I Never Cared About Code Styling… Until I Got Burned
A couple of years ago, I couldn’t care less about semicolons, spacing, or brace styles. I was the classic “if it runs, ship it” dev. But in 2025, I’ve turned into that person who actually enjoys clean, consistent code.
Why? Because I got burned. Multiple times.
This isn’t a how-to guide—it’s a brain dump of how I built a custom ESLint setup, infused it with AI smarts, wired it into CI, and somehow made code reviews… enjoyable?
It Started With One “Dumb” Bug
It was late on a Tuesday—one of those jittery, caffeine-fueled evenings. I reviewed a pull request from a teammate (let’s call him Sid). It passed tests, looked fine, and I merged it.
The next day, we had a bug in production. Why?
A missing return statement in a one-liner for loop—because someone omitted braces.
A rule ESLint could’ve flagged. If we hadn’t disabled it.
That was the moment I snapped. No more silent code failures. No more avoidable bugs sneaking into prod. I wanted our codebase to yell when something smelled off—not just syntax-wise, but readability-wise.
ESLint Isn’t Just a Linter. It’s a Therapist.
I’d used ESLint before—mostly whatever config came with Create React App or Next.js. But I realized those defaults were just scratching the surface.
I didn’t just want a syntax checker. I wanted a code guardian. Something opinionated. Something smart. Something that would grow with the team.
So, naturally, I thought, “Let’s extend Airbnb’s style guide, sprinkle in some plugins, and call it a day.”
It worked—until our codebase grew and started evolving in ways static rules couldn’t keep up with.
Because real-world code isn’t about rules. It’s about communication. Especially when you’re debugging at 1 a.m. during an outage.
And that’s where AI entered the chat.
Meet the Lint Whisperer: AI-Driven Suggestions
Somewhere along the journey (don’t ask where), I started playing with OpenAI’s Codex. I had this idea:
What if we trained a lightweight model on our codebase—not just to check syntax, but to understand how we write code?
I hacked together a plugin that:
- Took a
diff - Queried the model
- Asked: “Does this match our team’s style?”
And guess what? It worked—kinda.
It flagged things ESLint never would:
- Function names that didn’t match our usual naming tone
- 50-line async handlers that begged to be split
- Unnecessary state variables junior devs were prone to add
It wasn’t perfect, but it felt like a linter with a personality. A linter that knew our team.
The AI + ESLint Combo: Surprisingly Powerful
Eventually, I married both systems:
- ESLint handled hard rules: unused imports, strict equality, required returns.
- AI assistant offered soft suggestions: “maybe rename this?” or “split this logic?”
The AI ran after the linter—like a co-pilot, not a cop.
And then we wired everything into CI:
- Lint must pass. No exceptions.
- AI suggestions appear in comments (optional but helpful).
- Human reviewer gets the final say.
What happened next surprised me: we talked more.
The AI didn’t replace code conversations. It started them.
The Pain That Nearly Made Me Quit
Let’s be real. This was not all sunshine and clean commits.
- The AI gave terrible suggestions sometimes. Like renaming
userDatatodataUserbecause of historical pattern noise. - ESLint configs are fragile. One misconfigured plugin? Nothing works.
- CI integration was a performance bottleneck. Took weeks to optimize.
But gradually, the chaos became a process. And the process became a culture.
Why This Still Feels Worth It
This setup didn’t just clean up our code—it:
- Reduced dev arguments.
- Slashed review time.
- Made onboarding smoother (new devs could just run
npm run lintto “read our minds”).
And for me? It made reviews fun again. I wasn’t stuck nitpicking semicolons—I was thinking about architecture, performance, logic flow.
If you’re a developer and think linters are overkill—I get it.
But when done right, they’re like a friend tapping your shoulder going, “Hey… didn’t you mess this up last sprint too?”
Add a little AI, and that friend has a memory longer than yours. And a calm voice that says: “Hey, maybe rename that for clarity.”
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Final Thoughts: Build It Your Way
I still occasionally write bad code on purpose—just to see if my system catches it. Sometimes it does. Sometimes it doesn’t. But every time, I learn something.
And that’s really the point.
Not to chase perfection—but to catch the little stuff before it becomes big.
So if you’re tempted to build your own linting system:
- Start with ESLint
- Add the rules your team actually cares about
- Experiment with AI
- Automate it into your CI
- Watch your team’s code quality—and culture—get better
It won’t be perfect. But it’ll be yours.
And your future self will thank you.
