How AI Is Changing Tech Interviews (And What Stays the Same)

AI can write code. Interviewers know this. So what happens to coding interviews?

The short answer: they're evolving, not disappearing. Here's what's actually changing.

Take-homes are getting harder

Take-home assignments used to be "build a small app in 4 hours." Now some companies give problems that are harder to AI-assist: design decisions, architecture trade-offs, code review of deliberately buggy code. The goal: can you reason about the problem, not just produce working code?

If you get a take-home, expect questions like "Why did you choose X over Y?" or "How would you scale this?" The interviewer wants to see your thinking, not just your output.

Live coding is focusing on communication

When you code live, the interviewer is watching how you think. Do you talk through the problem? Do you consider edge cases? Do you respond to hints? Can you debug when something breaks?

AI can't help you there. The interviewer is assessing your process. They want to see you reason, make trade-offs, and communicate. The code matters, but the journey matters more.

System design is more important

System design is harder to AI-assist. You're drawing, talking, and making decisions in real time. Many companies are putting more weight on it—especially for senior roles.

If you're preparing for interviews in 2025, don't neglect system design. It might be the differentiator.

"How do you use AI?" is a real question

Interviewers are asking. They want to know:

• Do you use it? (Most candidates do.)
• Do you understand its limitations?
• Do you review its output?
• Can you work effectively without it?

Have a clear, honest answer. "I use it for boilerplate and exploration, but I always review and understand the code." That's fine. Pretending you don't use it is weird. Pretending it's flawless is naive.

What hasn't changed

Fundamentals still matter. Data structures, algorithms, system design concepts—you need to understand them. AI can help you apply them faster, but it can't fill gaps in your understanding.

Communication still matters. Can you explain your thinking? Can you collaborate? Can you handle feedback? Those skills are as important as ever.

Practice still works. The candidates who do well are the ones who practiced. Mock interviews, timed problems, system design sessions—they all help.

How to prepare

Prepare for both worlds: one where you have AI (take-homes, daily work) and one where you don't (live coding, whiteboard design). Practice explaining your reasoning. Practice debugging. Practice system design out loud.

The interviews are changing. The preparation isn't: understand the fundamentals, communicate clearly, and practice under pressure.