What Is an AI Coding Round? How to Practice for One

An AI coding round is a coding interview where you are allowed, or expected, to use an AI assistant while you work. It usually gives you an existing codebase instead of a blank file, and it judges how you work with the AI as well as the code you end up with. This guide explains the format, lists who runs one (with sources), and gives a 2-week practice plan. For the rules each company sets, see our AI coding interview overview. To practice the round itself, AICodingRound gives you real tickets in multi-file apps; the free beta has limited places: get a place.

What an AI coding round is

A classic coding interview asks you to solve a self-contained problem from scratch, often an algorithm puzzle, with no help. An AI coding round changes three things:

1. You get an assistant. A chat panel, an AI that can edit files, or your own tool of choice, depending on the company.
2. The code already exists. You read a project with several files, find your way around, and change it. Google's reported pilot calls its version "code comprehension": read, debug and optimize existing code (Moneywise, citing Business Insider; reported).
3. The process is part of the grade. How you checked the AI's output, and whether you can explain the final code, matter as much as whether it works.

It is usually one round in a loop, not the whole loop. No report we found says Google or Meta dropped their classic coding rounds.

How much AI you get: three rules

First, find out which rule your round uses. Your recruiter can tell you.

• Chat-only. The AI answers questions and can read the code, but you type every change. Meta's AI-enabled round is reported to work this way: the assistant "can't directly edit your files" (Hello Interview; reported, not a Meta statement).
• Agent. The AI can write and edit code for you. Canva says it now expects backend, machine learning and frontend candidates to use AI tools, naming Copilot, Cursor and Claude as examples (Canva Engineering, June 11, 2025). CodeSignal sells "agentic coding assessments" where candidates use Cursor, Claude Code or Codex (CodeSignal).
• No AI. Many rounds still ban it. Anthropic's guidance says live interviews are done without AI "unless we indicate otherwise" (Anthropic). In a Karat survey of 400 engineering leaders, "62% of organizations still prohibit AI use in technical interviews" (Karat, January 7, 2026).

Using AI in a no-AI round is the fastest way to fail one. When in doubt, ask.

The tasks: bug hunt, feature, review

Most AI coding rounds use one or more of three task types.

• Bug hunt. You get a symptom ("back-to-back bookings are rejected") and a codebase. Reproduce it, find the cause, fix it, and show nothing else broke. Meta's round is reported to open with a bug-fixing phase (Hello Interview; reported).
• Feature. Add something to code you did not write: a new endpoint, a new rule, a new field. The hard part is fitting the project's existing patterns, not typing the code.
• Review. Read a pull request, often one an AI wrote, and decide what must change. GitLab runs a version of this for some positions: candidates review a merge request before a 90-minute call, and the page says "We encourage the use of AI in the interview process" (GitLab handbook). Our code review interview guide covers it.

Some rounds add a speed-up phase: the code works, but it is too slow on bigger inputs.

What gets judged

Put the public descriptions side by side and four things come up.

1. The result. Does it work, and did you break anything else on the way?
2. Verification. How did you check what the AI gave you? HackerRank's CEO lists one of the questions its AI interviewer asks: "How did you validate the AI-generated code?" (HackerRank)
3. Understanding. Can you explain the code, including the parts the AI wrote? Hello Interview quotes a reported internal line about Meta's round: "Should use AI, but need to show you understand the code" (Hello Interview; reported).
4. AI judgment. Did you give the AI clear, small tasks, and did you catch it when it was wrong? Canva lists "Critically reviewed and improved AI-generated code" among what successful candidates did (Canva Engineering).

Notice what is missing: typing speed and memorized algorithms.

Who runs AI-allowed rounds

"Confirmed" means the company said it on its own page or on the record. "Reported" means a third party describes it.

LinkedIn, Shopify and Stripe show up in candidate reports, but we found no company statement, so they are not in the table.

A 2-week practice plan

About an hour a day. Use an AI in every session, under the rule you expect in your round. Each step names a problem from our library.

Days 1 to 3: read before you touch. Open a project you have never seen. Before prompting, write down where a request enters, where data is stored, and which file owns the rule in the ticket. Then fix one small bug: Back-to-back bookings rejected (easy, about 20 min) and Invoice lines don't add up to the subtotal (easy, about 10 min).

Days 4 to 6: bug hunts from a symptom. Reproduce first, then form one hypothesis at a time. Ask the AI to explain one specific path, and check its answer against the code. Try A forwarded password-reset email still changes the password a day later (medium, about 40 min).

Days 7 and 8: add a feature. Read how the project already does similar things, then build to match. Try Book a room every week (medium, about 45 min). Run the full test suite, not only your new tests.

Days 9 and 10: review AI-written code. Read the ticket, then the PR description, then the code, then the tests. Every gap between them is a comment. Try Review the AI's reminders PR (medium, about 30 min).

Days 11 and 12: make it fast. Measure before you change anything, and show the number before and after. Try The invoice list takes seconds to load a full page (easy, about 25 min).

Days 13 and 14: full rounds. Set a timer, pick a problem you have not seen, and finish with two minutes of explanation out loud. Try Flash sale sold 53 units of a kettle with 40 in stock (hard, about 60 min). Then write down the question you answered worst and practice it again.

The AI round is usually added next to the classic rounds, not instead of them. Our LeetCode alternatives guide maps tools to rounds.

Practice the AI coding round on AICodingRound

We built AICodingRound for exactly this round, and every day of the plan above runs on it.

• Real codebases. 49 public problems in Python, TypeScript and SQL on Postgres: bug hunts written like real bug reports, feature builds, reviews of AI-written pull requests, test writing and code-reading questions. Each runs in a cloud workspace with an editor, terminal, tests and a live preview.
• Your own AI, in coach mode. Bring your own Claude or Codex. It reads code and explains, but it does not write the fix for you, which is close to a chat-only round. For a no-AI round, leave it closed.
• Checked like real work. Tests check that your fix works and that nothing else broke.
• A debrief. A few questions about your own change: what caused the problem, how you checked it.
• Levels, not a raw score. The report shows Strong, Solid or Developing for each skill, including how you used AI.

Keep algorithm practice for the classic rounds; we have no algorithm or system design problems. For the AI round, start with day 1 today. The beta is free and places are limited: get a place.

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