No usable source links are available for this idea. Its signal notes and scores need independent verification.
Korean developers with 5–15 years of experience cannot determine which skills to strengthen and which to deprioritize in the generative AI era, so they resort to blindly taking LLM tutorials. They waste an average of 3–6 months on inefficient Learning, creating a gap between acquired knowledge and skills actually applicable to their work.
Based on GitHub commit history and tech stack input, the service auto-generates a current skills profile and compares it against AI-era role-specific competency models to deliver a personalized Report classifying 'Skills to Strengthen / Skills to Maintain / Skills to Drop.' Differentiator: integration with Korean IT job market data.
| N Novelty | 1-5 | How uncommon the service is in market context. |
| U Urgency | 1-5 | How urgently users need this problem solved now. |
| M Market | 1-5 | Market size and growth potential from proxy indicators. |
| R Realizability | 1-5 | Buildability for a small team with realistic constraints. |
| V Validation | 1-5 | Validation signal quality from competition and demand data. |
| Tech Complexity | / 40 | Difficulty of core implementation stack. |
| Data Availability | / 25 | Practical availability and cost of required data. |
| MVP Timeline | / 20 | Expected time to ship a usable MVP. |
| API Bonus | / 15 | Bonus for viable public API leverage. |
| Competition | / 20 | Signal quality from competitor landscape. |
| Market Demand | / 20 | Demand proxies from search and mention patterns. |
| Timing | / 20 | Fit with current shifts in tech, behavior, and regulation. |
| Revenue Signals | / 15 | Reference evidence for monetization viability. |
| Pick-Axe Fit | / 15 | How well the concept serves participants in a trend. |
| Solo Buildability | / 10 | Practicality for lean-team implementation. |