AI Industry 101
A plain-English field guide to the AI industry for people who want to step in.
A field guide to the AI industry for smart engineers and non-engineers — lawyers, marketers, bankers, and anyone considering a career switch into AI. Covers the landscape, business basics, key players, jargon, industry mechanics, competitive moats, career paths, and the latest market data — organized so you can read one bite-sized piece at a time and build a real mental model of how this industry actually works.
Collection Outline
The Landscape — What Is This Industry?
The shape of the post-2022 LLM ecosystem and why it counts as an industry.
How It Works — The Business Basics
APIs, inference economics, GPUs, and the money that moves around them.
The Players — Segmentation You Need to Know
Frontier labs, open-source shops, infrastructure, middleware, and apps — who does what.
The Jargon Dictionary
The vocabulary you need to read any AI paper, pitch, or press release without bluffing.
How the Industry Operates
Product cycles, enterprise deals, VC dynamics, safety debates, and the regulatory climate.
Winning Factors — What Makes Companies Win or Lose
Distribution, data, talent, compute, brand, and lock-in — the six moats that matter.
Career Paths & Functional Roles
Research, engineering, product, GTM, policy — and what each one actually does.
Latest Data & State of the Industry
Benchmarks, market size, adoption, hiring reality — as of right now.