Twenty-eight sessions. One arc.
Four movements, from first line of code to a real deliverable for a real business. Open a movement to find each class presentation.
AI
Engineering
Weeks 1–4. How models actually work, how to build with agents, and how to ship something that runs — ending in an app you present.
Consulting
Weeks 5–8. Scoping a problem, reading a business, and writing down what you are actually going to do — ending in a case-study exam.
The
Engagement
Weeks 9–12. In the field with your partner business, start to finish — scoping, building, training — ending in the build you present.
Buffer
Weeks 13–14. Two weeks held back on purpose — Thanksgiving falls in the first of them. Whatever the semester needs, then the final review.
The Curriculum Research Compendium.
From machine code to agent swarms: the full research foundation behind this curriculum — language history, forward-deployed engineering, software and AI architecture, the development of AI, and the SaaS question. Every chapter cited.
Set up your machine to build.
Four installs, in the order they have to happen — Homebrew, Node.js, Git and Claude — then a bundler and a test runner. The commands, the download links, and what to do when one of them does not work.