GLOSSARY
The vocabulary, defined
- The Commercialization Gap
- The distance between an AI model that works and a business that pays for it. Closing it takes pricing, unit economics, go-to-market, and a repeatable story, not a better model. Read the commercialization gap piece →
- Chief AI Officer
- The role that owns the line between what AI can do and what the business gets paid for: build-buy-kill calls, AI pricing, cost to serve, and the board translation. Read the Chief AI Officer guide →
- Fractional Chief AI Officer
- A senior operator who owns AI commercialization on a part-time or advisory basis, giving a company the judgment without a full executive salary. Read the fractional Chief AI Officer guide →
- Story, Model, Machine
- The three layers of the commercial rebuild: the story the market can repeat, the pricing model that survives diligence, and the go-to-market machine that converts. See the Story, Model, Machine framework →
- The Commercial Layer
- The commercial layer of a technically complex company: positioning, pricing, go-to-market, and capital narrative. The part that is usually stuck. See the commercial layer breakdown →
- A Story the Market Can Repeat
- Positioning simple enough that a buyer can re-explain it when you are not in the room. Complexity does not travel; a repeatable story does. Read why the market buys a story →
- Category as a Proof System
- A category is believed only when proof sits behind it. Declaring a name is free and worth nothing. Build the receipts first, name the category second. Read the category creation piece →
- Compute Reality
- The fact that every AI call has a real, variable cost. Pricing that ignores it erodes margin as usage grows. Read the compute reality piece →
- Usage-Based Pricing
- Charging for what the product consumes rather than per seat, so revenue tracks the variable cost of compute instead of decoupling from it. Read the usage-based pricing piece →
- Session Zero
- The first anonymous visit, before any on-site history exists. The hardest and most valuable moment to personalize. See Session Zero in the Lab →
- Answer Engine Optimization (AEO / GEO)
- Making your content the answer AI engines cite: machine-readable positioning, liftable definitions, and structured pages built for ChatGPT, Perplexity, and Google's AI answers rather than ten blue links. Also called Generative Engine Optimization. This site practices it, down to the llms.txt. See the 2027 CMO guide →
- Agentic Marketing
- Marketing built for a world where AI agents act for the customer: researching, comparing, and shortlisting vendors before a human ever sees your site. The work shifts from persuading people to being legible, verifiable, and quotable to the machines they send ahead. See the 2027 CMO guide →
- AI Referral Traffic
- Visitors who arrive from an AI assistant such as ChatGPT, Perplexity, Claude, or Gemini after it cited or recommended you. Still small next to search, but unusually high intent: the assistant already qualified them before the click. A channel to instrument now, not later. See the 2027 CMO guide →