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data-ai-tech-strategy
Use when creating Data/AI strategy, principles, roadmaps, MLOps plans, or executive docs.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
메뉴
Use when creating Data/AI strategy, principles, roadmaps, MLOps plans, or executive docs.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Use when copy editing, proofreading, polishing, or removing AI-sounding prose.
Use when coaching technical leaders on conflict, burnout, cofounders, CTO transitions, or growth.
Use when writing Manning-style technical chapters, Chapter 1s, examples, callouts, or summaries.
Use when drafting ML/AI papers, verifying citations, framing evidence, using LaTeX, or preparing submissions.
Use when writing strategic tech posts, engineering narratives, opinion pieces, or industry analysis.
| name | data-ai-tech-strategy |
| description | Use when creating Data/AI strategy, principles, roadmaps, MLOps plans, or executive docs. |
| allowed-tools | Read,Write,Edit,Bash,Glob,Grep,WebSearch,WebFetch |
Use to turn Data, AI, and ML work into clear strategy: business alignment, architecture direction, principles, roadmap sequencing, MLOps maturity, and leadership communication.
Use five pillars: business alignment, technical vision, organization design, delivery excellence, and governance/ethics.
Translate technical work into executive terms. Prefer numbers, tradeoffs, commitments, and known unknowns over generic platform language.
Load references/strategy-document-template.md, references/engineering-principles.md, references/mlops-principles.md, or references/roadmap-planning.md only when needed.