When to Use AI in a Coding Interview (and When Not To)

TL;DR

Most live technical interviews still prohibit AI tools. Take-home assessments vary widely.
Always ask explicitly before the interview starts. Ambiguity is not permission.
"AI allowed" in a take-home usually means using it as a reference, not having it write your solution for you.
The bigger risk: if you lean on AI to produce code you can't explain, you'll fail the follow-up conversation.
This is a risk management question. Understand the stakes, then decide.

The honest starting point: nobody fully agrees on this yet.

The norms around AI use in technical interviews are shifting faster than companies have updated their official policies. You will talk to engineers who think using AI in an interview is straightforwardly cheating. You will talk to others who think prohibiting AI tools is like prohibiting Stack Overflow in 2015. You will encounter take-home assessments where the instructions explicitly allow AI tools and live interviews where the company hasn't addressed the question at all.

This ambiguity is real, and pretending there's a clear universal answer would be misleading. What there is: a way to think about it clearly, so you can make decisions that don't blow up in your face.

The Current State of Live Technical Interviews

Most live coding interviews, the kind where you share your screen with an interviewer and write code in real time, still expect you to work without AI assistance. This is often implicit rather than stated. The interviewer is watching you think and code. The evaluation is of your reasoning process, not just the output.

Even in companies that use AI tools heavily in day-to-day engineering work, the technical interview is generally testing your underlying capability. The logic is that the interviewer needs a signal about what you can actually do, and that signal is harder to read if AI is doing part of the work.

There's also a practical reason: if you use AI to generate code during a live interview and the interviewer asks you to explain a specific line or modify the approach, you need to be able to do that in real time. If you can't, you've created a worse impression than if you'd written slightly less polished code yourself.

The risk of using AI in a live interview without explicit permission is high. The upside is modest. If you're using AI tools well in your preparation, your live performance should reflect that learning. How Much LeetCode Is Enough covers the preparation side in detail.

Take-Home Assessments: A Different Set of Rules

Take-home coding challenges are where the norms are most varied. Companies fall into roughly three categories:

Explicitly AI-allowed. Some companies now explicitly state that AI tools are permitted. This reflects the reality that engineering work today involves AI tools, and they want to see how you use them. If the instructions say AI is allowed, use it. But understand what that means in practice.

Explicitly AI-prohibited. Some companies specify no AI tools, sometimes including no Stack Overflow, no external resources beyond documentation. This is an integrity requirement, not just a suggestion. If you use AI in a no-AI assessment and it comes up later, the outcome is bad.

Silent on the question. This is the most common and most problematic case. The instructions don't mention AI at all. Here you need to ask.

The right move when instructions are silent: email the recruiter or hiring manager before you start. Ask something like: "The instructions don't mention AI tools specifically. Is it acceptable to use AI coding assistants as a reference during the assessment?" This takes two minutes. It removes ambiguity. It demonstrates that you take the assessment seriously.

You might get "yes," "no," or "use your best judgment." Each of those is useful information. "Use your best judgment" generally means they're not going to penalize you for using AI appropriately, but they will ask you to explain your code, so you need to be able to do that.

The take-home challenge guide at Take-Home Coding Challenge Guide covers the full process of how to approach these assessments. The AI question is one piece of it.

What "AI Allowed" Actually Means in Practice

The permission to use AI tools in an assessment is not the same as permission to have AI write your solution for you. This distinction matters.

Using AI as a reference means: asking it to explain a function signature, looking up syntax for something you don't remember, asking it to describe a data structure's time complexity. This is roughly equivalent to using documentation. You understand what you're doing. You're using AI to answer specific questions quickly.

Using AI to write your solution means: describing the problem, getting back code, pasting it in, submitting it. You may not fully understand what was generated. You can't necessarily explain the decisions in it.

The second approach is risky even when AI use is permitted, because take-home assessments almost always have a follow-up conversation. An interviewer will ask you to walk through your code, explain your choices, and sometimes ask you to extend or modify it on the spot. If you can't do any of those things because you didn't write the code, the take-home didn't help you.

The practical question isn't "is AI allowed" but "can I defend this code in a conversation without access to AI?" If yes, you're fine. If no, you have a problem regardless of what the rules say.

The Explain-It-Live Test

This is the most useful heuristic for deciding how much to use AI in any interview context: after you write or generate code, can you explain every line of it in a live conversation without looking anything up?

Apply this test to your portfolio projects too. Apply it to any code you submit in an assessment. If you can pass this test, the question of whether you used AI to help produce the code is mostly irrelevant. You understand it. You can modify it. You can defend the decisions.

If you can't pass this test, using AI helped you produce code you don't own intellectually. That will show up in the follow-up conversation, and it will cost you the offer.

This framing takes the moral dimension out of it and puts the focus where it belongs: on whether you actually know what you built. AI coding tools for junior engineers covers why this matters more broadly for your career.

How to Get to a Point Where You Don't Need AI to Pass Interviews

The cleanest solution to the AI-in-interviews question: become good enough at coding that you don't need AI assistance to perform well in a live technical interview.

This is not a suggestion to stop using AI tools. It's a suggestion to use them in your preparation in a way that builds genuine capability rather than dependency. If you've been practicing problems with AI assistance in a way that builds understanding, your live performance will reflect that. If you've been using AI to generate answers you memorize, you'll hit a wall under pressure.

The specific practice that matters: write code without any assistance, regularly, as part of your preparation. Solve problems on paper. Do timed sessions with no external resources. Then review your solutions with AI help: ask it to explain better approaches, identify what you missed, and give you harder variations. The assistance goes into your learning loop, not your performance moment.

There's a version of technical interview prep where you use AI tools extensively and come out stronger for it. There's another version where you use AI tools extensively and come out weaker. The difference is in what you're using them for.

Clarifying Before You Start

A practical checklist for any technical assessment:

Read the instructions carefully for any mention of AI tools. If AI is explicitly allowed or prohibited, you have your answer.

If the instructions are silent, ask before you start. A brief email to the recruiter asking about resources takes less than two minutes and removes ambiguity.

In live interviews, if you're uncertain whether you can use a browser, documentation, or any external resource, ask at the start. Most interviewers will tell you exactly what's expected.

If the interview explicitly allows AI and you choose to use it, treat it as a reference tool. Use it to answer specific questions quickly, not to generate solutions to the core problem.

After any AI-assisted code you write: apply the explain-it-live test. If you can't pass it, go back and understand the code before you submit.

The Stakes Are Not Equal Everywhere

One more thing worth saying: the stakes of using AI inappropriately vary by context.

Using AI in a take-home when it's prohibited is a straightforward integrity issue. If it's discovered, the outcome is a rescinded offer and potentially a conversation that follows you.

Using AI in a live interview that explicitly prohibits it is visible to the interviewer. You're on screen. They can see when you switch windows.

Using AI in an assessment where it's permitted is fine. The question is only whether you understand what you produced.

Getting this calibration right is what separates candidates who treat the interview process seriously from those who are trying to find shortcuts. The companies that are worth working at are evaluating whether you can actually do the job. The best preparation for that is actually being able to do the job.

The prove your skills are real article goes into depth on a closely related question: how to talk about AI use in your portfolio work honestly without it undermining your credibility. The same principles apply to interview contexts.

The bottom line: understand the rules for each specific assessment, ask when the rules aren't clear, and make sure you can defend any code you submit regardless of how you produced it. That approach manages the risk correctly.