GuideAdvanced
AI Economics: Budget, Cost, and Price Guide
AI is no longer a small line in the budget. Team tools are billed by consumption, the AI features in the product are paid per token, and the bill can grow much faster than revenue without anyone deciding it should. This guide teaches you to make the economic decisions about AI with numbers: how much to spend on team tools and on product features, how to read a token invoice, how to set ceilings and a budget per team, how to calculate cost per result instead of cost per call, how to translate that cost into margin, which pricing model to use for an AI feature, how to build worst-case scenarios, when to switch models or providers because of cost, and how to defend the budget in front of finance. You learn it as CTO of **Faro Legal**, a legal SaaS for law firms in Mexico, Colombia, and Chile, with 35 engineers and two AI features: contract summaries and the case file assistant. In six months the AI bill grew 177% while revenue grew 20%, gross margin fell from 80% to 73%, and the CFO asks in the leadership meeting how much the company will spend in 2027 and whether every summary it sells makes money. Module by module you build the answer: a cost diagnosis, a team budget, a unit cost sheet, a margin model, a pricing proposal, a scenario plan, and a model decision memo. There is no code to write. The math is done in tables and by hand, the model prices in the case are stated assumptions, and outside figures come with their source and date.
- lessons
- 64
- modules
- 8
- available in
- English · Spanish
- access
- Free
What you'll be able to do
- Separate the team's AI bill from the product's and read a token invoice line by line
- Explain with a cost bridge why the bill grew: volume, price, and waste
- Build an AI budget per team with ceilings, alerts, and exceptions
- Calculate cost per result and find the waste you pay for without getting anything
- Translate AI cost into gross margin per user, per segment, and per customer
- Choose a pricing model for AI features: subscription, credits, usage, hybrid, or outcome-based
- Build worst-case scenarios and thresholds that trigger decisions
- Decide when to switch models or providers because of cost without breaking quality
- Deliver an AI economics plan and defend it in front of finance and the board
What you need to bring
It's for you if...
- Startup CTOs and technical founders who answer for the AI bill
- Heads of engineering and product, directors, and VPs who need to budget for AI
- Tech leads and engineering managers in charge of their team's spend or of an AI feature
Requirements and materials
- Answering, or being about to answer, for a budget or a product feature
- Knowing what a language model is as a user; no programming needed
The syllabus, module by module
Open any of them to see its lessons.
What people usually ask
No limit. It's a free guide: come in whenever you like, as often as you like.
No. Modules run from easier to harder, but you can jump to the one you need. Progress is saved per lesson.
Whatever is needed is listed under “What you need to bring”, above. If nothing is listed there, you can start from zero.
In the WhatsApp group, and every two weeks there's a live with an instructor where questions get worked through.
Start whenever you like
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