote roadmap author -- and a team that discovered the solution itself defends and refines it under pressure, where a team handed a spec ships it and moves on. **Key insights:** - The PM is not a project manager or backlog administrator -- they own value and viability and need deep knowledge of customers, data, business, and industry - The product designer owns the user experience holistically, not just visual design - Engineers are the best source of innovation because they know what is technically possible - Keep teams durable (stable membership) and highly collaborative - Accountability means outcomes (adoption, retention, revenue), not output (stories shipped) **Product applications:** | Context | Application | Example | |---------|-------------|---------| | Team structure | Organize around outcomes, not components | "New user activation" team owns the whole first-week experience | | Hiring | Hire PMs for competence, not credentials | Evaluate customer knowledge, data fluency, business acumen | | Performance | Measure results, not velocity | Track activation-rate improvement, not stories per sprint | **Ethical boundary:** Never claim to empower teams while overriding their discovery findings with executive mandates -- if leadership dictates the solution, the team is not empowered. See [references/empowered-teams.md](references/empowered-teams.md) when staffing or diagnosing a team -- role-by-role competence breakdowns with red flags, missionary vs mercenary dynamics, coaching, and a feature-factory-to-empowered transformation table. ### 3. Product Discovery Techniques **Core concept:** Systematically test ideas against the four risks using opportunity assessment, customer interviews, prototyping, and user testing -- producing evidence quickly and cheaply. **Why it works:** Ideas are assumptions; without rapid testing, teams build for months on untested assumptions and discover failure only after launch. Discovery techniques compress learning cycles from months to days. **Key insights:** - Prototypes are the primary tool: high-fidelity for usability, live-data for feasibility, Wizard of Oz for value - Test with real target users, not colleagues; qualitative testing (5 users) reveals problems, quantitative validates at scale - Interview for behavior (what they did), not opinion (what they say the
Build lean, opinionated products using the 37signals philosophy from "Getting Real", "Rework", and "Shape Up". Use when the user mentions "Getting Real", "Rework", "Shape Up", "37signals", "Basecamp method", "six-week cycles", "fixed time variable scope", "appetite vs estimates", "betting table", "breadboarding", "fat marker sketch", "build less", "underdo the competition", "opinionated software", "we have too many meetings", "how do we ship faster", or "stop overbuilding". Also trigger when cutting scope to ship sooner, running a small team, or avoiding long-term roadmaps. Covers shaping, betting, building, and the art of saying no. For MVP validation, see lean-startup. For design sprints, see design-sprint.
Guided journey from a working codebase grown slow and tangled to one measurably fast, cleanly bounded, and readable. Orchestrates eight skills phase by phase - working-with-legacy-code, clean-architecture, software-design-philosophy, refactoring-patterns, system-design, ddia-systems, release-it, pragmatic-programmer - every phase carries its method inline so it runs standalone, asking the user questions at every decision point and recording results in the project docs/ folder (PERFORMANCE.md, ARCHITECTURE.md, ARCHITECTURE-OPTIMIZATION-PLAN.md) so the journey resumes across sessions. Use when the user wants to make an app faster, untangle drifted boundaries, fix slow endpoints and queries, or says ''it works but it is slow and getting worse''. For an untested prototype, improve-code-quality; for an aged codebase you fear to touch, remove-technical-debt; for greenfield structure, design-code-architecture; for marketing-site page speed, improve-website. For one framework in isolation, invoke that skill directly.
Create uncontested market space using value innovation instead of competing head-to-head. Use when the user mentions "blue ocean", "red ocean", "strategy canvas", "ERRC framework", "value innovation", "non-customers", "buyer utility map", "the market is too crowded", "how do we stand out", or "escape the price war". Also trigger when exploring a new market category, or finding underserved or non-customers. Covers the Four Actions Framework, Six Paths, buyer utility map, and value-cost trade-offs. For real strategy formulation and bad-strategy detection, see good-strategy-bad-strategy. For tech adoption strategy, see crossing-the-chasm. For product positioning, see obviously-awesome.
Structure software around the Dependency Rule: source code dependencies point inward from frameworks to use cases to entities. Use when the user mentions "architecture layers", "dependency rule", "ports and adapters (hexagonal)", "onion architecture", "screaming architecture", "where should business logic go", "decouple from the database", "swap the framework without a rewrite", or "keep business rules independent". Also trigger when deciding which layer code belongs in, isolating core logic from infrastructure, defining module boundaries, or debating whether the framework should call your code or the reverse. Covers component principles, boundaries, and SOLID. For code-level quality, see clean-code. For domain modeling, see domain-driven-design.
Write readable, maintainable code through disciplined naming, small functions, and clean error handling. Use when the user mentions "clean up this code", "this function is too long", "code smells", "naming conventions", "boy scout rule", "single responsibility", or "unit test quality". Also trigger when reviewing a pull request for readability, untangling a messy function, debating comment styles, or improving error-handling patterns. Covers SRP, comment discipline, formatting, and unit testing. For refactoring techniques, see refactoring-patterns. For architecture and dependency rules, see clean-architecture.
Start and scale networked products using Andrew Chen''s "The Cold Start Problem" framework for network effects. Use when the user mentions "network effects", "chicken and egg", "cold start", "two-sided marketplace", "atomic network", "hard side", "liquidity", "critical mass", "invite-only launch", "how do I get my first users", or "the marketplace has no buyers or sellers". Also trigger when launching a marketplace, social, or collaboration product that is worthless without other users, deciding launch sequencing and seeding tactics, or diagnosing stalled network growth at scale. Covers the five stages: cold start, tipping point, escape velocity, hitting the ceiling, and the moat. For word-of-mouth virality, see contagious. For habit-driven retention, see hooked-ux.
Engineer word-of-mouth and virality using the STEPPS framework (Social Currency, Triggers, Emotion, Public, Practical Value, Stories). Use when the user mentions "go viral", "word of mouth", "shareable content", "social currency", "why people share", "referral program", "nobody is sharing it", or "make this spread". Also trigger when designing shareable features, crafting social campaigns, or building products that spread through peer recommendation. Covers environmental triggers and high-arousal emotional content. For sticky messaging, see made-to-stick. For persuasion tactics, see influence-psychology.
Build a weekly cadence of customer touchpoints using Opportunity Solution Trees, assumption mapping, and interview snapshots. Use when the user mentions "continuous discovery", "opportunity solution tree", "weekly interviews", "assumption testing", "discovery habits", "product trio", "outcome-based roadmap", "how do I talk to customers regularly", "we keep building things nobody uses", or "connect research to the roadmap". Also trigger when setting up regular customer feedback loops, prioritizing which experiments to run, or tying discovery insights to delivery work. Covers experience mapping, co-creation, and prioritizing opportunities. For interview technique, see mom-test. For team structure, see inspired-product.