AI Glossary
What it means, why it matters to your business, and where it shows up in a real build decision.
In plain terms
Tokens are the small chunks of text that AI models read and generate, roughly three-quarters of a word each, and the unit most AI usage is billed in. Your AI running cost is essentially a token bill. Longer prompts and longer answers cost more, so cost control is a design decision, not an afterthought.
Tokens are to AI what minutes are to a phone plan. You are billed for every word in, every word out, and every system prompt. Volume is what drives the bill.
A team builds a reporting assistant that summarizes 10-page PDFs. At scale the per-report token cost makes the unit economics break. Redesigning the prompt to send only key sections cuts running cost by 70 percent.
Token counting belongs in every AI cost model from day one. Map your typical input and output sizes before you pick a model and before you price any product feature.
You cannot avoid tokens; you can optimize them. Caching repeated system prompts, truncating unnecessary context, and routing simple tasks to smaller models are the main levers.
The primary unit of ongoing AI cost.
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