High-impact AI output must always be reviewed by a person before use. Automatic feedback and recommendations on the platform are advisory and never replace human judgement.
The learning loop
1Learn Task-oriented modules with ungraded self-checks
2Practice Realistic meeting notes, datasets and notebooks
3Assess Server-scored pre- and post-tests make learning visible
4Apply Turn what you learned into a Use Case or Canvas for your own work
Task-oriented
Courses are designed around real work tasks rather than tool features. Practice files contain simulated teaching data.
Verification and responsibility
Courses repeatedly practice separating fact, analysis and unknowns, checking sources and numbers, and reviewing AI output before handing it on.
Course progression
Courses have four levels: Foundation, Core, Advanced and Architecture. Learning Paths suggest an order; prerequisites are recommendations and are never enforced.
