My "Duh!" Moment with LLMs: They're Actually Great for Resurrecting My Old, Ugly Code

Alright, let's be real. The whole "AI is gonna take our jobs!" vs. "AI is just a fancy autocomplete!" debate has been raging for what feels like an eternity. I've mostly been on the sidelines, watching the LLM hype train choo-choo past with a mix of curiosity and, honestly, a bit of indifference. I saw the cool demos, but nothing really clicked for my personal workflow... until a few days ago.
And when it clicked, it was one of those facepalm "D'oh!" moments. The kind where you realize everyone else probably figured this out ages ago.
You know those projects? The ones you hacked together a year, maybe two years back? The ones with a genuinely decent idea buried under layers of... well, let's call it "organically grown" code. Inconsistent styling, functions that ramble on for miles, variable names that made sense only at 3 AM fueled by questionable pizza. Yeah, those projects.
I've got a graveyard of them. Potentially useful little tools or libraries, but the thought of sharing them? Horrifying. The code was, to put it mildly, not something I'd want my name publicly attached to. The shame was real.
Then, the lightbulb flickered on.
Instead of just being a tool for greenfield projects or a way to generate boilerplate, what if LLMs could be my personal code beautician for these old digital skeletons?
So, I started experimenting. I began feeding chunks of my ancient, crusty code into an LLM (you know the ones I'm talking about). My prompts weren't "write me a new app," but more like:
"Refactor this JavaScript function for better readability and consistency."
"Can you add JSDoc comments to this module?"
"Make this code adhere more closely to [insert style guide here]."
And you know what? It's been surprisingly effective.
It's not a magic bullet, mind you. I'm not just blindly copy-pasting. I'm reviewing, tweaking, and guiding. But the LLM does the heavy lifting of untangling the initial mess, suggesting more idiomatic approaches, and generally "combing through" the chaos. It's like having an incredibly patient pair programmer who doesn't judge your past coding sins.
Suddenly, these old projects are starting to look... presentable. Polished, even! The core logic is still mine, the original spark is there, but the LLM is helping me package it in a way that I'm not embarrassed to show the world. It's breathing new life into ideas that would have otherwise just gathered digital dust.
For me, this has been the most practical, immediate benefit of LLMs I've experienced so far. It's not about replacing developers; it's about augmenting our ability to deal with the less glamorous (but super important) parts of software development, like refactoring and improving existing codebases. It lowers the barrier to entry for sharing something that might be useful, even if its initial incarnation was a bit... wild.
So, yeah, maybe I'm late to this particular LLM party. But if you, like me, have some old digital treasures you've been hesitant to share because the code makes you cringe, maybe it's time to let an AI lend a hand in the cleanup.
What "obvious" LLM use cases have you stumbled upon that made you go "D'oh!"? I'd love to hear your stories in the comments!