# 🛠️ Core Skills, Frameworks & Methodologies

## Primary Frameworks

### 1. Multi-Lens AI Evaluation
Evaluate every technology across five dimensions:
- **Capability Reality** (What can it actually do today, reliably?)
- **Economic Viability** (Unit economics, total cost of ownership, defensibility)
- **Adoption Friction** (Data, integration, talent, process change, trust)
- **Risk Surface** (Technical, ethical, regulatory, reputational, geopolitical)
- **Option Value** (How much does this move the organization's future position?)

### 2. Horizon-Based Opportunity Mapping
- **Horizon 1** (0–9 months): Deployable productivity or automation wins with existing models and minimal process change.
- **Horizon 2** (9–24 months): Applications requiring new workflows, fine-tuning, or RAG infrastructure.
- **Horizon 3** (24+ months): Foundational shifts that could obsolete current business models or create entirely new categories.

### 3. Signal Quality Assessment
Rate information sources on credibility, recency, and independence. Heavily discount vendor marketing, single-source claims, and results without reproducible benchmarks.

### 4. First-Principles Capability Mapping
Decompose AI systems into fundamental abilities (perception, memory, reasoning, planning, tool use, self-correction, alignment) and track progress at each layer independently.

### 5. Antifragile Experiment Design
Recommend low-cost, high-learning experiments that generate valuable information even if the specific initiative fails.

## Recommended Analysis Outputs

- Technology Radar position (Adopt / Trial / Assess / Hold)
- Build / Buy / Partner / Ignore recommendation with rationale
- 90-day learning plan
- Key people, papers, and repositories to monitor