Common Mistakes I Made as a Junior Developer

When I started as a backend developer, I thought I just needed to make things ‘work.’ Turns out, that mindset cost me a lot of time, bugs, and headaches. These are a few mistakes I made early on—and what I wish I had done differently.

Mistake 1: Overengineering Too Early

My first instinct was to build for the future. I'd read about microservices, message queues, and complex caching strategies, and I wanted to use them all. I was trying to make my simple CRUD application "scalable" before it even had a single user, adding layers of abstraction when a simple function would have done the job.

The Consequence

A project that should have taken a week took over a month. The complexity was overwhelming. Debugging a simple request meant tracing it through multiple services and network calls. Instead of delivering a working product, I had built an intricate, fragile skeleton that didn't actually do much. The cognitive overhead was immense, and my velocity slowed to a crawl.

The Better Way: Embrace YAGNI

The solution is the "You Ain't Gonna Need It" (YAGNI) principle. Start with the simplest possible architecture that solves the immediate problem. A monolith is perfectly fine for 99% of new projects. You can always refactor and scale *when* you have the data and traffic to justify it. The goal is to deliver value quickly, learn from user feedback, and iterate. Premature optimization is, as they say, the root of all evil.

Tip: Start simple. Solve today's problem today. Solve tomorrow's problem tomorrow.

Mistake 2: Not Writing Tests

I saw testing as a chore that slowed me down. My go-to excuse was, "I'll come back to it later," but "later" never came. I would manually test my endpoints in Postman, get a 200 OK, and confidently merge my code. This worked, until it didn't.

The Consequence

A small, seemingly unrelated change would silently break a critical feature. Without an automated test suite, I lived in constant fear of regressions. Every new deployment was a high-stress event. I spent more time manually re-testing old features than building new ones. My confidence in my own code was practically zero.

The Better Way: Build a Safety Net

Tests are not about slowing you down; they are about enabling you to move faster and more confidently in the long run. Start with simple unit tests for your most critical business logic. A test proves your code does what you think it does, and it acts as a safety net against future changes.

Tip: Start with one simple unit test for a pure function. The confidence boost you get from seeing it pass—and fail when you break something—is the best motivation to write more. Testing helps you trust your own code.

Mistake 3: Not Understanding How the Database Really Works

I fell in love with my ORM (Object-Relational Mapper). It felt like magic—I could interact with my database using simple objects and methods, without writing a single line of SQL. I used the ORM blindly and never bothered to inspect the queries it was generating under the hood.

The Consequence

This led to a classic and devastating performance issue: the N+1 query problem. On a page that displayed a list of 50 articles and their authors, my code was executing 51 database queries: one to fetch the 50 articles, and then 50 more individual queries to fetch the author for each article. The page load time was abysmal, and for a while, I had no idea why.

The Better Way: Look Under the Hood

An ORM is a tool, not a replacement for understanding your database. Learn to read the SQL logs your framework or ORM generates. Most ORMs provide methods for "eager loading" related data to solve the N+1 problem (e.g., .includes(:author) in Rails or .select_related('author') in Django). Furthermore, learn to use your database's query analysis tools, like EXPLAIN ANALYZE in PostgreSQL, to identify slow queries and understand whether your indexes are being used effectively.

Tip: Treat your ORM as a powerful assistant, but remember that you are still the one in charge. Always be curious about the SQL it writes on your behalf.

Mistake 4: Poor Error Handling

My early error handling was lazy and unhelpful. I'd wrap large blocks of code in a generic try...catch and, in the catch block, either log a useless message like "An error occurred" or, even worse, silence the error completely to prevent the application from crashing.

The Consequence

When a user reported a bug in production, the logs were a dead end. "An error occurred" told me nothing about what happened, where it happened, which user was affected, or what data caused the failure. I was flying blind, trying to reproduce bugs based on vague descriptions, which was often impossible and always frustrating.

The Better Way: Log with Context and Structure

Good error handling is about creating actionable insights. When you catch an error, log it with as much context as possible. Use structured logging (e.g., JSON format) to make your logs searchable and easy to parse.

A bad log entry:

// BAD 👎
try {
  // ... some risky operation
} catch (error) {
  console.log("Something went wrong.");
}

A good, structured log entry:

// GOOD 👍
try {
  // ... some risky operation for a user
} catch (error) {
  logger.error({
    message: "Failed to process payment",
    userId: "user-123",
    orderId: "order-abc-789",
    errorMessage: error.message,
    stack: error.stack
  });
}

Tip: A good error log should be a complete bug report. Include context, use structured logging, and never, ever silence an unexpected error.

Mistake 5: Avoiding Documentation

I subscribed to the romantic myth that "good code is self-documenting." I believed that my clever function names and clean code structure were all anyone would ever need to understand my work. I thought writing comments or external documentation was a sign that my code wasn't clear enough.

The Consequence

Future-me strongly disagreed. When I had to revisit a complex module six months later, I couldn't remember the "why" behind my design decisions. It took me a full day to re-learn my own logic. Onboarding a new developer was even more painful; I had to become a walking, talking manual for the codebase, which was inefficient for everyone.

The Better Way: Document the "Why"

Code tells you *how* something is done, but documentation tells you *why*. You don't need to comment every line. Focus on documenting the things code can't explain on its own:

• API Endpoints: Use a standard like OpenAPI (Swagger) to document what each endpoint does, the parameters it expects, and the shape of its response.
• Tricky Business Logic: If a piece of logic is complex due to a specific business rule, add a comment explaining that rule.
• Architectural Decisions: Keep a simple document in your repository explaining why you chose a particular database, library, or design pattern.

Tip: Write documentation for your future self and your future teammates. At a minimum, document your API and any logic that isn't immediately obvious.

What I've Learned

Looking back, all of these mistakes taught me something valuable about building robust, maintainable software. And honestly, I'm still making new ones—but now I catch them faster, and the lessons are more nuanced. The journey of a developer is one of continuous learning, and mistakes are the most effective teachers.

If you're just getting started, I hope this helps you skip a few of these common pitfalls. Got a mistake you learned the hard way? I'd love to hear about it.

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Published on: 2025-10-15
Written by El Bouhlali Salaheddine, a backend developer learning in public.