I've solved over 300 LeetCode problems. But this isn't a story about grinding for FAANG interviews—it's about how consistent problem-solving fundamentally changed how I think about code.

Why I Started

I didn't start LeetCode to get good at interviews. I started because I kept hitting walls in production code—situations where I knew there had to be a better solution, but I didn't know enough data structures or algorithms to find it.

LeetCode became my training ground for systematic problem-solving.

What I Actually Learned

1. Pattern Recognition

After solving enough problems, you start seeing patterns. Two pointers. Sliding window. Dynamic programming. These aren't just interview tricks—they're mental models for solving real problems.

When I encounter a production bug now, I instinctively think: "Is this a graph problem? Could I use a hash map here? Would memoization help?"

2. Time-Space Tradeoffs

Every algorithm is a tradeoff. Faster? Use more memory. Less memory? Sacrifice speed. Understanding these tradeoffs viscerally changed how I write production code.

I now consciously think about performance implications of every data structure choice. Arrays vs Sets? Maps vs nested loops? These decisions matter at scale.

3. Edge Case Thinking

LeetCode problems force you to think about edge cases: empty inputs, single elements, maximum constraints. This mindset carries over to production.

I now write more defensive code by default. I think about null checks, boundary conditions, and failure modes before they become bugs.

4. Code Clarity

Explaining solutions in LeetCode discussions taught me to write clearer code. If you can't explain your solution simply, you don't understand it well enough.

This has made me a better code reviewer and a clearer communicator with teammates.

Beyond the Interview

Yes, LeetCode helped me win competitive programming contests. But the real value was in how it trained my brain to approach problems systematically:

  • Understand the problem: What are the constraints? What's the goal?
  • Consider approaches: What data structures fit? What algorithms apply?
  • Optimize iteratively: Start with brute force, then optimize.
  • Test edge cases: Where could this break?

The Competitive Edge

Solving DSA problems gave me wins beyond interviews:

  • 1st place in Web Development competition
  • 1st place in ML NOVA hackathon
  • 2nd place in two DSA challenges
  • 3rd place in 8-hour AI Hackathon

Each win reinforced the same lesson: systematic problem-solving beats raw talent.

How to Approach LeetCode

Don't just grind blindly. Here's what worked for me:

  • Focus on patterns, not problems: Learn the underlying concepts.
  • Revisit hard problems: If you don't get it, come back after a week.
  • Explain your solutions: Write them down, explain to others.
  • Track your progress: Consistency beats intensity.
  • Apply to real code: Use what you learn in your projects.

The Bottom Line

LeetCode isn't about memorizing solutions. It's about training your brain to see problems as puzzles with systematic approaches. That mindset—more than any specific algorithm—is what makes you a better engineer.