AI total cost of ownership and lock-in
On This Lesson 4 topics
This lesson is planned. The outline below lists the topics it will cover. The full lesson has not been published yet.
In this lesson
build a multi-year cost model and plan the exit.
Planned topics
- Drivers: tokens or GPU hours per request, requests per user, growth, evaluation, human review, and staffing.
- Prices and models change quickly; model scenarios, and verify current rates before use.
- Lock-in sits in prompts, fine-tunes, vector indexes, and provider-specific features.
- Keep an abstraction, an evaluation suite, and a second option to make switching affordable.
Draft outline details
Demonstration
a three-year cost sheet: usage assumptions, unit costs, caching savings, review effort, staffing, with a price-change sensitivity and an exit plan row.
Check your understanding
What helps you switch providers later?
Show answer
An abstraction layer and an evaluation suite that tests a new model quickly.
Practice
Apply this lesson with the module's lab, exercises and quiz.
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