AI Training System
How to teach yourself or a team to use AI — limits, data rules, role practice, verification, and workflows that stick.
1. Start here
AI training shouldn't start with "here are 50 AI tools." It should start with: what work do you already do that AI can help you do faster, better, or with less friction? Nobody needs to become a machine-learning engineer — they need to know what AI is good at, what it's bad at, how to give it context, how to review output, and what data never to share.
The goal isn't AI excitement. The goal is AI capability.
2. The training system
The curriculum runs through six skills in order: learn the limits, protect data, prompt better, practice with realistic role exercises, verify output, and save what works. Each skill comes with repeatable exercises built on real workflows, not toy demos.
3. Make it stick for a team
For groups, the system adds shared data rules, a shared workflow library, and review habits — so AI skill becomes part of how the team operates instead of one enthusiast's side project. Useful experiments graduate into team SOPs.