The Great Debate: Have We Gone Overboard with DSA Rounds?

If you have applied for a software engineering role at any major tech company in the last decade, you know the drill. You spend weeks or even months grinding LeetCode, memorizing complex algorithms, and practicing data structures that you will likely never use in your day-to-day work. Then, you undergo several rounds of high-pressure coding interviews where you have forty-five minutes to solve a problem that took a computer scientist years to discover.

This is the state of technical interviewing today. The industry has become obsessed with Data Structures and Algorithms (DSA) as the primary filter for hiring developers. But is this really the best way to find great engineers? I believe we have gone overboard with DSA rounds, and it is time we had a serious conversation about what we are actually measuring.

The Origin of the Algorithm Interview

The rise of DSA interviews can be traced back to companies like Google and Microsoft in the early 2000s. The logic was simple: these companies were dealing with problems at a massive scale, and they needed engineers who understood the fundamental principles of computation. They wanted people who could think deeply about time and space complexity.

At that time, this made sense. But as these companies grew and became the industry leaders, their hiring practices were copied by everyone else. Suddenly, even small startups building simple web apps were requiring candidates to solve hard-level dynamic programming problems.

The result is a standardized testing culture in software engineering. We have created a system that rewards people who are good at a very specific type of puzzle-solving, rather than people who are good at building software.

The Disconnect Between DSA and Real Work

Most software engineering work today is not about writing efficient sorting algorithms from scratch. It is about building reliable systems, integrating with third-party APIs, managing complex state, and collaborating with a team. It is about understanding business requirements and translating them into maintainable code.

In my years of professional development, I have almost never had to implement a red-black tree or a graph traversal algorithm during a normal workday. When I need those things, I use a well-tested library that has already implemented them far better than I ever could.

The skills that actually make someone a great developer—things like architectural thinking, testing discipline, and empathy for users—are almost never measured in a DSA interview. We are testing for a tiny subset of the skills required for the job and ignoring the rest.

The Problem of Inclusivity and Bias

DSA rounds also create significant barriers for talented developers. People who don’t have the time to spend months practicing competitive programming—such as those with families or those from less privileged backgrounds—are at a massive disadvantage.

This leads to a homogenization of the workforce. We end up hiring people who have a similar educational background and who have had the luxury of time to prepare for these specific types of interviews. We miss out on great engineers who have unconventional paths into the industry but who have deep practical experience.

It also leads to ageism. Younger developers, who are fresh out of college and have these algorithms at the top of their minds, often perform better in DSA rounds than experienced developers who haven’t touched these concepts in years. But who would you rather have building your production system: someone who can solve a LeetCode hard problem in thirty minutes, or someone who has ten years of experience building and maintaining complex systems?

The Rise of the Grind Culture

The obsession with DSA has created a toxic grind culture in our industry. There are entire websites and communities dedicated to hacking the technical interview. People are studying how to pattern-match common problems rather than learning the underlying principles of computer science.

This is a massive waste of human potential. Think about all the amazing projects and tools that could have been built with the thousands of hours that developers spend every year practicing for interviews that have nothing to do with their work.

We are training an entire generation of developers to be good at passing tests rather than being good at solving real-world problems.

A Better Way Forward

I am not saying that we should eliminate DSA entirely. Understanding the fundamentals of computer science is important. But it should not be the only thing we measure.

We need to move towards more holistic and practical interviewing methods. Some companies are already doing this. They are using take-home assignments that mimic real-world tasks, or they are doing pair-programming sessions where the focus is on collaboration and problem-solving rather than getting the perfect answer.

They are asking questions about system design, code review, and testing. They are looking for evidence of a candidate’s ability to learn and adapt. These methods are more predictive of how a developer will actually perform on the job.

Why it Matters for My Clients

For my clients, my stance on DSA means that I value practical results over theoretical puzzles. When I am building a project, I am not trying to impress anyone with my knowledge of obscure algorithms. I am focused on building a product that works, that is maintainable, and that solves their problems.

I bring a wealth of experience in building real systems to every project. I know how to make trade-offs between speed and quality. I know how to build for the long term. These are the skills that actually deliver value to a business, and they are the skills that I have honed through years of hard work, not just by grinding LeetCode.

Conclusion

The technical interview process is broken. We have let a single, narrow metric define what it means to be a good software engineer. It is time we recognized that our industry is much broader and more complex than a few algorithm puzzles.

By moving towards more practical and inclusive hiring practices, we can build better teams and a better industry. We can stop the mindless grind and start focusing on what truly matters: building great software that makes a difference in the world.