Four destinations
Learning paths
Start with the capability you need. Move at your own pace. Finish with evidence you can reuse in a real project.
01
PATH 01 · Start here
Practical AI foundations
Learn what current AI systems can help with, where they fail, and how to turn a broad idea into a small learning exercise.
- A plain-language capability map
- One bounded job brief
- A review and stop rule
02
PATH 02 · Builder
Build a reliable AI assistant
Design an assistant around approved knowledge, a visible instruction set, representative tests, and a clear escalation path.
- An instruction contract
- A five-case evaluation set
- A sourced response and escalation pattern
03
PATH 03 · Operator
Automate a repeated workflow
Map a repeated job, choose the right boundary between deterministic automation and AI judgment, then rehearse exceptions.
- A current-state workflow map
- A trigger, action, and review design
- A failed-run recovery rehearsal
04
PATH 04 · Advanced
Ship and operate an AI tool
Move beyond the demo by assigning ownership, protecting data, measuring failures, and planning rollback and exit.
- An environment and access map
- A production launch gate
- An operating and change record