Technical Interviews are the Solution: But, What's the Problem Again?
Technical Interviews are Broken
Let’s get this out in the open. Everyone knows the coding interview process is bogus. Leetcode algorithms, rehearsed STAR questions, and 8-hour take-home assignments tell us next to nothing about a candidate. It selects for people who are either lucky, stubborn, or confident and thick-skinned. People with minimal family obligations or community involvement. Able to grind out 600 miserable hours on leetcode, and enough money to not work while they do it. It also screens out people who are reflective, collaborative, or sensitive. These high-stakes, unfamiliar settings can activate the brain’s stress circuits. Neuroscientists tell us that the amygdala interprets social evaluation as a threat, which can shut down access to the very skills we’re trying to assess: problem-solving, clear thinking, and communication. But choking in these contexts doesn’t mean a candidate is weak or unqualified. In fact, it’s often the opposite. These are people with finely tuned self-monitoring systems. Given psychological safety and time to integrate, they often become your strongest teammates.
We’re Measuring the Wrong Things
We have the desire to compare apples to apples, so having atomic little puzzle tests help us to judge people’s performance relative to each other. Objectively that feels more fair, but it’s not a good predictor of a person’s performance as a team member. We may as well just use their SAT scores.
What actually distinguishes good engineers?
- Balance future-proof code against the reality of constant requirement changes.
- Balancing effort and priorities with imperfect information
- Knowing when to abstract and when not to (DRY vs WET)
- Thinking like a User and pushing back when appropriate
- Staying curious — but not chasing every shiny new framework
- Knowing when to let business goals override engineering purity (and when not to)
These are complex, contextual skills that don’t shine in a 45-minute Leetcode session.
But FAANG Companies Do It!!!
FAANG companies argue that leetcode algorithms are just little puzzles, and smart people are good at puzzles. In reality, FAANG companies are now full of people who spent months studying those logic puzzles on leetcode.com so that they would already know the answer in the interview. That’s their prerogative.
The problem is that it's not just about the time and effort candidates are spending. Applying and interviewing for jobs is emotionally exhausting, and rejection hurts. It hurts real bad. People in r/leetcode regularly say they feel worthless after an interview. r/cscareers is mostly people talking about changing careers. Suicide is mentioned alarmingly often. It’s getting out of hand. So let’s review, we’re:
- Burning out strong candidates
- Driving out people who don’t perform well under artificial pressure
- Selecting against neurodiverse people, and polymaths
- Reinforcing a monoculture of people who “interview well”
There’s No Perfect Interview, But There Are Better Ones
No hiring system is flawless. But the current standard manages to be both actively harmful and ineffective at identifying good hires.
I thought that the rise of AI-assistant interview “cheating” tools would force companies to re-examine their hiring processes, but instead they’re monitoring candidates eye movements. Someone needs to say it: This is dumb. Let’s rethink the technical interview.
So, fellow engineers, what was the problem technical interviews were invented to solve in the first place?
Bias Declaration: I’m a white, English-speaking male with 20+ years of engineering experience. I write this as someone who’s relatively privileged in tech and still struggles with today’s interview norms. If you're from a different background and have a different take, I'd love to hear it, especially if it challenges what I've said here. Diversity in hiring matters to me, and I’m curious if some groups feel differently.