What production taught us about reviewing AI translations
Reviewing translations in real repositories changed what I looked for. A fluent passage could still sit inside a broken Markdown table, leave out part of the source, or overwrite an edit someone had already made.
This article follows how those failures shaped Co-op Translator. Alongside questions about translation quality, I needed checks that could catch structural damage during generation, preserve human edits, retry failed chunks, and leave unresolved failures visible.
Those checks give maintainers a more useful starting point for review. They do not settle whether a translation carries the right meaning. That still needs human judgment.
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