About this course
Most teams do not fully understand how AI and cloud costs work until something goes wrong. Token billing, context windows, model tiers, and provider-specific pricing all interact in ways that make spend hard to predict. This course walks you through the cost model from first principles, shows you what drives spend in practice, and teaches you how to set up the monitoring that catches changes before they become surprises.
What you will learn
- How token billing, context windows, and model tiers affect your monthly spend
- Which cost signals matter day to day vs which are noise
- How to set up production monitoring that gives you daily visibility
- Why relying on provider dashboards alone creates blind spots
How to use this course: Work through the modules in order for the full picture, or jump to the lesson that matches the problem in front of you right now. Each module is a standalone read — estimated total time is 28 minutes.
Course modules
3 lessons · 28 min total read time
How LLM pricing works
Understand token billing, context windows, and why a small product change can move spend quickly.
How to track LLM usage in production
Measure requests, token usage, and cost by provider, service, and category instead of relying on provider dashboards alone.
Monitoring AI infrastructure in production
Set up the minimum monitoring stack for daily visibility, cost spikes, and weekly review handoffs.
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