git commit -m "fix: remove clever recursion, use simple loop"
That commit message still haunts me. Not because the code was wrong—it worked perfectly. Not because the performance was bad—it was actually faster than what came before. It haunts me because of what happened in the code review that followed.
"Why did you change this?" Sarah asked during our team standup, pulling up the diff on her screen. "The recursive solution was elegant."
I had spent three hours the night before crafting what I thought was beautiful code. A recursive function that traversed a nested data structure with mathematical precision. Each function call building on the previous, creating this satisfying symmetry that felt like solving a proof in computer science class.
"It's more readable," I said, confident in my answer.
"For who?" she asked.
That question broke something in me. And then rebuilt it entirely.
The Recursion Trap
I had been programming for four years at that point. I could write closures that made functional programming purists weep with joy. I understood monads well enough to explain them at meetups. My GitHub was a monument to algorithmic complexity disguised as elegance.
But I had never asked myself the most important question in software development: Who is this code for?
I assumed code was for computers. Or maybe for other developers who shared my fascination with abstract patterns and clever solutions. I optimized for the dopamine hit of solving problems in ways that felt intellectually satisfying.
Sarah's question forced me to confront an uncomfortable truth: I was writing code for an audience of one. Me. And that audience was about to quit the company in six months.
The recursive function I was so proud of? It required understanding of recursion, data structure traversal, and the specific business logic of our user permission system all at once. The "simple loop" I had reluctantly replaced it with could be understood by anyone who had written a for loop.
"Readable for the person who gets paged at 2 AM when this breaks," Sarah continued. "Readable for the junior developer who joins next month. Readable for you, when you come back to this code in a year and can't remember why you thought recursion was necessary."
The Real Performance Metric
This wasn't just about recursion versus loops. This was about a fundamental misunderstanding of what we were optimizing for.
I had been optimizing for code elegance. Sarah was optimizing for team velocity.
I measured success by how few lines of code I could use to solve a problem. She measured success by how quickly someone could understand, modify, and debug that solution under pressure.
I thought about performance in terms of Big O notation. She thought about performance in terms of how long it takes a new team member to become productive.
The recursive solution might have been more "correct" in some abstract computer science sense. But the simple loop was more correct for our team, our deadlines, and our on-call rotation.
This shift in perspective changed everything about how I approached code. Instead of asking "What's the most elegant solution?" I started asking "What's the most collaborative solution?"
Code as Communication
Programming, I realized, is not primarily about talking to computers. Computers don't care if your variable names are descriptive or if your functions are well-organized. Computers will execute a = b + c just as happily as totalPrice = basePrice + tax.
Programming is about talking to humans. Future humans who will read, modify, and maintain your code. Present humans who need to understand what your code does during code review. Past humans—including yourself—who made decisions that need to be preserved and understood.
Every function name is documentation. Every abstraction is a teaching moment. Every architectural decision is a conversation with your team about how you collectively think about the problem you're solving.
When I started treating code as communication rather than clever problem-solving, everything improved. My pull requests got approved faster because reviewers could quickly understand the intent. Bugs became easier to fix because the code told a clear story about what it was trying to accomplish. New team members could contribute to my codebases without needing a PhD in abstract data structures.
The Tools That Actually Help
This realization completely changed how I use development tools, including AI assistants. Instead of asking Claude to generate the most efficient algorithm, I ask it to help me write code that tells a clear story. Instead of using GPT-4o to create impressive one-liners, I use it to break complex logic into simple, named functions.
The Code Explainer became invaluable not for understanding other people's clever code, but for checking whether my own code would be clear to someone seeing it for the first time. If I had to use an AI to explain what my code does, that was usually a sign that I needed to rewrite it more clearly.
I started using the Grammar Checker not just for documentation, but for commit messages, code comments, and variable names. Because if communication is the goal, then clarity of language matters as much in code as it does in any other form of writing.
The Document Summarizer helped me distill complex technical requirements into simple, actionable tasks that the whole team could understand and contribute to.
These tools became force multipliers for collaboration, not just individual productivity.
The Compound Effect of Clarity
Six months later, our team's velocity had noticeably improved. Not because we were writing more code, but because we were writing code that worked together better.
Pull requests moved through review faster because the intent was clear from reading the diff. Debugging sessions became collaborative problem-solving instead of archaeological expeditions through clever abstractions. New team members started contributing meaningfully within weeks instead of months.
The junior developer who joined our team that quarter told me months later that our codebase was the first one where she felt confident making changes without breaking things. Not because the code was simple—the business logic was still complex—but because the code was honest about its complexity.
Complex business rules were broken into named functions that read like documentation. Edge cases were handled explicitly rather than hidden in clever abstractions. The architecture reflected the real-world processes we were modeling, not some idealized computer science textbook example.
The Uncomfortable Truth About "Best Practices"
Most of what we call "best practices" in software development are actually collaboration practices in disguise.
Test-driven development isn't about catching bugs—it's about creating a shared understanding of what the code should do. Code reviews aren't about finding syntax errors—they're about building collective ownership of the codebase. Continuous integration isn't about automation—it's about creating feedback loops that keep the team aligned.
The practices that make code "good" are almost always the practices that make code collaborative.
This means that the most valuable skill you can develop as a programmer isn't mastering the latest framework or algorithm. It's learning to write code that makes your team smarter, not just yourself.
Beyond the Individual
That single commit message taught me something that years of computer science education had missed: software development is a team sport that happens to involve typing.
The best programmers I know aren't the ones who write the most clever code. They're the ones who write code that makes everyone around them more effective. They choose boring, predictable patterns over novel solutions. They write tests that serve as examples of how to use their APIs. They refactor not to show off their skills, but to make the codebase more welcoming to new contributors.
They understand that every line of code is a vote for the kind of team they want to work with.
The Questions That Matter
Now when I'm writing code, I ask different questions:
Will the person debugging this at 3 AM understand what I was thinking? Will a junior developer be able to extend this feature without rewriting it? Does this code teach good patterns to someone reading it for the first time? If I left the company tomorrow, would this code help the team or hurt it?
These aren't questions about code quality in some abstract sense. They're questions about being a good teammate.
The most impactful commit you can make isn't the one that solves the hardest technical problem. It's the one that makes it easier for your team to solve problems together.
Your code will be read far more often than it's written. Write it for the humans who come after you, not for the computer that executes it.
-Leena:)
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