Originally published on AI Tech Connect.
Two problems that look like one Teams building for both markets usually file this work under "internationalisation" and hand it to whoever is least busy. That framing hides the fact that the two halves have almost nothing in common. Serving Hindi, Tamil or Bengali is an economics and capability problem. The model can probably do the task, but the same meaning consumes several times more tokens, which raises your cost, eats your context window and lengthens your latency. No amount of prompt engineering fixes a tokeniser. Serving British English is a control problem. The model can produce perfect en-GB output, and will still drift back towards American spelling over a long generation because the underlying distribution pulls that way. It costs nothing extra and fails constantly. They need…
