Practice Coding Interviews with a Real AI Interviewer

You already know how to solve coding problems. But solving and performing are two different skills. Interviews test whether you can think out loud, clarify ambiguity, defend trade-offs, and write working code under pressure — while being questioned in real time. That skill does not come from grinding problems alone. It comes from practice under interview conditions.

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What is an AI coding interview?

An AI coding interview on intervu.dev is a structured, real-time mock interview session where the AI acts as your interviewer. It presents a problem, listens to your approach, asks probing follow-up questions, gives hints if you are stuck, and evaluates how effectively you communicate your thinking.

Each session follows the real FAANG interview flow: clarify requirements → discuss approach → code a solution → test edge cases → discuss complexity and trade-offs. Feedback is signal-based — you receive evaluation on communication clarity, problem-solving approach, code quality, and how well you handle pressure. Not just whether your solution passed test cases.

Sessions are available on demand. No scheduling, no waiting for a human interviewer, no cost to start.

How it works

01

Pick your problem

Choose from FAANG-style problems by difficulty, or paste any LeetCode URL to practice with a problem you're already working on.

02

Think out loud

The AI interviewer presents the problem and listens as you clarify requirements, ask about edge cases, and walk through your approach.

03

Code under pressure

Write and run your solution in real time while the AI asks follow-up questions about your choices, just like a real interviewer would.

04

Get signal-based feedback

Receive structured feedback on communication, trade-offs, code quality, and problem-solving approach — not just a pass/fail.

AI practice vs. human mock interviews

AI mock interviews and human mock interviews serve different roles in your preparation. AI sessions are available instantly, 24/7, with no scheduling friction — you can do ten sessions in the time it takes to schedule one with a human interviewer. AI gives consistent, unbiased feedback on the same dimensions every time, which makes it ideal for building volume and muscle memory.

Human interviewers provide nuance, emotional read, and real-world company context that AI cannot fully replicate. They catch soft signals — nervousness, pacing issues, interpersonal dynamics — that matter in real interviews.

The optimal strategy: use AI to build volume and sharpen fundamentals, then use human mock interviews for final polish before your target company interviews.

Frequently asked questions

Is this the same as asking ChatGPT to interview me?
No. ChatGPT is a general-purpose chatbot — you have to prompt it correctly, manage the conversation structure yourself, and it has no code execution environment. intervu.dev is purpose-built for coding interviews: it runs a structured session with a real interview flow, executes your code in a sandboxed environment, and evaluates the specific signals that FAANG interviewers assess — communication, trade-offs, code quality, and problem-solving approach.
What programming languages are supported?
intervu.dev supports Python, JavaScript, TypeScript, Java, C++, and Go. You choose your language before the session starts, and the AI generates appropriate starter code and scaffolding for that language. The code execution environment is fully sandboxed and supports standard library imports.
Do I need to sign up to try it?
No. Guest mode is available with no sign-up required — you can start a full AI coding interview session immediately. Creating a free account unlocks session history, performance tracking, and additional features.
How is the AI feedback different from LeetCode's feedback?
LeetCode tells you if your solution is correct and efficient. intervu.dev evaluates the dimensions that human interviewers actually score: how clearly you communicated your approach, how well you handled ambiguity, whether you considered edge cases proactively, and how you responded to follow-up pressure. This is the gap between solving problems and getting offers.

The work you put into LeetCode matters. Make it count in the interview room.

Grinding problems builds your algorithmic foundation. But without simulating the interview itself — the pressure, the follow-ups, the communication — that work does not fully translate to offers. Practice the way the interview actually works.

Start a Free AI Coding Interview