This course teaches measurement, caching, and model choice so your AI feature stays affordable.
Includes practical lessons, exercises, and a clear next step after you enroll.
About this course
Curriculum
Lessons are listed in order. Each one has a goal, a walkthrough, practice, and a short check before you continue.
- 01Where the money actually goesTokens, retries, tools, and idle features — not just the sticker price.
- 02Measure before you cutUnit cost, quality, and latency on the same dashboard.
- 03Routing: cheap when you can, expensive when you mustA small model first, a large model on hard cases.
- 04Caching and context dietDo not pay twice for the same prompt, and do not paste the novel.
- 05Quality after the cutA harness so “cheaper” does not mean “worse” in production.
- 06A cost budget the team can live withCaps, alerts, and an owner — like any other production spend.
- 07Workshop: a complete pass on a real taskCombine the earlier lessons into one working example you can keep.
- 08Quality bar, common mistakes, and a 30-day planLock in a checklist so the skill survives after the course ends.
- 09Measure results so you know the work is actually betterAdd a simple evaluation so quality and cost are not guesswork.
- 10Ship it: handoff, monitoring, and the next projectPut the workflow where other people can use it without you in the room.