chief-ai-officer-advisor
Chief AI Officer advisory for startups: model build-vs-buy decisions (API vs fine-tune vs in-house), AI risk classification under EU AI Act + US state patchwork, AI cost economics (API-to-self-hosted breakeven), and AI team org evolution. Use when deciding whether to call an API or fine-tune, classifying AI use cases for regulatory risk, calculating when self-hosting pays off, sequencing AI hires, or when user mentions CAIO, AI strategy, model selection, foundation model, fine-tuning, EU AI Act, NIST AI RMF, AI governance, model risk, or AI economics. Strategic only — does not duplicate engine
Profile →npx skills add alirezarezvani/claude-skills --skill chief-ai-officer-advisor --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Chief AI Officer Advisor Strategic AI leadership for startup CAIOs and founders without one. **Four decisions, no AI hype:** 1. **Should we use an API, fine-tune, or build our own?** — model build-vs-buy with 3-year TCO 2. **Is this AI use case high-risk under regulation, and how do we govern it?** — EU AI Act + NIST AI RMF + US state patchwork 3. **When do we switch from API to self-hosted, and at what cost?** — token economics with breakeven analysis 4. **What AI role do we hire next?** — stage-to-role map (AI engineer ≠ ML engineer ≠ research scientist) This skill does **not** cover tactical AI/ML engineering. For RAG implementation, agent design, prompt engineering, eval infrastructure, model deployment, or cost optimization, see `engineering/rag-architect/`, `engineering/agent-designer/`, `engineering/prompt-governance/`, `engineering/self-eval/`, `engineering/llm-cost-optimizer/`. ## Keywords CAIO, chief AI officer, AI strategy, model selection, foundation model, fine-tuning, RLHF, DPO, LoRA, QLoRA, build vs buy, AI build-vs-buy, model risk tier, EU AI Act, AI Act Article 6, Article 9, Article 10, Annex III, prohibited AI, high-risk AI, NIST AI RMF, AI risk management frame
- Keywords
- Quick Start
- Key Questions (ask these first)
- Core Responsibilities
- 1. Model Build-vs-Buy
- 2. AI Risk Classification & Governance
- 3. AI Cost Economics
- 4. AI Team Org Evolution
- Workflows
- Workflow 1: Model Selection Decision (1 hour)
- Workflow 2: AI Risk Classification (2-4 hours)
- Workflow 3: API-to-Self-Hosted Breakeven (1 day)
- Workflow 4: AI Team Roadmap (1 week)
- Output Standards
Decision A: API vs fine-tune vs build python scripts/model_buildvsbuy_calculator.py # embedded customer-support sample python scripts/model_buildvsbuy_calculator.py path/to/use_case.json Decision B: Risk classification under EU AI Act + US state laws python scripts/ai_risk_classifier.py # embedded hiring-AI sample python scripts/ai_risk_classifier.py path/to/use_case.json Decision C: API vs self-hosted economics python scripts/ai_cost_economics.py # embedded 5M tokens/day sample python scripts/ai_cost_economics.py path/to/workload.json python scripts/model_buildvsbuy_calculator.py use_case.json
What does the chief-ai-officer-advisor skill do?
Chief AI Officer advisory for startups: model build-vs-buy decisions (API vs fine-tune vs in-house), AI risk classification under EU AI Act + US state patchwork, AI cost economics (API-to-self-hosted breakeven), and AI team org evolution. Use when deciding whether to call an API or fine-tune, classifying AI use cases for regulatory risk, calculating when self-hosting pays off, sequencing AI hires, or when user mentions CAIO, AI strategy, model selection, foundation model, fine-tuning, EU AI Act, NIST AI RMF, AI governance, model risk, or AI economics. Strategic only — does not duplicate engine
How do I install it?
Run `npx skills add alirezarezvani/claude-skills --skill chief-ai-officer-advisor --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From alirezarezvani/claude-skills, a repository with 23,791 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.