Industry
Cheap should mean stricter, not looser
The assumption that cheaper AI must mean looser standards has it backwards. Vagueness is what forces you to buy scale; precision about what good looks like is what makes small models sufficient.
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Perspectives from aime.
Essays on the economics of educational AI, the shifting architecture of the model landscape, and what it means to build for cost-sensitive, sovereignty-conscious environments. New piece every Tuesday.
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Society
Teacher cognitive load is now a political variable
Teacher workload has moved from a wellbeing footnote to a system-level political variable. Ministries that treat teacher cognition as national infrastructure will out-perform those that treat it as an HR problem.
Education
Curriculum is the missing data layer of education AI
Every conversation about AI in education assumes curriculum exists as usable data. It doesn't. Until curriculum becomes structured, machine-reasonable intelligence, no AI system can do more than generate around it.
Policy
Sovereignty is not a slogan: what it actually means to own an AI system
Sovereign AI is becoming a marketing term. Real sovereignty is operational: data residency, weight custody, curriculum ownership, audit rights, exit provisions and offline operation. A procurement-grade definition.
Industry
The post-API era: why AI's next phase looks more like databases than search
The first phase of commercial AI was API-as-product. The next phase looks more like the shift from time-sharing to owned databases — buyers stop renting intelligence when the intelligence becomes strategic.
Industry
The thirty-billion mistake: when edtech mistook engagement for learning
$30 billion a year of edtech spend, limited evidence of effectiveness. The diagnosis: the category optimised engagement and called it learning. The next category will be measured on outcomes against curriculum, not minutes on platform.
Industry
Why the AI debate sounds one-sided — and what's actually happening underneath
The frontier-model conversation dominates the headlines, but a quieter shift toward small specialised models, agent orchestration and local inference is reshaping the economics of AI — especially for education and emerging markets.