More rules should mean better output. That's the intuition. I spent weeks building a comprehensive CLAUDE.md — 200 lines covering naming conventions, security rules, error handling, architectural patterns, import ordering, type safety requirements, and more. I was proud of it. I'd thought through every scenario. Then I scored the output. 79.0 / 100. My carefully crafted documentation was actively
I've been shipping software internationally for 5 years, and I've seen localization bugs tank launches in ways that make deployment failures look quaint. Currency displays in the wrong locale. Dates that make Japanese users think the app was built in 1970. Phone numbers that break form validation in Brazil. Last week, I decided to actually test TestSprite on a real project instead of adding it to
description: "Critical issues blocking TestSprite adoption in Indonesia, Malaysia, Philippines. Production fixes included." tags: testsprite, testing, devops, indonesia, localization cover_image: "https://dev-to-uploads.s3.amazonaws.com/uploads/articles/testsprite_mcp_review.png" canonical_url: "" published: false Code Review: Why TestSprite's MCP Failed in Southeast Asia (And How to Fix It) TL;DR
TestSprite adalah platform testing yang fokus pada quality assurance untuk aplikasi modern. Setelah menggunakan TestSprite dalam satu proyek production-grade di berbagai device dan region, saya ingin share pengalaman mendalam tentang bagaimana tool ini menangani localization dan timezone handling — aspek yang sering diabaikan tapi krusial untuk aplikasi global. TestSprite memungkinkan developer un
description: "Real-world TestSprite evaluation testing Indonesian e-commerce with IDR currency, timezone handling, and 3 locales. Grade A review with technical findings." https://images.unsplash.com/photo-1516321318423-f06f70a504f0?w=1200&h=600&fit=crop" TL;DR: TestSprite is 80% faster than manual visual regression testing. Grade A for multi-locale apps. Grade B+ for logic testing. Real findings:
Have you ever looked at code you wrote six months ago and thought: "Who wrote this monster?"? Relax, it happens to all of us. In software engineering, writing code that a machine understands is the easy part. The real challenge is writing code that other humans (including your future self) can understand, maintain, and scale. This is exactly where Software Design Principles come into play. In this
Part 1 of 5 in The New Engineering Contract — what it means to lead engineers when AI is doing more of the coding. SWE-CI tested 18 AI models across 71 consecutive commits. Most broke something on commit 47 they'd already broken on commit 1. That's not an intelligence problem. That's a learning system that isn't learning. A paper made me uncomfortable this month. Not because of what it found about