What automated language support actually looks like
Teams spread across countries usually solve language in one of two ways. Either everyone works in English and accepts that some members are operating at a fraction of their normal fluency, or someone bilingual ends up relaying messages and quietly becomes a bottleneck.
Automated language support means neither of those is necessary. In Shavely, translation happens as part of sending a message rather than as a step somebody performs afterwards. A member in Osaka writes Japanese, a member in Manila reads Tagalog, a member in São Paulo reads Portuguese, and none of them did anything except type.
The practical difference is who carries the cost. Where a shared working language pushes the effort onto whoever is least fluent, and a bilingual relay pushes it onto one person, automated translation pushes it onto the system.


