What’s Wrong with Your Tech Hiring Process

Let’s talk about a hiring trap too many tech companies fall into: obsessing over algorithm interviews. You know the drill—red-black trees, linked lists, sorting algorithms, the works. These are the puzzles candidates sweat over, the ones that supposedly separate the “elite” from the rest. But here’s the truth: mastering algorithms doesn’t always mean someone’s a stellar developer.

Picture this: a team of 10 developers at a fast-paced tech giant (think Twitter-level). They’re all brilliant at algorithms, but the codebase? Chaos. No common patterns, no clean design—just a mess of code going in every direction. Why? Because algorithm wizards aren’t always business-savvy coders. Day-to-day work isn’t about crafting perfect binary trees; it’s about delivering features fast, keeping designs clean, and making code that’s easy to maintain.

Here’s the kicker: the best developers aren’t the ones who can solve a complex algorithm in record time. They’re the ones who can jump into a project, understand it quickly, and ship business value at lightning speed. In fact, for most teams, you only need one algorithm guru. The other nine? They should be fast, practical, business-focused coders who keep the machine running smoothly.

So why are we still stuck on algorithm-heavy interviews? It’s become the default, but it’s not the answer. Only about 1 in 15 companies nail a business-focused interview—one that tests real-world problem-solving with simple, practical coding challenges. And when those interviews are done right, they uncover developers who can hit the ground running.

Take this example: a VP of Engineering joined a company and tested their developers with a straightforward business problem. The twist? Most of the team failed it. They called the test “too easy,” but couldn’t deliver. Meanwhile, one US-based hire aced it, proving the approach worked. Rolling out this style of interview transformed hiring, bringing in developers who could dive into code, understand it fast, and deliver results—without overcomplicating things.

The lesson? Over-relying on algorithm interviews is like hiring a rocket scientist to fix your car. Sure, they’re brilliant, but they might overengineer the solution and slow you down. Instead, rethink your process. Design interviews that mirror real business challenges. You’ll build teams that move fast, deliver features, and keep your codebase clean.

💡Pro tip: If you do find an algorithm genius, pair them with your team for those rare, niche problems. But for the rest? Hire for speed, clarity, and business impact.

Ready to level up your hiring game? Share this with your tech leads and let’s spark a conversation!

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Thanks for reading,

CTO Teachings