Short essays and longer pieces on AI capability, teaching, and the tooling that makes it all work. Open to everyone.
What AI detectors for teachers actually measure, why false positives happen, and a classroom-tested framework for handling suspected AI-generated work without turning every assignment into a trial.
A plain-English guide to the difference between an AI model and its harness, why Claude Sonnet 5 and Fable 5 matter, and how Chat, Cowork, and Code create different agent experiences.
A practical guide to developing an AI-first mindset: treat AI as a teammate, reimagine experiences, redesign workflows, and build a personal AI toolkit.
A plain-English guide to AI benchmarks, who creates them, how they are developed, what major benchmark categories measure, and why benchmark scores need context.