The correct option is Maintaining code comments in several human languages at the same time.

This choice produces the least measurable productivity improvement because comments are internal developer aids rather than shipped artifacts, and maintaining parallel translations adds overhead without improving the product. Automated translation can introduce subtle inaccuracies that drift over time, and keeping multiple comment languages synchronized across branches and pull requests slows reviews and increases merge churn. Teams usually pick a single working language or rely on on demand translation for occasional comprehension, which avoids ongoing duplication work.

Automatically translating product manuals and API documentation between human languages is likely to deliver clear benefits because these documents are user facing deliverables. Translation expands reach, reduces manual rewriting, and scales with human review to improve throughput and coverage across regions.

Generating localized error messages for a globally used application directly improves user experience and support outcomes. Automating string translation within a standard localization workflow lets teams cover many locales quickly and consistently, which reduces developer effort while increasing quality for users.

Understanding and contributing to a repository where commit messages issues and review comments are written in a language the developer does not read removes a comprehension barrier that would otherwise block work. Machine translation here enables developers to read and respond to issues and pull requests promptly, which accelerates collaboration and throughput.

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