A useful first technical round gives an engineer enough information to decide what to explore next. The candidate should do some real work, explain the approach and have room to ask questions. Hiring teams now have AI interviewers that can conduct that round without an engineer joining every session.
This guide explains what an AI coding interview can do, how to set one up and how to check whether it is improving your developer shortlist.
What Can an AI Coding Interviewer Do Today?
An AI interviewer can ask a candidate to write and run code, discuss an approach, investigate a failed test and explain a design decision. It can ask follow-up questions based on the work, so the conversation develops as the candidate solves the problem.
Fabric’s developer interviews combine coding, debugging, system design and technical discussion. The aim is to conduct the first technical round: see the candidate work, explore their reasoning and give the panel a detailed assessment to review.
For example, a candidate might investigate an API that creates duplicate records. They can ask about the requirements, reproduce the failure, change the code and test the result. The interviewer can then explore why the fix works and what happens under load.
This should feel collaborative. Candidates need to be able to ask a question, rethink an approach and discuss a trade-off. A spoken quiz about past projects cannot show those skills as clearly as doing the work.
AI-assisted work is another option. OpenRound, part of Fabric’s technical hiring offering, lets candidates work in an existing codebase with AI coding tools. You can assess how they guide the tools and verify the result, while keeping independent coding rounds for skills you want to test without assistance.
How to Set Up an AI Coding Interview
1. Use a Practical Engineering Task
Choose a problem that resembles the role. A backend candidate might fix an endpoint that mishandles retries. A frontend candidate might repair a form’s loading and error states. A data engineer might correct a query that double-counts transactions.
An existing codebase can be more useful than a blank editor. It shows whether the candidate can read unfamiliar code, locate the relevant part and make a safe change.
Keep the task small enough to leave time for discussion. Provide the requirements, a working environment and the rules for documentation and AI tools. Include the expected tests and review criteria in the setup so the interview assesses the skills you intended.
2. Check the Candidate Experience Yourself
Take the interview before sending it to applicants. Pause while thinking. Ask for clarification. Explain an approach that needs a little time. The interviewer should respond to those behaviours without repeatedly cutting in or rushing to the next question.
A good AI coding interview lets candidates code, run tests and discuss what they find. They should be able to collaborate with the interviewer throughout the task.
Fabric combines a responsive voice with few interruptions and supports resuming after a connection break. Send clear computer and headset instructions with the invitation. Coding needs a keyboard and enough screen space, even when the platform also supports phone-based conversations.
3. Review Possible Cheating Before the Next Round
A correct solution is less useful if the candidate cannot explain how it was produced. For independent rounds, review signs of undisclosed help alongside the technical result.
Fabric’s cheating detection flags possible help from phones, second screens and AI interview assistants. Check the recording and context before deciding what a flag means. A short follow-up on the candidate’s own code can help resolve an unclear result.
For an OpenRound project where AI is allowed, focus on ownership of the solution. Did the candidate understand the generated code, test it and catch mistakes? Permitted AI use and hidden assistance are different assessment questions; the invitation should make the rules clear.
4. Give the Panel a Detailed Candidate Scorecard
The next engineer should receive more than a total score. Share what the candidate built, the reasoning they explained, the tests they discussed and any unresolved integrity concerns.
| Area | What the panel needs |
|---|---|
| Coding | What worked, what remained incomplete and how the candidate handled errors |
| Problem solving | How the candidate investigated the issue and changed their approach |
| Technical discussion | Answers about design choices, edge cases and trade-offs |
| Integrity | Relevant flags and the result of the review |
| Next-round focus | Skills that need deeper discussion |
Fabric provides a recording, transcript and assessment for this handover. The panel can spend more time on deeper engineering questions when the first-round evidence already establishes the basics.
5. Improve Round One Using Later-Round Results
Compare the AI interview with what happens in rounds two and three. If candidates pass the first round but repeatedly struggle with debugging in the next, adjust the task or follow-up questions. If good candidates are being held back by unclear instructions, fix the setup.
Track two simple measures for each role:
- Later-round pass rate: candidates who pass the next round divided by candidates from the Fabric shortlist who attend it.
- Offer rate from the Fabric shortlist: candidates who receive an offer divided by candidates who passed the Fabric round.
Fabric reports that, in its hiring work, roughly one in four or five candidates who clear its round receives an offer. That is a useful reference point for discussing shortlist quality. Your own rate will vary with the role, hiring bar and later-round process.
Keep the candidate group and time period consistent when comparing results. An offer rate for a completed hiring batch tells you more than one calculated while half the shortlist is still interviewing. Track completion and total offers too, so improving a ratio does not hide lost candidates.
Choosing an AI Coding Interviewer
Look for practical code execution, a two-way technical conversation, a good candidate experience and a serious integrity review. Ask to see the report your engineers will receive and how the interview can be adjusted after later-round feedback.
Fabric is our recommendation when you want those parts in one first round, with OpenRound available for AI-assisted projects. For alternatives, read our AI interviewers for technical hiring comparison. If you already use a separate coding assessment, this guide explains when to combine it with an AI technical interview.
Build a Coding Round for Your Team
Bring a developer role and a practical problem. See how Fabric conducts the interview and prepares the panel report.
Frequently Asked Questions
Can an AI interviewer replace the first technical round?
Yes, when it covers the coding and discussion your team needs at that stage. Have engineers review the setup and results, then use later interviews to explore deeper technical judgment and team experience.
Can candidates ask the AI interviewer questions?
A two-way interviewer should let them clarify requirements and discuss an approach. Check this in a sample interview rather than choosing a format that only records answers.
Can we allow AI coding tools?
Yes. OpenRound supports practical work with AI tools permitted. You can also use Fabric for independent coding rounds. Tell candidates which rules apply before they start.
What should we measure after launch?
Track completion, later-round clearance and offers among candidates who pass the AI round. Use the later interviews to improve the task, follow-ups and scoring.