Hi everyone, my name is Greg. I've been working in web development since 2020. A few years ago, I started my journey into LeetCoding. Over this time, I've gathered several key insights that I'd like to share with you!
Where LeetCode shines?
It helps develop algorithmic and abstract thinking, and builds a solid foundation for competitive programming. It gives you confidence during live coding interviews and when tackling non-trivial problems. It trains you to mentally visualize complex data structures and their relationships, map out entire solutions in advance, evaluate asymptotic complexity, and write highly performant, optimized code.
Where LeetCode falls short?
The vast majority of product development tasks revolve around working with frameworks and APIs, making deep DSA knowledge less directly applicable day-to-day. LeetCode won't teach you product mindset, system architecture, teamwork, or how to maintain a legacy codebase. The main takeaway: LeetCode can make you a great programmer, but not necessarily a great software engineer.
Identifying and closing fundamental gaps
Beyond basic algorithms and data structures, solving certain problems forces you to dive into number theory, combinatorics, bit manipulation, recursion, search algorithms, memoization, dynamic programming (DP), and more.
LeetCode vs. Real-world development
Even the hardest LeetCode problems completely lack surrounding context - they are entirely isolated. Real-world development tasks, however, always come with an existing codebase and business context that you must account for, which is often where the real complexity lies.
The cognitive benefits extend beyond programming
After hundreds of problems, your brain adapts to systems thinking, changing how you approach real-life challenges. Instead of panicking, you instinctively break large problems down into manageable, solvable steps. Where there used to be chaos, you start seeing patterns. You naturally lean toward simpler, more efficient solutions and minimize wasted effort.
To hit "Beats 100%" performance
Choosing the right algorithm isn't enough; you also need a deep understanding of your programming language and leverage its full potential. Several solutions to the same problem may have identical time and space complexity, but their underlying implementations can cause actual execution time to vary wildly. As a result, a highly language-optimized O(n2) algorithm can sometimes outperform an unoptimized O(n) solution in practice.
I might write another post later about practical micro-optimizations in JavaScript/TypeScript.
LeetCode is the path of the IT samurai!