Well, This Wasn’t in the Job Description
We spend more time reading code than writing it. And most of that time? We’re reading someone else’s code. Chances are, it’s not an uplifting experience.
Maybe it was a rushed MVP. Maybe it’s a legacy system built by three devs who’ve all since disappeared into the ether. Maybe it’s your code from six months ago, which is somehow worse.
Whatever the case, you’ve inherited it now. Congrats. Here are five things to do when faced with a gnarly codebase that makes you question your career choices.
1. Read It Like an Archaeologist, Not a Critic
You’re not here to judge. You’re here to understand. Pretend you’re brushing dust off a piece of ancient tech, not roasting it on Twitter.
Resist the temptation to label everything “garbage.” Start by asking: what was this trying to do? What constraints might they have had? What shortcuts were probably necessary?
Instead of rewriting it all from scratch (which you won’t), focus on uncovering the original intentions. Sometimes the logic is buried under years of duct tape — but there was logic once.
Pro move: jot down confusing patterns as questions, not accusations. “Why is this loop reassigning itself?” is better than “wtf is this trash.” It’ll help your future debugging and preserve your sanity.
2. Run It. Break It. Run It Again.
Before you touch a single line, get it running. Locally. In a container. In staging. On a Raspberry Pi duct-taped to your modem. Whatever it takes.
You need to see the beast in motion. Trigger features, hit edge cases, try invalid input. Watch how it responds. Some things will crash spectacularly. Others will weirdly work.
This is how you learn the terrain. Think of it as a reconnaissance mission, not a rescue operation.
And yes, this might involve reading a README last updated in 2019 or figuring out why it depends on a deprecated npm package called leftpad-magic.
3. Map the Landmines
There are always a few “do not touch” areas. Legacy functions nobody understands. Cron jobs that magically keep the business running. Data pipelines held together by tab-delimited CSVs and prayer.
Map these out. Comment them. Annotate them. Make a living doc if you need to. This isn’t overengineering — it’s survival.
Because one day, someone (you?) will try to refactor a critical part at 4:45 PM on a Friday. Your notes might be the thing that prevents a full-blown incident.
Think of it like marking traps in a dungeon. It’s not glamorous, but future-you will thank present-you.
4. Find the “One Smart Thing”
Even the ugliest codebases have one bit of elegant, well-considered design. Maybe it’s a clever bit of caching. Maybe the data model actually anticipates edge cases. Maybe some long-forgotten dev wrote a shell script that works flawlessly every single time.
Find that piece. Admire it. Then steal the pattern.
Because buried in the wreckage of bad code are usually hints of what the author wanted the system to be — before it devolved into spaghetti.
Recognizing that “one smart thing” also gives you a thread to pull on if you ever do get the green light to refactor properly.
5. Start Small. Fix What You Touch.
The heroic rewrite is a fantasy. You will not rebuild the system in two weeks with clean architecture and perfect tests. You will get halfway, then get pulled into sprint planning or on-call.
Instead, fix things incrementally. Touching a function? Refactor it. See a poorly named variable? Rename it. Writing a feature? Add tests for the nearby stuff.
This is the Boy Scout Rule: leave the code a little better than you found it.
Over time, these small changes compound. You build trust with teammates. You make future maintenance suck slightly less. You stop fearing the codebase.
Coming Soon…
I’ll be expanding each of these into standalone posts, diving deeper into how to:
Reverse-engineer legacy logic without losing your mind
Use staging environments and logs as your secret weapons
Build minimal but helpful internal docs around landmines
Spot (and reuse) the clever patterns buried in legacy code
Actually make progress on refactoring, even with deadlines
And yes — I’ll include a version for folks who use AI coding assistants (whether it’s Claude, Augment, Copilot, or whatever else). They’re great at speeding things up… and occasionally making legacy code worse in new and exciting ways.
TL;DR: You will inherit bad code. It will suck. But with a little strategy — and some sarcasm — you can survive it, improve it, and maybe even learn a thing or two from it.