Data Structures and Algorithms (DSA) training develops critical thinking skills including clear thinking under pressure, problem decomposition, pattern recognition, and effective communication of solutions, which are essential for technical interviews where companies evaluate how candidates think rather than just their coding ability.
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Deep Dive
Day 5 solving leetcode #dsa #coding #faangAdded:
Day five of solving lead code and today I'm solving reorder linked list. But before I start I saw a comment on my previous video asking, "Does DSA even help?" And honestly, I used to think the same.
As a data engineer I'm not reversing linked list or detecting cycles in my day-to-day work.
So for a long time, DSA felt unnecessary. But now that I'm actually practicing consistently, I think DSA helps in different ways. It trains you how to think clearly under pressure, to break down a problem, to identify patterns, to communicate your approach, and to come up with a working solution within limited time. Because in interviews, they are not only checking if you can code. They are actually checking how you think.
And if DSA didn't matter at all, why are top product-based companies still asking these questions even in the age of AI and all these advanced tools?
That's my opinion, at least.
What's your take on this? Do you think DSA is still relevant in 2026?
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