HackerRank's Chakra AI Interviewer Goes Live After 500,000-Test Beta

HackerRank will make its Chakra AI interviewer generally available on Monday, after the agent ran more than 500,000 interviews during a six-month beta with employers including Snowflake, Snorkel, and Capgemini.

The platform, used by more than 3,000 companies to assess and hire developers, replaces conventional coding tests with a session that observes candidates solving real problems in a live code repository.

What does Chakra actually do?

A candidate opens a task built around an actual codebase and works through it inside a canvas that includes an AI assistant. Chakra watches the work and asks follow-up questions in context — why one approach was chosen, or how the solution would shift under a new constraint.

"The previous modality of evaluation was evaluating the output," HackerRank co-founder and CEO Vivek Ravisankar said in an interview. "Now, because of AI, anybody can produce an artifact."

The implication, Ravisankar argued, is that employers now have to score the thinking and judgment behind the answer, not the answer itself. HackerRank calls that "AI fluency" — how a candidate frames a problem, weighs model output, and steers it toward a solution.

What changes in the hiring process?

Three rounds collapse into one. The recruiter screen, take-home assessment, and engineer follow-up combine into a single Chakra session, Ravisankar told TechCrunch.

Beta customers included Snowflake, Snorkel, and Capgemini. HackerRank also tested the product internally. The broader customer base spans Amazon, Nvidia, Clay, and Replit. A community of more than 30 million developers sits on the platform.

Why the cheating flag dropped

Allowing AI inside the interview sounds like an invitation to cheat. HackerRank's data showed the opposite. Suspicious-activity flags ran 70% to 80% lower in Chakra sessions than in comparable traditional HackerRank assessments, Ravisankar said. Rates varied by geography and seniority.

Ravisankar's read: giving candidates a sanctioned AI tool removes the incentive to smuggle in outside software that feeds answers. The cheat vector that mattered most was already on the desk.

Who keeps the hiring decision?

AI scores the candidate. Humans make the call. Chakra applies the rubric an employer sets, while interviewers reserve their airtime for culture fit and candidate questions.

The design responds to a regulator's complaint about letting algorithms pick people. New York City, for instance, requires automated employment decision tools to pass an independent bias audit and to notify candidates before use. Ravisankar called compliance with such rules part of the build.

Can a tuned model really be less biased?

Ravisankar's claim is direct: "AI is way less biased than humans, if you tune it properly." An AI rubric, he said, applies the same criteria to every candidate rather than tilting toward background or education.

Researchers and regulators counter that automated tools can inherit or amplify the bias baked into training data, model design, and scoring criteria. The dispute will run through whatever Chakra customers do next.

What it means for HackerRank's own business

Chakra is a bet against the coding-challenge product that built HackerRank since its 2012 launch at TechCrunch Disrupt. The Y Combinator-backed startup's old scorecard measured whether developers solved problems correctly. Ravisankar believes that scorecard now measures less.

He compared the internal shift to Apple's iPod-to-iPhone transition: the legacy product still ships, but the new one leads. "Chakra is going to be the headline," he said. "It's going to be the way that we're going to move forward."

Whether employers ship that headline at scale — or pull back when audits and rulings land — will decide where Chakra sits in 2026.