DSA Doesn’t Make You a Better Engineer (Alone)

Source: Dev.to

Introduction

Let’s address the elephant in the interview room.

DSA is a skill. Somehow, solving algorithm problems has turned into a moral flex: “I’ve solved 487 LeetCode problems.” Cool. There’s always that one person who solves DSA before breakfast, tweets screenshots of green checkmarks, and treats time complexity like astrology (“O(n log n) energy today”).

Relax. Nobody is asking you to sort an array by hand at 2 AM in production.

Reality at Work

At work, you mostly:

• Read existing code
• Fix off‑by‑one bugs
• Rename variables
• Debug why something worked yesterday

You rarely hear:

“Quick, find the longest palindromic subsequence before the API times out.”

What Companies Want

• Problem‑solvers – they value the ability to think through constraints.
• Practical tasks – “Please invert this binary tree you’ll never see again.”

You pass the interview, and on Day 1 the task might be as simple as:

“Can you add a button?”

When DSA Is Useful

• Working on performance‑critical systems
• Dealing with large‑scale data
• Reasoning clearly under constraints
• Training logical thinking

These are valid reasons, not because “FAANG requires it,” “Everyone on Twitter/LinkedIn does it,” or “I might need DP someday (you won’t).”

Analogy: DSA Is Like the Gym

Good:

• Builds strength
• Improves thinking
• Boosts confidence

Bad:

• Comparing reps with strangers
• Making it your entire personality
• Judging others for not going

Do some. DSA won’t save bad architecture; it’s a tool. Learn the concepts, but remember that your codebase cares more about clarity than your longest streak.