{
  "id": 10247516,
  "title": "The Translation Was Still There. That Was the Bug.",
  "url": "https://urgent.news/2026/09/27/the-translation-was-still-there-that-was-the-bug",
  "topic": "tech",
  "section": "Tech",
  "published": "2026-09-27T16:22:29.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/msalways/the-translation-was-still-there-that-was-the-bug-3e54"
  },
  "original_language": "en",
  "account": "The bug lay hidden within the translation. Despite the app building without issue, the French and German strings had transformed into something no longer reflective of the product's actual content. This peculiar issue arose from Translatron's core function: translating source strings into target languages. Initially, the tool's main goal was to generate accurate translations using large language models. However, as Translatron evolved, the real challenge shifted. Crafting translations that would seamlessly fit into a product, which constantly undergoes changes, proved to be a complex task. A simple string like \"Continue\" could signify anything from continuing checkout to onboarding or even reading. The original string alone didn't provide enough context to grasp its significance. Similarly, certain product rules, such as whether a term like \"Workspace\" should be translated or remain unchanged, were influenced by historical decisions made by the team. A translation isn't just an end product; it's the result of specific assumptions made during the translation process. When these assumptions change, the translation may require reevaluation. If they remain the same, regenerating the translation could be unnecessary and potentially detrimental. Translatron has been progressing towards identifying what was affected, updating those translations, and leaving unrelated or intentionally edited content untouched. The name itself, Translatron, carries a Transformers-inspired meaning. Initially, the name was a playful reference to the idea of one language transforming into another. However, the tool's functionality has shifted towards a more precise approach: determining what genuinely requires change and transforming only that which needs it. The principle has become: transform what needs transforming and preserve what doesn't. This transformation has led to a new perception of Translatron, moving it away from being an AI translator and towards a localization compiler. In essence, when something changes, Translatron identifies the affected output, regenerates the necessary pieces, and validates them, while everything else remains unchanged. This approach ensures an ordinary JSON output for the application, maintaining predictability amidst uncertainty. Translatron is open source at [github.com/Msalways/Translatron](https://github.com/Msalways/Translatron). For those who have encountered localization challenges in production environments, the author expresses curiosity about how their team determines when an existing translation needs another review.",
  "summary": "I changed a checkout button from Pay now to Continue to payment . Nothing failed. The app built normally, the translation keys were still present, and every locale file was perfectly valid. But the French and German strings were now translations of something the product no longer said. That is a strange kind of bug because, from the application's point of view, there is no bug at all. That…",
  "key_points": [
    "Bug hidden in translation process",
    "Translatron evolved to localization compiler",
    "Tool identifies affected outputs, preserves unchanged content"
  ],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}