Guides on localization, translation workflows, and building products for a global audience.
Crowdin, Lokalise, and Phrase are built for teams with a dedicated localization budget. Here's how to tell if you actually need that, or just need a smaller tool.
One-click, whole-project machine translation sounds like it replaces the review step. It doesn't — here's what it's actually good for, and where it can go wrong.
Finding good translators is only half the job. Structuring roles, permissions, and review responsibility is what actually keeps quality high.
Most localization problems aren't translation quality issues — they're process gaps that show up the same way across almost every team.
Open-sourcing your localization work can bring in volunteer translators — but it's not the right call for every product. Here's how to decide.
Treat translations like code: pull the latest strings automatically, fail the build on missing keys, and stop shipping half-translated releases.
The moment you have more than one translator, terminology drift becomes a real risk. A shared glossary is the cheapest fix.
Every platform wants strings in a different shape. Here's what each major translation file format is for and when you'll actually run into it.
AI translation is fast and cheap, but it isn't a replacement for human review. Here's a practical framework for deciding where each one fits.
A practical, four-stage workflow — from string extraction to review — that scales from a two-person side project to a multi-language product team.
The two terms get used interchangeably, but they describe different scopes of work — and mixing them up leads to under-scoped projects.
Localization is more than translating strings. Here's what actually goes into shipping a product that feels native in every market you support.