Thinking
Short, practical writing on the decisions that make systems actually ship. Six notes, each with a full article below.
A demonstration proves a model can do something once. Production asks whether it can do it repeatedly, unsupervised, and at an acceptable level of quality. That gap is where most AI initiatives stall.
Automation succeeds or fails at the handover to a person. The question is where to put that step, and what the reviewer actually needs to see to decide quickly.
When reporting numbers diverge, the problem is usually ownership of the definition rather than tooling. Fix the definition before you fix the chart.
When your tools speak your language, your productivity speaks for itself. Yet for decades, African languages have been treated as an afterthought by the global hardware and software industry.
From Nairobi to Lagos to Cairo, offices across the continent are rethinking what it means to work in your mother tongue. At the center of this shift are companies like Boyeg, building technology and services that make African languages viable in the modern workplace.
Geez. Tifinagh. Nsibidi. Africa's writing systems are ancient, beautiful, and overdue for their digital moment. Today, initiatives like Boyeg are helping bring these scripts into the modern workspace by aligning cultural heritage with contemporary technology.
Six notes on the decisions behind the systems we build. Each article explores a practical challenge: moving from AI demo to production, designing human-in-the-loop checkpoints, fixing metric definitions before the dashboard, plus how linguistic diversity shapes office technology and how history moves digital scripts into modern use.
Tell us what you are stuck on and we'll consider covering it in a practical note.