AI Engineering: My Learning Notes (VitePress)

My personal, easy-to-understand learning notes from reading AI Engineering: Building Applications with Foundation Models by Chip Huyen (O'Reilly, 2025), written up as a VitePress documentation site.

⚠️ These are my own notes from working through the book, shared for learning purposes. They reflect my understanding and capture the ideas, not the book's full depth (case studies, references, diagrams). If you find them useful, please buy the book.

What's inside

• Getting Started: about these notes + "The Big Picture" mental model
• All 10 chapters in my own words, in plain English:
  1. Introduction to Building AI Applications with Foundation Models
  2. Understanding Foundation Models
  3. Evaluation Methodology
  4. Evaluate AI Systems
  5. Prompt Engineering
  6. RAG and Agents
  7. Finetuning
  8. Dataset Engineering
  9. Inference Optimization
  10. AI Engineering Architecture and User Feedback
• Reference: a Glossary and a one-page Cheat Sheet

Getting started

# 1. Install dependencies
npm install

# 2. Start the dev server (hot reload) → http://localhost:5173
npm run docs:dev

# 3. Build the static site (output: docs/.vitepress/dist)
npm run docs:build

# 4. Preview the production build locally
npm run docs:preview

Requires Node.js 18+ (tested on Node 22).

Project structure

ai-engineering-book/
├─ docs/
│  ├─ .vitepress/
│  │  └─ config.mts        # Site config: nav, sidebar, theme, search
│  ├─ index.md             # Home page (hero + features)
│  └─ guide/
│     ├─ introduction.md   # About this summary
│     ├─ big-picture.md    # The overall mental model
│     ├─ ch01..ch10*.md    # One page per chapter
│     ├─ glossary.md       # Plain-English term definitions
│     └─ cheat-sheet.md    # One-page refresher
├─ package.json
└─ README.md

Notes

• Local search is enabled (no external service needed).
• Content reflects the structure and ideas of the first edition (December 2024 / 2025).