Learning to love other people’s code.

As developers, I think we’ve all been there. A client asks for a “small change” to a project you’re maintaining. You didn’t write the code, but the request seems reasonable enough.

Two days later, you’re staring at your screen, wondering why you didn’t just become a mechanic like your family suggested. Just me?

The trap was set long before you joined the project. The original designers and developers are gone, off working at different companies. If you’re lucky, there are a few others around who can offer some anecdotal mythology about how things came to be.

So now what?

We all approach this situation differently. Here’s how I’ve learned to navigate it.

Start with “Why?”

The first question I ask is: Why did they do it this way?

If I can answer that, I can usually solve most of the problems I encounter. Instead of focusing on how I would have built it, I try to accept that the code exists as it does because, at the time, it worked given the constraints, resources, and requirements.

So what were those constraints? What pressures shaped these decisions?

And why does this always seem to happen on a Friday afternoon?

Using Tech Debt as Clues

Codebases aren’t sterile—they accumulate debris over time. And like an archaeological dig, that debris can tell a story.

Some useful questions to ask:

• Why hasn’t this code been refactored?
• Why are we using outdated libraries or frameworks?
• Why weren’t variable or method names updated as their purpose evolved?
• Are the comments still accurate?

Technical debt exists for many reasons—and not all of them are bad. Understanding why that debt was accepted helps frame everything else.

Was it:

• A time or budget constraint?
• A technical limitation?
• A skill gap?
• Or simply not considered debt at the time?

Answering those questions often explains why you’re currently daydreaming about playing video games instead of actually playing them.

Analyzing the Time Period

Context matters.

Like an archaeologist, you can’t just examine the artifacts—you need to understand the era they came from. For maintainers, that means digging into the commit history, old tickets, past designs, and even git blame (oh… it’s them again).

Consider the following:

• What did the code look like when that comment was written?
• What requirement changes drove later modifications?
• How often has this requirement changed?

Our industry moves fast. Libraries and frameworks come and go. Some solutions may not have existed when this code was written; others may no longer exist today.

These factors matter when you’re trying to understand why a particular approach was taken.

More importantly, this process often reveals the concerns previous developers were trying to address—and those concerns are what you need to carry forward.

Understanding the Person

Spend enough time in a codebase and you start to recognize individual developers by their style—their naming conventions, structure, even their spacing.

Understanding who wrote the code and where they were in their career can add valuable context.

Was this a junior developer solving the problem the best way they knew how? Or a senior developer balancing trade-offs between performance, deadlines, and maintainability?

I try to approach this with empathy. Assume good intentions from those who came before you.

That doesn’t mean every decision was the right one. Sometimes, a genuinely bad call was made and now it’s yours to fix.

Putting It All Together

So how does this help?

For one, it stops the doom spiral. Instead of reacting emotionally, you start investigating methodically.

With better context, you can make better decisions:

• Maybe it’s time to pay down some technical debt.
• Maybe it’s time to modernize libraries or frameworks.
• Or maybe it’s best to leave things alone—for now.

Either way, you’re no longer operating on instinct or frustration. You’re making informed decisions.