Writing about development and technology.
Server in the US meant slow responses for Korean users. Cloudflare Workers runs code at 300+ edge locations, cutting latency dramatically.
They all look the same at first, but each cloud has distinct strengths. A startup founder's guide to choosing the right cloud provider.
Managing isLoading, isError, and data separately creates impossible states. Discriminated unions make illegal states unrepresentable.
Tired of typo bugs in CSS class names and event strings? Template Literal Types let you enforce string patterns at compile time.
When your function's return type depends on input, conditional types replace 'any' with precise type inference. Type-level if-else explained.
Dealing with union types where API responses could be success or error? Type guards changed how I handle runtime type checking entirely.
I kept creating duplicate types until I discovered utility types. Partial, Pick, Omit, and Record let you transform existing types effortlessly.
Tired of writing setup docs for every new team member? docker compose up spins up your DB, Redis, and app server in one command.
Tired of ESLint and Prettier config conflicts? Biome combines linting and formatting in one blazing-fast Rust-based tool.
node_modules over 1GB and 5-minute installs? Switching to pnpm cut both size and speed in half with its clever symlink approach.
Managing frontend, backend, and shared libraries in separate repos was sync hell. Setting up a monorepo with Turborepo changed everything.
npm install took 3 minutes, bun install took 10 seconds. It's fast, but can you actually use it in production?
Solo developers can't get code reviews? AI review tools changed that. Setting up automated code review on every PR.
My first LLM API integration brought token cost explosions, latency issues, and hallucinations. Here's what I learned building real features.
MCP lets AI read files, query databases, and call APIs through a standardized protocol. Think of it as USB for AI tool connections.
ChatGPT answers questions. AI Agents plan, use tools, and complete tasks autonomously. Understanding this difference changes how you build with AI.
Asking AI to 'make a login page' gives garbage. Structured prompts with context, constraints, and examples produce production-ready code.
I actually used all three AI coding tools for real projects. Here's an honest comparison of Copilot, Claude Code, and Cursor.
10MB images upload fine but 2GB videos timeout. Chunked uploads, presigned URLs, and retry logic for robust file upload systems.
Sending one notification is easy. As notifications scale up, preventing duplicates, respecting preferences, and handling retries becomes a completely different engineering problem.
