When someone asks you what AI is really costing you, will you have the answer?
A hands-on, self-paced course that teaches you how AI usage turns into cost, risk, and real business value — enabling you to read any AI workflow’s receipt, spot the waste, and name the controls needed. No coding experience is required, and the lesson works with any leading AI model including ChatGPT, Claude, Gemini, and Microsoft Copilot.
Learn how to manage the true cost of AI workflows and automations.
If you lead AI transformations, you already feel where AI is heading. It has stopped being a side experiment and become part of how all work gets done. And somewhere in every engagement, a critical question is being asked — “what is this actually costing us, and who’s responsible?”
For some clients, it comes up on day one. For others, it stays quiet while everyone chases the upside, right up until a bill, a security review, or a runaway workflow drags the question into the room. Either way, it comes up.
Here’s the warning shot the whole industry saw: one company ran up roughly $500 million in a single month on Claude after missing its usage limits. Read that as a signal of where things are headed. AI is now an operating pattern, and operating patterns need someone who can speak to cost and control without hand-waving.
You don’t want to be the person in the room learning this for the first time while the bill keeps rising.
What you’ll learn
Read the receipt.
See everything a single AI request carries that costs tokens: prompt, documents, history, instructions, output.
Spot the waste.
Recognize what quietly inflates usage: bloated context, the wrong model for the job, and conversations that should have started clean.
Name the right control.
Match the moment to best practices — limits, monitoring, ownership, model routing, or human review — and know which one the situation calls for.
Tell human-paced from machine-paced.
Understand why a workflow running thousands of records through an API behaves nothing like a person using an assistant, and why each needs a different governance lens.
Rough out ROI.
Connect usage to outcome and put a defensible number on whether a workflow is worth it.
Who should take this course
This is for you if you lead transformations.
You’re a partner or consultant adding AI to a practice that used to be all lean-agile. You don’t need to be the deepest technical expert in the building, but you need to walk the walk on AI cost and risk the moment a client raises it.
This is for you if you’re rolling out AI from the inside.
You’re a manager or change agent putting AI tools and workflows in front of your own teams, and you need to know whether it’s actually improving work or quietly creating rework — plus a shared language your whole team can use to talk about it.
This isn’t for you if you’re looking for a technical build.
If you’re an engineer who wants to configure model routing, write the integrations, or stand up the monitoring stack yourself, this isn’t for you. This course makes you fluent in the operating questions, and it won’t leave you able to build a custom cost dashboard.
How the course works
Enroll to get instant access at $49.
Start on your own schedule — no cohort, no deadlines, no time pressure.
Complete the course
by moving through nine short lessons (most videos run under a few minutes) built around three modes: doing, watching, reading, but weighted toward doing. After each lesson you run a copy-paste exercise in your own model. You earn a completion badge upon finishing the course.
Apply it Monday morning
by using the AI Token Economics Operating Kit — a Workflow Review plus nine copy-paste tools. Monday morning, take a real AI workflow (yours or a client’s), run the review on it, and produce a one-page operating snapshot: what it costs, where the waste is, what controls it needs.
AI fluency is the new professional standard.
Being able to read the bill isn’t about counting tokens for their own sake. It’s about being the person who can look at any AI workflow and confidently say what it costs, where the risk sits, and whether it’s worth it. That fluency used to be optional. As AI moves from prompts to workflows to agents, it’s becoming the price of being taken seriously in the conversation.
