Install
openclaw skills install @deciqai/dynamic-core-competenceActivate when: user asks 'what is our real edge?', 'what will our moat look like in 3 years?', 'which capabilities should we invest in?', someone says 'competitive advantage' without a specific testable claim, or a team is assessing whether their current position will survive a technology or market shift. Do NOT activate when: the question is purely operational (no competitive position implication), or the market is too new to assess competence importance trajectories (use lean experimentation instead).
openclaw skills install @deciqai/dynamic-core-competenceCore competence (Prahalad & Hamel, 1990) becomes dynamic when you recognize that competences decay, markets change what they reward, and building sequence matters. The common failure: treating competence as a static asset — identify once, defend, leverage indefinitely. Leaders in one technology cycle become entrenched incumbents in the next, not because they stopped being competent but because the market stopped rewarding what they held.
Skill composition: Use AFTER [porters-five-forces] to know what the market structure rewards. Use WITH [second-order-thinking] to trace which competences become obsolete as markets evolve. Use BEFORE [okr-goal-setting] — OKRs must target specific competence dimensions.
When NOT to use:
In Coach mode, respond one step at a time. Each [WAIT] is a hard stop — output only that step's question, then stop.
Output artifact: Dynamic Competence Portfolio
Gate rule: Generic claims ("we have a great culture") are not accepted without decomposition into specific, testable mechanisms. Every competence must survive the new-entrant test: could a well-funded new entrant replicate this within 18 months? If yes, it is a temporary advantage, not a core competence.
Step 1 — Inventory all 16 competence dimensions (sales channels, R&D, talent, cost advantage, intangible assets, culture, patents, economies of scale, network effects, org transformation, switching costs, invention, monopoly, difficult to substitute, capital operations, scarcity). Self-assess [Strong/Moderate/Weak/N/A] + specific evidence. Gate 1: Every Strong rating has a mechanism statement. Step 2 — Rate each Moderate+ competence on: (a) Strength 1–5; (b) Decay rate — Fast/Medium/Slow; (c) Market importance in 3 years — Rising/Stable/Declining + named market force. Gate 2: Specific reasons, not gut feel. Step 3 — Identify at-risk competences: Type 1 = decaying without investment; Type 2 = declining market importance. Specific threat + timeline for each. Gate 3: No vague concern. Step 4 — Identify build priorities: Type 1 = rising importance, currently weak; Type 2 = unlock competences (e.g., talent must precede R&D). Sequence: which ONE first, and why (unlocks others or window closing). Gate 4: Sequenced with explicit reasoning. Step 5 — Investment plan: Per build priority: specific action, minimum investment for 12-month milestone, observable signal, explicit opportunity cost (which existing competence gets less). Gate 5: All four elements present. Stop-rule: If your competence map is identical to any competitor's, return to Step 1 and require mechanism-level specificity for every Strong rating.
Dynamic Competence Portfolio — [Entity] — [Date]
1. Current Inventory: | Dimension | Strength 1-5 | Decay Rate | Market Importance 3yr | Mechanism |
2. At-Risk: | Competence | Risk Type (decay/declining importance) | Specific Threat | Timeline |
3. Build Priorities (sequenced): | Priority | Competence | Reason | Investment | 12-Month Milestone | Signal |
4. Unlock Map: which competences must be built before others
5. Opportunity Cost Statement: which competences receive less investment and why
→ Method in Action: Corning Incorporated's Competence Evolution, 1851–2007
Apply the framework to specific industry contexts. Contributions welcome via the repo.
| Pack | Key rising dimensions | Watch out for |
|---|---|---|
| Software & Platforms | Network effects, switching costs (data lock-in) | Patent protection declining vs. AI cycles; build network effects before scale |
| Manufacturing & Industrial | Cost advantage mechanism (scale vs. process vs. geography — different decay rates) | "Good people" without systematic talent infrastructure |
| Early-Stage Startups | Pre-PMF: R&D + talent → post-PMF: switching costs + network effects → scale: economies of scale + brand | Spending on sales channels before PMF |
→ Primary sources: references/sources.md
[D] = designed upfront | [O] = observed in real use. [O] entries are more valuable.
| Fake move | Reality |
|---|---|
| [D] "Our competitive advantage is our people." | People are a vector, not a competence. Name what they do together systematically that competitors cannot replicate. |
| [D] "Our brand is our moat." | Brand is an output. The competence is the operational capability that consistently delivers the brand promise. |
| [D] "Our technology is proprietary." | Temporary without an R&D competence that continuously renews it. Static proprietary tech has a finite half-life. |
| [D] "We've always been the cost leader." | Diagnose the mechanism — scale, process, geography — each decays differently. History is not protection. |
| [D] "Our customer relationships are our moat." | Only if switching costs are deliberately engineered (integration depth, data lock-in). Relationship moats decay when the rep leaves. |
| [D] "We'll build new competences when we need them." | The window closes before the need is evident. Network effects and switching costs cannot be built after the leader has critical mass. |
| [D] "Competitors can't copy us — we've done this 20 years." | Time is not a barrier. What would a well-funded entrant need? If "2 years and $50M," you lack a durable moat. |
| [D] "Our patents protect us for 20 years." | Technology cycles are often shorter than patent terms. Patents protect specific claims; technology moves to work-arounds. |
| → Add [O] entries here after each real use — paste the actual failure pattern | What went wrong and why |
Part of deciqAI Knowledge Skills — open-source thinking skills that make rigor executable for AI agents. Built by deciqAI · https://deciqai.com · Contributions welcome — see the template at the repo root.