Where a couple of years of this gets you
Curious
You've heard gamification works. You're not sure which bits, or whether AI belongs anywhere near it.
Playing
You run one mechanic with one class. It half works — which is exactly what it's supposed to do.
Designing
You stop bolting points onto lessons and start building for motivation instead of compliance.
Judging well
You can tell a genuinely useful AI workflow from a lazy one in about thirty seconds.
Teaching it
You're the person colleagues come to before they trial something new.
In every issue
Four pieces, always in the same order. No think-pieces, no thirty-slide frameworks, no breathless takes about the future of education.
The mechanic
One idea you can use immediately
A single game-design move sized for a real lesson — quests, streaks, XP for effort, respawns instead of red pen. You get the setup, the way it usually goes wrong, and how to tell if it worked.
Ethical AI
One tool, with the ethics attached
A prompt or workflow worth your prep time, and the honest caveats beside it: what it does with student data, where it quietly gets things wrong, and what you should tell your class.
The read
One article, reviewed
Something doing the rounds, read properly — what it gets right, what it overclaims, and whether it earns your twenty minutes.
The field notes
What actually happened
Short accounts from educators who tried the thing — what they changed by week two, what they dropped, and the small stuff nobody writes up. Specific enough to steal.
What an issue looks like
Here's the shape of a typical issue, so you know exactly what you're agreeing to before you hand over an email address.
Everything is written for a real timetable — the mechanics assume you have a class in forty minutes, and the AI sections assume your school has rules you have to live inside.
The Meadows Mindset
Example issue · about 4 minutes
The mechanic
The Respawn Rule
Retakes that cost something small — so a second attempt still means something.
Ethical AI
Marking with a model
A rubric-first workflow, and the three places it reliably drifts from your judgement.
The read
One article, reviewed
Something doing the rounds, read properly — what it gets right, what it overclaims, and whether it earns your twenty minutes.
The field notes
Two weeks in a Year 8 science room
What one teacher kept, what they binned, and the bit that surprised them.
Where this newsletter stands on AI
Plenty of people will sell you a prompt pack. These are the lines every recommendation here is held to — including when that means telling you not to use something.
Students first
Learning goals lead and tools follow — never the other way round. If a mechanic only makes a spreadsheet look better, it doesn't go in.
Student data stays out
Nothing here asks you to paste identifiable student work into a tool that trains on it. Where a workflow needs real work, we say how to strip it first.
Disclosure over deception
If AI touched it, say so — and that cuts both ways. Modelling honest use is most of what we're actually teaching here.
Points are not motivation
Gamification done badly buys compliance and calls it engagement. We're blunt about which mechanics do that, and when to take one away.
Written for anyone who works with learners
If part of your job is getting someone to care about something difficult, you're in the right place.
Classroom teachers
Primary through secondary
Coaches & school leaders
Rolling this out across a team
Higher ed & L&D
Lecturers, trainers, course designers
Tutors & youth programs
Homeschool, clubs, after-school
Start with the next issue
One email every Tuesday. Confirm your address and you're on the list.