How to AI
👋 This handbook is based on the following resources and my own experience (still new). I encourage you to explore the original sources for deeper insights and broader context.
Primarily:
AI Engineering by Chip Huyen
AI Product Manager's Handbook by Irene Bratsis
Others:
Building effective agents by Anthropic
The 2025 AI Engineer Reading List by Latent Space
12-Factor Agents — Reliable LLM app principles by Dex Horthy (video)
Zero to One: Learning Agentic Patterns by Phil Schmid
From Software Engineer to AI Engineer by Gergely Orosz
AI Engineer YouTube channel by World's Fair - tons of real world use cases
AI Engineering Anti-patterns by Chip Huyen
Pre-reading:
☕ For super basic concepts, check out AI Agents Roadmap by Roadmap.sh
😄 For a non-tech intro to LLMs, check out Intro to Large Language Models by Andrej Karpathy
😍 For a tech-ish deep dive, check out Deep Dive into LLMs like ChatGPT by Andrej Karpathy
This handbook is written with the help of Cursor AI with vibe coding and NotebookLM.
Note: As someone new to AI Engineering myself, this handbook represents my public learning journey - Jamie Wen
Before we start, here are two diagrams about cognitive bias and hype cycle. I think they are quite interesting for this journey.
Gartner Hype Cycle - AI 2025
🦉, let's get started.
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