This capstone-style course connects the full stack so you can ship a real AI product, not just demos.
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.
- 01The product thesis in one pageUser, job, wedge, and why a model is required.
- 02Experience: the loop the user repeatsInput, wait, result, edit, save.
- 03System: retrieve, generate, tools, evalThe four boxes behind the loop.
- 04Quality and cost as product specsSLOs for task success, latency, and unit cost.
- 05Launch: canary, support, and the kill switchA real launch, not a tweet.
- 06Iterate: the backlog after v1Eval failures, cost, and the next job in the thesis.
- 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.