Can You Use AI in Coding Interviews?
The honest answer is: it depends on the company, the role, and the interview format.
Some companies still expect a traditional coding interview with no AI assistance. Some allow approved tools in a controlled environment. Some explicitly want to see how you work with AI because that reflects day-to-day engineering now. The mistake candidates make is assuming the rules are obvious. They are not.
If you are interviewing in 2026, you should treat AI usage as part of your interview preparation, not as an awkward side question.
Ask the Recruiter Before the Interview
Do not guess. Ask directly and professionally:
"Will AI coding assistants or autocomplete tools be allowed during the coding interview?"
"If AI tools are allowed, are there specific tools or usage guidelines I should follow?"
"Will the interviewer expect me to explain any AI-generated code I use?"
This does two things. First, it protects you from violating the company's rules. Second, it signals maturity. Good candidates do not try to find loopholes. They clarify expectations and operate within them.
If the recruiter says AI is not allowed, respect that. If the recruiter says AI is allowed, do not treat that as permission to outsource the interview. It changes the format, not the bar.
What Interviewers Still Evaluate
AI can generate code quickly, but interviewers are rarely evaluating typing speed alone. They are looking for:
Problem understanding. Did you clarify the requirement, edge cases, and constraints before jumping into a solution?
Algorithmic reasoning. Can you explain why your approach works, what its complexity is, and where it might fail?
Debugging skill. When the code breaks, can you isolate the issue logically or do you just keep asking the tool for another version?
Code judgment. Can you identify whether the generated code is maintainable, testable, and appropriate for the problem?
Communication. Can you keep the interviewer with you while you think through the problem?
Those signals still matter. In some ways, they matter more when AI is present because the interviewer has to separate tool output from your actual engineering judgment.
If AI Is Allowed, Use It Transparently
If the format allows AI, say what you are doing:
"I am going to ask the assistant for a first-pass implementation, then I will review it for edge cases and complexity."
"This generated solution is close, but I do not like how it handles empty input. I am going to adjust that."
"The tool suggested recursion here. I think an iterative approach is safer because of stack depth."
That kind of narration is powerful. It shows that you are still driving. You are using AI as a collaborator, not hiding behind it.
The worst version is silent copy-paste. The interviewer sees code appear, but they cannot see your reasoning. Even if the code works, the signal is weak.
Prepare for AI-Aware Interview Questions
More interviewers are adding questions like:
"What would you ask AI to help with here?"
"Review this AI-generated solution. What is wrong with it?"
"The assistant produced this test suite. What cases are missing?"
"Would you ship this code to production?"
These are good questions because they mirror real engineering work. Teams are already reviewing AI-assisted pull requests, debugging generated code, and deciding where automation helps or hurts. Candidates who can evaluate AI output calmly will stand out.
What Not to Do
Do not use an AI tool secretly when the rules prohibit it. That is not clever. It is an integrity issue.
Do not accept the first answer without review. Generated code often looks confident while missing subtle cases.
Do not let AI replace your explanation. The interviewer needs to hear your reasoning.
Do not over-optimize for tool tricks. The best signal is still clear thinking, structured problem solving, and solid fundamentals.
How to Practice
Practice in both modes.
First, do traditional coding practice without AI. You still need the fundamentals: data structures, common patterns, complexity analysis, testing, and debugging.
Second, practice AI-assisted problem solving. Ask for a solution, then critique it. Look for missing edge cases. Rewrite unclear parts. Add tests. Explain what you would and would not trust.
Third, practice saying your reasoning out loud. This is where many candidates struggle. If you use AI silently, you may look faster but less credible. If you use it thoughtfully and explain your judgment, you look like an engineer who can operate in the real world.
Bottom Line
AI is changing coding interviews, but it is not removing the need for engineering fundamentals. The strongest candidates will be comfortable in both worlds: able to solve problems without AI, and able to use AI responsibly when the format allows it.
If you are preparing for top tech or AI company interviews, pair this with a full preparation plan. Start with How to Prepare for a Top Tech Company Interview, then build realistic practice through Software Engineer Interview Coaching or Big Tech Interview Coaching.
About Me
Nimesh Patel is an engineering leader and career coach with over 20 years of experience building cloud-native enterprise and consumer software systems in Big Tech (including Google) and high-growth AI startups. He has led globally distributed engineering organizations of 60+ engineers and leaders, conducted 650+ interviews across engineering, management, and executive roles, made 50+ hires, and coached and promoted 30+ engineers and leaders. He provides interview and career coaching through ScaleYourCareer. Follow him on LinkedIn.
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