Let’s address the elephant in the interview room.
DSA is a skill.
Not a lifestyle.
Not a personality.
Not a substitute for having hobbies.
Somehow, solving algorithm problems has turned into a moral flex.
“I’ve solved 487 LeetCode problems.”
Cool.
Do you remember what you built last month?
The Cult of Problem Counts
There’s always that one person:
- Solves DSA before breakfast
- Tweets screenshots of green checkmarks
- Treats time complexity like astrology
“O(n log n) energy today.”
Relax.
Nobody is asking you to sort an array by hand at 2AM in production.
Reality Check: DSA vs Actual Work
At work, you mostly:
- Read existing code
- Fix off-by-one bugs
- Rename variables
- Debug why this worked yesterday
Nobody says:
“Quick, find the longest palindromic subsequence before the API times out.”
The Interview Paradox
Companies:
“We want problem solvers.”
Also companies:
“Please invert this binary tree you’ll never see again.”
You pass the interview.
You join the company.
Day 1 task:
“Can you add a button?”
When DSA Actually Matters
Let’s be fair.
DSA is useful when:
- You work on performance-critical systems
- You deal with large-scale data
- You need to reason clearly under constraints
- You want to train logical thinking
That’s it.
Not because:
- “FAANG requires it”
- “Everyone on Twitter/LinkedIn does it”
- “I might need DP someday (you won’t)”
A Healthier Way to Treat DSA
Think of DSA like the gym.
Good:
- Builds strength
- Improves thinking
- Helps confidence
Bad:
- Comparing reps with strangers
- Making it your entire personality
- Judging others for not going
Do some.
Stay consistent.
Don’t become weird about it.
Final Thoughts
DSA won’t save bad architecture.
DSA won’t fix unreadable code.
DSA won’t teach you communication.
It’s a tool.
Not a crown.
Learn the concepts.
Build real things.
Come back to DSA when performance actually matters.
Your codebase cares more about clarity than your longest streak.
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