Teacher workload, AI in education, and practical strategies for reducing planning time.
A worked example does more for a struggling student than ten minutes of you talking. Here's how to build them so they actually land.
Most learning intentions are either too vague to be useful or so bloated they read like a syllabus dot point. Here is how to write one that actually helps students learn.
Most teachers know the model. Fewer notice how easily it collapses into 'I mention, you struggle, we run out of time.' Here's how it breaks and how to fix it.
Explicit instruction lives or dies on one thing: knowing whether students actually got it before you move on. Here's how to build that into every lesson.
Most AI planning tools say they follow good teaching practice. None of them prove it. We built the rulebook of explicit instruction into the software — so every lesson is checked, and rebuilt if it falls short, before a teacher ever sees it.
I did not build SSA from a product roadmap. I built it from conversations with real teachers who told me exactly what was broken, what they needed, and what every other tool got wrong.
AITSL data shows full-time teachers work a median 50+ hour week. Close to 1 in 3 are thinking about leaving. Here is what the data actually says — and what schools can do about it.
Schools are adopting AI whether leaders plan for it or not. The question is whether the tools teachers use actually meet curriculum standards and reduce workload — or just create different problems.
Most attempts to reduce teacher workload add a new system, a new tool, or a new process. Here is how to actually cut planning time without creating a new burden.
Teachers are already using ChatGPT. But generic AI produces generic lessons — no verified outcome codes, no scope context, no student differentiation. Here is what purpose-built looks like.
Generate your first NESA-aligned scope and lesson plan in minutes. Free to start.