"Can I use AI in my coding interview?" The honest answer in 2026 is: it depends on the round, and you have to ask. Here's what has verifiably changed, from published employer guidance rather than anecdotes.

AI-allowed and AI-prohibited rounds now coexist

  • Canva (announced June 11, 2025) replaced its Computer Science Fundamentals screen with an AI-assisted coding screen for backend and frontend roles. AI use is expected, and the problems are realistic product challenges, not LeetCode with an assistant switched on.
  • Anthropic's candidate guidance (updated July 10, 2025) says the opposite by default: no AI in live interviews or take-homes unless explicitly permitted. Yet its January 21, 2026 engineering article permits AI for the performance-engineering take-home it describes. Even one employer has exceptions.
  • Microsoft's technical-interview guidance still covers problem solving, coding, testing, algorithms, data structures and complexity.

The takeaway: an employer's enthusiasm for AI tells you nothing about a specific round. Confirm permission separately for every round.

Proctoring isn't permission

CodeSignal documents proctored assessments with camera, microphone, screen sharing, photo ID and recordings reviewed by its verification team. Monitoring tells you how you're watched, not which tools are allowed. Ask your recruiter:

  • Are AI chat, code generation, inline completion and agent features allowed?
  • Can I use docs, web search, my own editor or a project template?
  • Must I use a supplied assistant or account?
  • What needs to be visible, recorded or submitted, including prompts?
  • What should I do if the approved tool fails?

What's being graded in AI-allowed rounds

Canva's October 20, 2025 interviewer guide lists engineering problem-solving, technical depth and ownership, and AI collaboration as evaluation areas. Anthropic's October 16, 2026 report on its own hiring scorecards found comments on autonomy and judgment rose the most. That's evidence about one company, not an industry standard.

In practice, show control: clarify requirements, review every generated change, test behavior, and defend your decisions. If an assistant picks a different reading of the requirements than you did, point out the mismatch instead of accepting plausible-looking code.

Take-homes: AI permission isn't automatic

If the instructions are silent, ask. Silence isn't permission. Also ask whether you may send the assignment or its data to an external AI service. If AI is allowed, submit work you can defend, with a README covering how to run it, how you interpreted ambiguous requirements, the design decisions you made and rejected, known limitations, and what the assistant contributed versus what you checked yourself. Never claim you wrote generated code by hand.

A practice plan for both formats

  1. Unaided: disable completions, solve a bounded problem in your interview language (clarify, implement, test, analyze complexity), then note where you got stuck.
  2. Assisted: write your plan first, delegate one bounded subtask, inspect every change, add a test the assistant didn't propose, and make one follow-up change yourself.
  3. Review code you didn't write: e.g. a booking-overlap function that wrongly treats [10, 11) and [11, 12) as conflicting. Find the smallest failing case, write a test that tells the right behavior from the wrong one, and make the smallest fix.

The full article, with the preparation categories and a step-by-step review exercise: Coding Interviews in the Age of AI: What Changed.

This post was written with the help of AI, as a summary of the StackChief article above.