The University of Mississippi told every department to write its own AI policy this semester, and the guideline names generative, assistive and agentic AI separately, in every course component. Most syllabus policies name one. Here is what the other two columns have to say.
Three student facing AI products shipped in forty eight hours, and two of them read a syllabus as structured data. Extraction is lossy. Here is what falls out of your course and what to do about it in week one.
Anthropic began marking Claude output on August 2, and the mark travels worldwide. Read the documentation and it says the content may have been processed by Claude. May. Processed. Not wrote. Here is what to ask students for instead.
A UCL professor says universities moved too quickly and too slowly at once. Manchester answered with a four value scale applied per assessment. Stellenbosch refused to write one rule at all. Both beat the one page policy, and the mechanism works outside a university.
The largest US teachers union just asked schools to keep AI out of elementary classrooms. Read past the headline and it becomes a lesson in teaching AI literacy in the right order.
Norman Eng’s new Faculty Focus framework offers four evidence-based questions for deciding when AI belongs in a classroom. The questions are sharp. The missing piece is the integration model for what happens once you say yes. Here is how SeedStacking fills that gap.
The AI cheating debate focused on students for three years. Teacher evaluation portfolios face the same integrity question, and nobody is asking it. The answer changes everything about how we evaluate professional competence.
A Harvard professor’s argument first framework for AI shows every educator what works: clear ground rules that force students to think before they prompt, turning AI into an accelerator rather than a shortcut.
AI literacy education built on the SeedStacking™ methodology. Small daily wins that compound into genuine fluency.
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