A backend developer is gazing at forty lines of legacy JavaScript that she didn’t write, can’t completely read, and must explain to a product manager in a meeting at nine the next morning somewhere in an apartment in São Paulo at eleven o’clock at night. Portuguese is her native tongue. Her second language is English, which is useful but requires work when it comes to technical aspects. The syntax she reads all day is, in a sense, her third. She launches GitHub Copilot, pastes the block, writes “explain this,” and in a matter of seconds, she receives a paragraph outlining the code’s functionality in simple, understandable English.
It’s not flawless, but it’s sufficient to get started. She develops her explanation, closes the laptop, and rewrites it in Portuguese for her personal notes. This isn’t a way to increase productivity. No one in the Silicon Valley press release circuit tends to put it quite that way, but for a large segment of the world’s developer labor, it is a daily reality.
English is the language used in the programming industry. The core languages, the main APIs, the Stack Overflow answers, and the official documentation—nearly all of it published first and mostly in English—are examples of cumulative history rather than intentional exclusion. The vast majority of the approximately 28 million software engineers that are employed globally are working in a language that their minds do not turn to when they are exhausted, frustrated, or lost in a new codebase.
Even though it’s rarely acknowledged in public, the cognitive cost of this is real and quantifiable. Learning to read and write code in a second language does more than merely slow you down. It causes a particular type of mental exhaustion that worsens over the course of an eight-hour shift, impairing judgment, causing errors to go unnoticed, and ultimately making documentation seem unachievable.
More subtly and effectively than most of the marketing surrounding them indicates, AI copilots have created an on-demand translation layer between language and logic. A developer can mentally translate a dense function into their native language with much less effort than parsing the raw syntax directly thanks to GitHub Copilot’s “Explain” feature and comparable features in programs like Tabnine and Amazon CodeWhisperer.
The primary purpose of these instruments was not to accomplish this. They were designed for speed, suggestion, and autocomplete. However, multilingual developers discovered the explanation use case primarily on their own, and as a result, usage has slowly increased across teams in Brazil, India, Eastern Europe, and East Asia.
This is especially helpful and challenging to replace when dealing with the legacy code issue. It is difficult for any developer to come upon an undocumented codebase that was written five or 10 years ago, complete with peculiar naming conventions and missing comments. It may seem truly unbreakable to someone whose English reading comprehension suffers under strain.
Here, AI functions more as a patient explanation than a collaborator, working through the reasoning step-by-step without passing judgment and available around-the-clock without the difficult social situation of asking a senior colleague to explain anything for the third time.
The extent to which AI solutions genuinely reduce the equity gap in multilingual development teams as opposed to merely mitigating individual annoyances at the margins is still unknown. There is a plausible argument that a better explanation button won’t address the underlying issue, which is the English-first documentation culture and the almost complete lack of non-English API name conventions.
However, given the speed at which bilingual developers have embraced these tools for uses that their authors did not specifically foresee, it seems as though there has always been a need for something adequate to satisfy it. The instruments are not flawless. The workaround remains a workaround. However, it’s the difference between being prepared and stuck in an apartment in São Paulo at eleven o’clock at night.
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