Open curriculum
Lessons for rooms where AI questions are shared out loud.
The curriculum area turns LLM concepts into teachable units for mixed-experience groups. It avoids product tours and focuses on durable understanding: how systems compose answers, how people can test them, and how institutions should explain the limits of model-assisted work.
Model basics
Prediction, tokens, context windows, training data, and why fluent output is not the same as verified knowledge.
Prompting as instruction
How constraints, examples, role framing, and output formats shape answers while leaving important limits intact.
Sources and retrieval
What changes when a system searches or retrieves documents, and how to review citation claims with care.
Disclosure and governance
How institutions can explain model use, keep records, invite challenge, and protect human accountability.