The AI industry isn't one market. It's a four-layer stack — and where a company sits tells you more than its brand ever will.
Infrastructure, models, platforms, applications. Each layer has its own economics, its own players, its own career shapes.
Last revised 5/20/2026
AI Industry 101
A plain-English field guide to the AI industry for people who want to step in.
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. Written for lawyers, marketers, bankers, and anyone considering a career switch into AI who wants a real mental model of how this industry actually works.
PrimerIndustry Map
Earn6CreditsinArtificial IntelligenceBusiness Acumen
8Modules47Sessions559Cards127Quizzes
Modules in this Collection’s System
Hover a module to read it directly
The Landscape — What Is This Industry?
The shape of the post-2022 LLM ecosystem and why it counts as an industry.
6Sessions
How It Works — The Business Basics
APIs, inference economics, GPUs, and the money that moves around them.
6Sessions
The Players — Segmentation You Need to Know
Frontier labs, open-source shops, infrastructure, middleware, and apps — who does what.
6Sessions
The Jargon Dictionary
The vocabulary you need to read any AI paper, pitch, or press release without bluffing.
6Sessions
How the Industry Operates
Product cycles, enterprise deals, VC dynamics, safety debates, and the regulatory climate.
6Sessions
Winning Factors — What Makes Companies Win or Lose
Distribution, data, talent, compute, brand, and lock-in — the six moats that matter.
6Sessions
Career Paths & Functional Roles
Research, engineering, product, GTM, policy — and what each one actually does.
6Sessions
Latest Data & State of the Industry
Benchmarks, market size, adoption, hiring reality — as of right now.
5Sessions
What You'll Walk Away With
- 4layers of the AI stack and their distinct economics
- 30+terms to stop bluffing in your next AI conversation
- 6competitive moats that separate AI winners from losers
- 5career paths across research, engineering, product, GTM, and policy
- 5data points every AI-adjacent professional should know
You'll Have Answers To
- ?What are the four layers of the AI industry stack — and why does where a company sits matter more than its brand?
- ?How do AI companies actually make money, and which business models are sustainable versus hype-driven?
- ?What separates a genuine competitive moat in AI from a temporary head start?
- ?Which career paths in the AI industry don't require a technical background — and what do they actually involve?
- ?Why did generative AI explode in 2022–2024, and what structural forces were building for years before the public noticed?
Critical Concepts Explored
Four-Layer AI StackFoundation Models vs. Fine-Tuned ModelsInference EconomicsData MoatModel CommoditizationAI-Native vs. AI-Augmented CompaniesCompute InfrastructureToken EconomicsScaling LawsAI Application Layer
Editor's Note
“The clearest map of the AI industry I've seen written for people who are not engineers.”
Treats the post-2022 AI landscape as a four-layer stack with distinct economics at each level. Never hypes, never talks down. By the time you finish, you can locate any AI company on the map — the real skill this collection builds.
Editor's Brief
- Who it's for
- Career switchers, non-technical professionals working alongside AI teams, and anyone considering a move into AI who wants to reason about the industry without bluffing.
- What stands out
- Structural rigor. It separates infrastructure, models, platforms, and applications — and explains why each layer has different margins, players, and career shapes. The jargon dictionary alone is worth the read.
- Read if
- You want to stop feeling disoriented every time someone says 'frontier model' or 'inference economics' at a meeting.
Gold Quotes
About the Curator
IIndustry FoundationsAn editorial channel that maps emerging industries for smart non-engineers. Field guides written with the rigor of a trade publication and the clarity of a Sunday long-read.
