Programming is an increasingly global profession, and developer tools are finally catching up. On Wednesday, Amazon Web Services (AWS) announced new language supports in Q Developer, its coding assistant, to better serve its global user base. Amazon says the assistant can now deliver feedback accurately in multiple languages, creating a familiar work environment for developers of all backgrounds.

For much of its history, software has been rooted in English -- a reality that gives primarily Western, English-speaking developers an upper hand. To address this, companies behind consumer AI tools have begun to roll out regional and language-specific products to improve usage amongst non-English-speaking communities. Some tools even change accents in real-time. 

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While the code itself still functions in English, Amazon Q Developer's adjustment aims to expand accessibility for the surrounding parts of a developer's workflow. 

"By expanding language support, Amazon Q Developer now enables developers to have more natural, fluid conversations about complex technical concepts in their preferred language, whether they're designing system architecture, generating documentation, or planning application localization strategies," AWS architect Brian Beach wrote in the announcement. 

To demonstrate, Beach asked Q Developer the same question in English, Chinese, Hindi, and Spanish. The assistant responded in all four languages and maintained "technical accuracy while adapting to linguistic nuances," Beach said. Q Developer also keeps follow-up questions and responses in the user's selected language, removing the barrier of constant back-and-forth translation from their workflow. 

Beach also showed how he could ask Q Developer to add comments to his code in French.

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Expanded language support is available now for Free and Pro users in the integrated development environment (IDE) and command line interface (CLI) and will soon be available in the AWS Management Console.

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• How to remove Copilot from your Microsoft 365 plan
• How to install an LLM on MacOS (and why you should)