The hype around AI coding tools for developers is exhausting. Half the industry tells you it is the end of manual coding, while the other half calls it a “slop machine” that generates unmaintainable garbage. After 14 years of wrestling with WordPress core and complex WooCommerce checkouts, I’ve realized the truth is in the messy middle. If you turn off your brain, you are a liability; if you ignore these tools, you are a dinosaur.
Lately, my team and I have been integrating tools like Cursor, Copilot, and Claude into our workflow. But we do it as “responsible developers.” To me, that means delivering quality code that doesn’t become a technical debt burden for the next guy. We treat AI output like code from a stranger on the internet: we test, we verify, and we never paste secrets or PII into a prompt without policy approval.
Mapping Unfamiliar Legacy Codebases
Joining a massive legacy codebase is intimidating. Whether it’s a 10-year-old custom theme or a tangled plugin, I use AI to generate a high-level architecture overview. Instead of clicking through folders for three hours, I ask the agent for the entry points, routing logic, and data layers.
“Give me a high-level architecture overview: entrypoints, routing, auth, data layer, build tooling. Then list 5 files to read in order. Treat explanations as hypotheses and confirm by jumping to referenced files.”
This approach turned a week-long onboarding session into a one-day deep dive. I recently wrote about the technical debt risks in AI development, and mapping the codebase first is the best way to avoid adding more debt.
Modernizing Legacy Build Stacks
I recently had a client with a site built nearly a decade ago. It used RequireJS and a version of Node.js that wouldn’t even install on my 2025 MacBook. Updating that build process manually would have taken days of dependency hell. Instead, I prompted an AI agent to migrate the SCSS and JS build process to a lean Vite stack.
Within an hour of refining the output, I had a working Vite config that handled our assets. Here is a simplified look at how we transitioned the logic:
// The AI-suggested vite.config.js for a WordPress theme
import { defineConfig } from 'vite';
import path from 'path';
export default defineConfig({
base: process.env.NODE_ENV === 'production' ? '/wp-content/themes/legacy-theme/dist/' : '/',
build: {
outDir: 'dist',
rollupOptions: {
input: {
main: path.resolve(__dirname, 'js/main.js'),
style: path.resolve(__dirname, 'scss/style.scss'),
},
output: {
entryFileNames: `[name].js`,
chunkFileNames: `[name].js`,
assetFileNames: `[name].[ext]`,
},
},
},
});Using AI Coding Tools for Developers to Ship Robust Tests
Let’s be honest: many developers skip writing tests because it’s tedious. But for a responsible developer, tests are non-negotiable. I use AI helpers to generate the “scaffolding” for Jest or PHPUnit tests. Furthermore, I pass along specific testing guidelines—like Kent C. Dodds’ principles—to ensure the AI doesn’t just write “happy path” tests that pass everything.
Specifically, I ask the agent to: “Cover the happy path, edge cases, and failure modes. Explain why each test exists.” This forces the AI to justify its logic, making it easier for me to review.
Best Practices: Prompting and Reviewing
The quality of your code depends on the specificity of your prompt. A powerful trick I learned from Ryan Florence is to end every initial prompt with: “Before we start, do you have any questions for me?” This allows the agent to clarify your intent before it starts hallucinating code.
Consequently, you must use version control religiously. AI can occasionally “go rogue” and refactor things you didn’t ask it to touch. By working in small, digestible chunks with frequent Git commits, you create stable rollback points. If you’re looking for more tips, check out my thoughts on the AI tools I actually use for web development.
Look, if this AI coding tools for developers stuff is eating up your dev hours, let me handle it. I’ve been wrestling with WordPress since the 4.x days.
The Senior Developer Takeaway
AI is not a silver bullet. It is a productivity multiplier for those who already know how to code. For juniors, the danger is skipping “the grind”—the painful debugging sessions where real expertise is built. Excellence and problem-solving will never go out of fashion. Use these tools to free up your mental capacity for high-level thinking, but never, ever turn off your brain.
