Frameworks¶
Actionable frameworks extracted from each chapter of Blueprint for an AI-First Company. Each framework is a standalone reference you can use immediately.
All Frameworks¶
| Framework | Source Chapter | Use When... |
|---|---|---|
| AI-First vs AI-Enabled | Ch 1: The AI-First Imperative | Determining whether your company should be built on AI or with AI |
| 7 Mental Models of AI-First | Ch 2: The AI-First Mindset | Adopting the thinking patterns that define AI-first leadership |
| Probabilistic AI | Ch 2: The AI-First Mindset | Designing products and processes that embrace uncertainty |
| Build vs Buy Calculus | Ch 2: The AI-First Mindset | Deciding whether to buy, boost, or build AI capabilities |
| Human-AI Collaboration | Ch 2: The AI-First Mindset | Designing workflows where humans and AI are genuinely additive |
| Foundation Models | Ch 3: The AI Landscape | Understanding the model landscape and choosing between providers |
| 6 Questions Before Choosing a Model | Ch 3: The AI Landscape | Evaluating and selecting AI models for your use case |
| 5 Infrastructure Mistakes | Ch 4: Infrastructure | Auditing your AI infrastructure for common failure patterns |
| 8 Patterns for AI Coding | Ch 5: Building with AI | Writing effective prompts and working with AI coding tools |
| 7 Failure Modes of Agents | Ch 6: Agent Architecture | Designing resilient AI agents and preventing common failures |
| 90-Day AI Fluency Program | Ch 8: Teams | Rolling out AI fluency training across your organization |
| Data Flywheel | Ch 9: Data Strategy | Building self-reinforcing data loops that compound over time |
| Data Moats | Ch 9: Data Strategy | Assessing whether your data creates defensible advantages |
| 6 Data Strategy Mistakes | Ch 9: Data Strategy | Avoiding mistakes that stall your data flywheel |
| Automation vs Augmentation | Ch 10: Operations & GTM | Deciding where AI should automate vs augment human work |
| 8 GTM Mistakes with AI | Ch 10: Operations & GTM | Avoiding go-to-market mistakes when deploying AI |
| Permission Model Framework | Ch 11: Ethics & Governance | Setting appropriate autonomy levels for AI systems |
| AI Governance Framework | Ch 11: Ethics & Governance | Building governance structures that enable rather than block |
| 7 AI Risks and Mitigations | Ch 11: Ethics & Governance | Identifying and mitigating the top AI risks |
| 10 Principles of AI-First | Ch 12: Staying Ahead | Applying enduring principles as AI technology evolves |
How to Use These Frameworks¶
Each framework follows a consistent structure:
- Overview — Why this framework matters and when to apply it
- The Framework — The complete framework with all items, examples, and data
- How to Use This — Practical guidance for immediate application
- Related Frameworks — Cross-references to connected frameworks
- Deep Dive — Link back to the full chapter for additional context
Start with the framework most relevant to your current challenge. Use the "Related Frameworks" links to explore connected concepts.
By Topic¶
Strategy & Positioning - AI-First vs AI-Enabled - Build vs Buy Calculus - 10 Principles of AI-First
Building & Technical - Foundation Models - 6 Questions Before Choosing a Model - 8 Patterns for AI Coding - 7 Failure Modes of Agents - 5 Infrastructure Mistakes
Data & Competitive Advantage - Data Flywheel - Data Moats - 6 Data Strategy Mistakes
Operations & Teams - Automation vs Augmentation - Human-AI Collaboration - 8 GTM Mistakes with AI - 90-Day AI Fluency Program
Governance & Risk - Permission Model Framework - AI Governance Framework - 7 AI Risks and Mitigations - 7 Mental Models of AI-First - Probabilistic AI