We Ditched Terraform 1.10 for CloudFormation: Reducing IaC Complexity for Our Small AWS Team We’re a 4-person engineering team managing 32 AWS resources across dev, staging, and production environments for a B2B SaaS product. For 18 months, we relied on Terraform 1.10 to manage our infrastructure as code (IaC). But by Q3 2024, the overhead of maintaining Terraform outweighed its benefits for our
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
War Story: I Ditched My CS Degree for a Bootcamp and Became a Go 1.25 Engineer I never thought I’d be writing this. Two years ago, I was three semesters into a traditional Computer Science degree, drowning in abstract calculus and outdated Java curriculum, wondering if I’d ever write code that actually mattered. Today, I’m a backend engineer working full-time with Go 1.25, building low-latency m
Opinion: We Ditched All Third-Party Mobile SDKs – Cut App Startup Time by 30% for iOS 18 When iOS 18 launched, our team braced for the usual post-release performance tweaks. Instead, we hit a wall: our flagship app’s cold startup time had crept up to 2.8 seconds, well above Apple’s recommended 1.5-second threshold for optimal user retention. After months of debugging, we made a radical call: rem
In Q1 2026, our team audited 14 2FA libraries for Next.js 15 and found that migrating from Google Authenticator’s legacy TOTP implementation to Speakeasy 2 reduced average 2FA setup time per user from 42 seconds to 21 seconds — a 50% reduction verified across 12,000 production user onboarding flows. ⭐ vercel/next.js — 139,252 stars, 30,994 forks 📦 next — 155,273,313 downloads last month Data
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