Webdev Blog by SB

React 18 shipped in March 2022. We merged our upgrade in April 2026. If you do that math, yes — we were four years behind. This is a post about what that upgrade actually looked like across a large, multi-generational codebase, and the specific issues that ate most of the time. Spoiler: the "breaking changes" in the official React 18 migration guide are the easy part. The Starting Point Our frontend is not one app — it's four generations of React code living in the same monorepo, accumulated over years of product growth: assets/js/ — the oldest layer, Alt.js Flux architecture app/ — second generation, class components everywhere web/ — Chakra UI-based, mostly hooks frontend/ — newest, Elastic EUI, greenfield The upgrade touched the first two generations: assets/js/ and app/ . That's the part of the codebase with the heaviest accumulation of legacy patterns — class components, Immutable.js collections in JSX, and some HOC patterns that had never seen a ...

AI coding assistants keep hallucinating EUI props. You paste in documentation, it gets ignored thirty messages later. You end up debugging code where half the props don't exist. The fix is an MCP server — about 200 lines of TypeScript that gives any MCP-compatible AI direct access to the EUI source. What EUI is EUI (Elastic UI) is Elastic's open-source React component library. It powers Kibana and the rest of the Elastic product suite. The library is large — over 100 components covering everything from basic buttons and forms to complex data grids, drag-and-drop interfaces, and charting primitives. Each component ships with TypeScript types, MDX documentation, and Storybook stories. It's a serious design system, which also means it's too big for any model to know completely from training data. Why AI gets EUI wrong Models know enough from training to be convincing but not enough to be correct. They'll use EuiButton with a size prop that doesn't exist, or...

You know that feeling when you open a PR and it's 47 files changed, 3,000 lines? The reviewer sighs, skims it, leaves a comment like "looks good," and merges it. No real feedback. Nothing caught. That's not code review—that's rubber-stamping. Stacked PRs are a way out of that trap. The Basic Idea Instead of one massive PR, you break the work into a chain. Each branch builds on the previous one, and each PR targets its parent branch rather than master directly. master └── branch1 (PR #1 → master) └── branch2 (PR #2 → branch1) └── branch3 (PR #3 → branch2) PR #1 is small, focused, and reviewable in ten minutes. PR #2 only shows the diff on top of PR #1—again, small. Reviewers can actually engage with the code. The tradeoff is that you now have to manage a dependency chain. That's the part people find annoying, and it's where most explanations fall short. Two Ways to Do This There's a raw git approach and a to...

If you're applying to hundreds of jobs and hearing nothing back, it's not just you. The system is broken. Big companies dominate job boards like LinkedIn because they pay for premium placement. A single listing at a major corporation can get over 1,000 applications. Your resume, no matter how strong, has almost no chance of being seen by a human. Most applications are auto-filtered within seconds. You're competing against thousands of people for positions that are often filled internally or through referrals before anyone looks at the application pile. The Ghost Job Problem Many major companies have hiring freezes but keep their job postings live. They're playing an optics game. Removing hundreds of job posts signals weakness to competitors, investors, and Wall Street. So they leave them up to maintain the illusion of growth. Every application you send to these frozen roles goes nowhere. You're spending hours applying for jobs that managers have no budget or per...

Modern development often involves managing multiple processes simultaneously. Between a backend server, a frontend build process, a database, and version control, it's easy to spend the first few minutes of any session just getting the workspace configured. Over time, I've developed a setup that prioritizes automation and consistency. The goal is to reduce the manual steps required to start working. My current workflow is based almost entirely in the terminal, using tmuxp to manage sessions and a few carefully chosen tools for coding, file management, and version control. The Foundation: Automated Sessions with tmuxp Many terminal users are familiar with tmux for managing multiple shell sessions. I use a tool called tmuxp to automate the setup of these sessions. It uses a configuration file to define all the windows, panes, and startup commands for a project. This means that instead of manually opening tabs, navigating to directories, and starting servers each time, I can d...

As a Web Engineer focused on full-stack implementations, I've spent years immersed in the AWS ecosystem. My daily toolkit prominently features services like EC2, DynamoDB, Redis, Lambda, API Gateway, and S3. While I was comfortable building and deploying applications, I knew there was a vast universe of AWS services and architectural best practices beyond my day-to-day work. This year, I set a personal goal at work to achieve the AWS Certified Solutions Architect – Associate certification. It wasn't just about a badge; it was about truly going deeper into subjects I touched lightly, understanding how to architect robust solutions, and ultimately becoming a more well-rounded cloud professional. I'm thrilled to say I passed the SAA-C03 exam on my first attempt with an impressive score of 903/1000! Here’s the exact study plan I followed over nine consistent months. Introduction: What is the Solutions Architect - Associate Exam? The AWS Certified Solutions Architect – Associate...

The quality of content has undergone a significant transformation over the past five decades, marked by a pervasive decline in certain critical aspects. This report examines the multifaceted drivers behind this trend, identifying how technological advancements, evolving economic models, and shifts in audience behavior have converged to create an information environment where content quantity often overshadows its intrinsic value and accuracy. The analysis reveals that the democratization of publishing, while offering unprecedented access and diversity, has simultaneously strained traditional quality control mechanisms. The relentless pressure for rapid content production, driven by competitive digital landscapes, has frequently compromised editorial rigor. Furthermore, the pervasive influence of Search Engine Optimization (SEO) and the emergence of "content farms" have incentivized the creation of material optimized for algorithms rather th...