How to Prepare for AI-Assisted Coding Interviews (When Every Company Has Different Rules)

Depending on where you interview this year, using AI during a coding interview is either grounds for rejection, tolerated without comment, actively expected, or the entire premise of the exercise. All four of those are true somewhere in mid 2026, sometimes inside the same company, and the format churn is moving faster than most prep advice has kept up with. I flagged this briefly at the end of new grad vs senior loops, and enough has happened since that it needs more than a paragraph.

I've conducted a lot of coding interviews, but never an AI-enabled one. The format descriptions below come from public writeups and consistent candidate reports, not from interviews I've conducted myself. What I have seen directly is the layer underneath the formats (what interviewers can and cannot grade, and why your narration carries so much of the score), and I'll say which of the two I'm doing as we go.

The four rule regimes

There is no standard right now, and it helps to see how wide the spread is. Whether you can use AI in a coding interview currently lands in one of roughly four buckets, and candidate reports suggest the bucket can differ between teams at the same company:

Banned. Still the most common arrangement as far as I can tell, particularly for phone screens, and public reporting suggests some companies are shifting interviews back to in-person partly as enforcement. If this is your loop, the rule is the rule. Using AI where it's prohibited is cheating, and being caught tends to end your candidacy with that company permanently.

Allowed, no big deal. Your normal tools are fine, and the interviewer evaluates roughly what they always evaluated. Reports from this bucket are the least consistent of the four, which makes it the riskiest one to assume you're in without asking.

Expected. The interview environment ships with an assistant, and ignoring it comes across a little like refusing to open the debugger. You might survive it, but you're leaving part of the designed exercise untouched.

Built around it. The most public example is Meta's AI-enabled coding interview, which interviewing.io has documented in a detailed walkthrough with real prompts and examples. Candidates work in an editor with an assistant built in, and how well you drive the tool is explicitly part of the evaluation.

Ask your recruiter exactly what your loop allows

Given a spread that wide, the single highest-value prep step is one email. Ask, per interview, some version of the following:

• Will any interview include an AI assistant in the coding environment?
• May I use my own tools (Copilot, ChatGPT, whatever I code with daily), or only what's provided?
• If an assistant is available, is my use of it evaluated, or is it simply there?
• Does the phone screen follow different rules than the onsite?

Recruiters handle logistics questions constantly, and asking for the rules in advance has never, in any loop I helped coordinate, counted against a candidate. The real risk is the other way around: several weeks of drilling for a ruleset your loop doesn't use.

Practicing to drive an assistant on a clock

When an interview permits or expects AI, what's being sampled (going by the public writeups, and by what the format seems built to reveal) is whether you can break a problem down, delegate the right pieces, and catch the tool's mistakes under time pressure. Most working engineers have been practicing exactly that at their desks for a couple of years. The new part is doing it out loud, timed, while being graded, and that combination needs practice of its own. If you're working through something like the four week prep plan, these slot naturally into the coding-focused weeks.

1. Prompt in scoped pieces. The pattern that comes through in the published Meta walkthrough is that pasting the entire problem in and accepting the answer wholesale goes over poorly, and it leaves you defending code you never reasoned through once the follow-up questions start. Requesting a specific function, a parser, or test scaffolding keeps you in the driver's seat.
2. Verify the output like a fast, confident junior pair wrote it. Read every line before accepting, and say the verification out loud: "this looks close, but it's storing seen characters in a set and I need last-seen indexes, so let me fix that." One sentence like that demonstrates you read the code, understood it, and caught the gap, which by candidate accounts is a large part of what these interviews probe.
3. Narrate the delegation decision itself. "I'll have it generate the input parsing and test cases, since those are mechanical, and I'll write the core logic myself because that's what's actually being assessed." A judgment call made silently is invisible to the person grading you, exactly as in a conventional interview.
4. Run full timed practice interviews. One medium problem, 35 minutes, assistant on, phone recording, narrating throughout. On playback, notice where the long silences are; it's almost always while you're reading AI output, which is when narration matters the most. The first recording tends to be humbling. Everyone's is.

Why communication signal grows when AI writes the boilerplate

This part I did see firsthand. Every coding rubric I graded against included communication and reasoning somewhere, and those were always the easiest sections to fail in silence (I went deep on this in talking while coding; the short version is that interviewers can't grade what they can't hear). An assistant in the loop strengthens that effect considerably. Once clean boilerplate appears in seconds, the code on screen tells the interviewer very little about you, because they know the tool produced it. What remains observable is which pieces you delegated and why, what you checked before trusting the result, and how you reacted when it was subtly wrong. All of that reaches the interviewer through your voice or it doesn't reach them at all. In practice, the AI-enabled formats push the coding interview toward a think-aloud judgment exercise with some typing attached, and narration was already the most underpracticed skill in the room.

What transfers through the format churn

I'm a Warhammer 40k nerd, and each new edition forces the whole community to relearn the meta: lists that took months to tune stop working, everyone grumbles for a while, and then everyone reads the new rulebook and adapts. The reliable pattern is that the same players keep reaching the top tables across editions, because the durable skills (reading the board state, trading efficiently, knowing why every unit is in the list) pass straight through the rules changes. AI-assisted interviewing is an edition change. The rulebook differs company to company right now, which is why the recruiter questions matter, and the underlying game is unchanged: decompose the problem, verify work you didn't personally type, keep the other person oriented on your thinking. Practicing with an assistant also helps outside the interview entirely, since scoping requests, auditing output, and deciding what to keep for yourself is increasingly what the job is.

If you want a place to build the out-loud half of this, practicing against something that responds and pushes back, that's what we built Preppable to do. And for the driving-the-assistant half, a free-tier assistant, a timer, and a phone recording cover most of it, with a patient friend playing interviewer as the upgrade. Whichever setup you pick, get the practice in before your loop's rules catch you unprepared.