Token Economics for Non-Technical Teams is here

A hands-on, self-paced course that teaches you to read what any AI workflow actually costs — so you're ready the moment the question comes up.

June 30, 2026

We just launched Token Economics for Non-Technical Teams, and you can start it today. It's a self-paced course that teaches non-technical teams how AI usage turns into cost, risk, and real business value. If you've ever looked at an AI tool and wondered what it's actually costing you to run, this is the course that answers it.

One company recently ran up a roughly $500 million bill in a single month on Claude after missing its usage limits. That number is a sign of where things are headed: AI has become an operating pattern, and operating patterns need someone who can speak to cost and control with confidence

What Token Economics for Non-Technical Teams is

The course takes you from guessing at the AI bill to reading it line by line.

By the end you can look at any AI workflow, read its "receipt," spot the waste, name the right control, and put a rough number on whether it's worth running. You become the person in the room who can answer the cost question instead of changing the subject.

It's nine short modules, about two hours and twenty minutes end to end:

Why Token Economics Matters Now — why AI became an operating pattern that needs an owner.

Why This Matters for Your Role — one shared language across five roles, from worker to leader.

What Are AI Tokens — how text becomes cost, latency, and limits.

Input, Output & the AI Request Receipt — everything a single request actually carries.

Context, History & Memory — why more context isn't better context.

Reasoning & Model Choice — matching the model to the job.

Subscription vs API Economics — why human-paced and machine-paced usage need different controls.

From Prompts to Workflows — how the economics shift as AI starts running the work.

The Monday Shift — the capstone that turns all nine lessons into one habit.

You also get the AI Token Economics Operating Kit: a Workflow Review plus nine copy-paste tools you'll reuse on real workflows long after you finish.

Who it's for

This is built for people leading AI adoption, not the engineers wiring it up. If you're a transformation consultant adding AI to your toolkit, it gives you a solid grasp of cost and risk before a client raises it mid-engagement.

If you're a manager or change agent rolling AI out inside your own organization, it gives your whole team one shared way to talk about what AI is really doing — and whether it's helping or quietly creating rework.

How it works

It's self-paced and on-demand. Start now, move at your own speed, and revisit any lesson whenever you need it. The course is hands-on, not a reading assignment: roughly 70% of your time is spent doing exercises, 20% watching short videos, and 10% reading.

After each lesson you paste a prompt into your own AI model and run an exercise that makes the lesson concrete.

And it’s designed for you to bring your own model. Everything works whether you're on OpenAI, Claude, Gemini, Microsoft Copilot, or your own open-source stack.

Questions you might have

Is this for me if I'm not technical?

Yes — that's exactly who it's for. It's a literacy course with no code, no configuration, and no prerequisites. If you want to wire up model routing and monitoring yourself, though, this isn't that course.

How long does it take?

About two hours and twenty minutes total, across nine short modules. Most module videos run just a few minutes with exercises making up most of the time to complete. And since it's self-paced so you can do it in pieces between other work.

What does "hands-on" actually mean?

After every lesson you get a prompt to paste into your AI model of choice. It runs you through an exercise tied to that lesson, and most exercises ask you to provide answers and judgment rather than just read an output.

What does it cost, and what do I get?

It's $199 for instant, self-paced access. That includes the nine modules, the take-home AI Token Economics Operating Kit, and a Completion Badge.

Won't the AI tools change anyway?

They will, and that's the point. The course teaches the durable operating questions: what context, what model, how it scales, who owns the guardrails, and what value proves it worked. That holds up no matter which app you're in. It's frontier-model agnostic on purpose, so the skill outlasts the tool.