Localizing Mobile Apps: The Complete Guide for iOS and Android
String extraction, plural handling, layout issues, RTL support, and app store listing translation for iOS and Android apps.
Writing
Technical writing on translation APIs, i18n patterns, and localization engineering.
String extraction, plural handling, layout issues, RTL support, and app store listing translation for iOS and Android apps.
A step-by-step tutorial for automating translations with react-i18next, i18next-parser, and a translation API. Extract, translate, and commit — no manual work.
How context transforms translation quality: disambiguating polysemous words, maintaining tone, and API patterns for sending context to translation engines.
The i18n advice you actually need: string concatenation traps, RTL layout gotchas, complex plural rules, and hardcoded error messages that will bite you in production.
How LLM-based translation compares to traditional NMT on WMT benchmarks, real-world A/B tests, and which language pairs still favor conventional models.
Which content to translate first, how to prioritize languages, hreflang implementation, and the 80/20 of multilingual SEO — without scaling your content team linearly.
Practical guide to multilingual docs with Docusaurus, GitBook, and MkDocs: directory structure, automated translation pipelines, versioning, and URL strategies.
System prompts, formality controls, glossary injection, few-shot examples, and markup preservation techniques for high-quality LLM translation.
How to translate Markdown and MDX files without breaking formatting, links, code blocks, or frontmatter. AST-based parsing, segment extraction, and reassembly.
How to parse, extract translatable segments, translate via API, and write back .PO, .XLIFF, and .ARB files with metadata intact.
Why translating user-generated content is harder than translating curated text: slang, typos, code-switching, offensive content, and latency constraints.
A practical evaluation checklist for translation APIs: language coverage, pricing models, rate limits, latency, caching, glossary support, format handling, and more.
Practical patterns for dealing with translation API rate limits: exponential backoff, token buckets, circuit breakers, request queuing, and fallback chains.
Hard numbers on translation pricing in 2026: professional human translators, NMT APIs, LLM-based translation, and hybrid workflows with a comparison table.
A practical breakdown of BLEU, COMET, BLEURT, and human evaluation for measuring translation quality — what each metric captures, its blind spots, and how to set up automated quality checks.
How to set up a continuous localization pipeline that translates new strings automatically, validates output, and ships with every deploy.
A practical guide for startups that need to ship in multiple languages without dedicated translators, localization engineers, or a big budget.
A comparative analysis of the three main React internationalization libraries, with code examples, bundle size analysis, and recommendations.
How to set up internationalization in Next.js App Router using next-intl, including middleware locale detection, route prefixing, and automating translations.
What BYOK means for translation APIs, why it gives you more control over costs and models, and how the architecture works.
Rate limiting, retry strategies, queue architecture, and cost optimization for translating large volumes of text through translation APIs.
How to build a real-time translation pipeline for chat applications using WebSockets, caching, and translation APIs.
Working code examples for translating text using Python, Node.js, and cURL with multiple translation APIs including Google, DeepL, and auto18n.
A step-by-step guide to detecting changed keys, translating deltas, and writing back translated JSON files automatically in CI/CD.
How to design a translation cache with proper key structure, invalidation strategy, and the cost savings math to justify the effort.
An analysis of DeepL API pricing at scale, its hard limits, missing features, and when it makes sense to look at alternatives.
A technical comparison of Google, DeepL, Amazon, Microsoft, LibreTranslate, and auto18n — with code samples, pricing, and honest tradeoffs for each.
A walkthrough of migrating a production app from Google Cloud Translation to LLM-based translation, covering quality improvements, cost changes, and implementation details.
A technical comparison of DeepL and Google Translate APIs covering auth, request format, pricing, language support, and translation quality.
A real breakdown of Google Cloud Translation API pricing tiers, the free tier trap, Neural vs Basic models, and what your bill will look like at scale.