AI Investing 101¶

From AI industry zero-base → systematically discuss AI US stock investing.
6 knowledge blocks · 5 real analysis processes · 100% based on free public sources.

Created by @0xcryptowizard · Telegram aiwizz

Start Learning 5-part overview

Who this is for¶

Complete beginners

Don't know what EPS / PE / FCF / 13F are — this site doesn't assume you do. Step by step.
Half-knowing AI

Heard of NVIDIA / ChatGPT, but don't know how the ecosystem actually works — Part 1 gives you the full map.
Want systematic judgment

Tired of following KOL hype — want your own decision framework + continuous review process.

5 Parts — Complete Learning Path

AI Industry

History → tech → supply chain → business → applications → geopolitics. 10 chapters, ~8 hours.

Historical base rate Transformer intuition HBM / nuclear 60 ticker map 5 real cases

10 chapter map
AI Investing

General investment framework (2.A) + AI-specific analysis (2.B). 10 chapters, ~10 hours.

DCF / Mental Models Historical analogs Portfolio sizing 4-dim thesis NVDA walkthrough

10 chapter map
Real Analysis Processes

Coatue / Druckenmiller / Buffett / Howard Marks — 5 public processes. 5 chapters, ~5 hours.

Hedge fund 5-step Buffett 5-step Find bottlenecks Multi-PM view Anti-thesis

5 chapter map
Public Real Cases

Use Part 3 tools to dissect 5 real events — DeepSeek / Samsung HBM / Stargate / Export Controls / Why Buffett doesn't own NVDA. 5 chapters, ~4 hours.

Algorithm wildcard Supply chain wildcard Policy wildcard Geopolitics wildcard Discipline of not participating

5 chapter map
Further Reading

Free source systematic map + 6-week day-by-day reading roadmap. 2 chapters + ongoing.

Company IR / SEC Motley Fool 13F Public podcasts PM letters

2 chapters + roadmap

What you'll be able to do¶

Capability	Example
Explain AI supply chain	What is the relationship between NVIDIA / TSMC / ASML / OpenAI
Read key terminology	HBM / CPO / RPO / Capex 2^nd-derivative / Scaling Laws
Use 4-dim thesis framework	view / supports / red_flags / catalysts + KPI predictions
Apply 5 analysis processes	Hedge fund / Buffett / Find bottlenecks / 3-PM / Anti-thesis
Recognize historical patterns	Is current setup like 1999 dotcom / 2010 mobile / 1840 railways?
See through short-term noise	DeepSeek -17% — panic or broken thesis? 4 invalidations didn't trigger = hold
Build your own thesis library	5-10 stock yamls + weekly/monthly review + 90-day retrospective

Recommended pace · 6-week reading roadmap¶

Week 1 ·

Industry basics¶

History + Transformer + NVDA + LLM + Hardware (Part 1 C1-C5)

Week 2 ·

Industry full¶

Supply chain + Business + Apps + Geopolitics + Cases (Part 1 C6-C10)

Week 3 ·

General investing¶

DCF + Mental Models + Historical analogs + Sizing + Behavioral

Week 4 ·

AI-specific + first thesis¶

4-dim yaml + NVDA walkthrough + write your own

Week 5 ·

Real processes¶

Hedge fund / Buffett / Find bottlenecks / Multi-PM / Anti-thesis

Week 6 ·

Public cases + new event¶

5 cases forensic + dissect 1 recent new event yourself

Detailed day-by-day plan in P5-C2 · 6-Week Beginner Reading Roadmap — 10 hr/week × 6 weeks = 60-hour threshold.

0 paid-source promise¶

All sources on this site are completely free and accessible:

Company IR + SEC EDGAR

10-K / 10-Q / 13F / 8-K — 100% free
Public Podcasts

Lex Fridman · Acquired · All-In · Invest Like the Best
PM Letters to Shareholders

Buffett · Howard Marks · Ackman — fully free
Institutional Holdings 13F

Whalewisdom · Dataroma — free tier sufficient
Academic Blogs

Aswath Damodaran (NYU) — free models + blog
Earnings Transcripts

Motley Fool — free 1-2 days after earnings

0 instances of SemiAnalysis / Stratechery / The Information paid quotes. The first 6-12 months on free sources alone already puts you ahead of 90% of retail investors.