HackerRank's AI Interviewer Chakra Goes Public After 500,000 Interviews

HackerRank says its AI interviewer Chakra has already conducted more than 500,000 interviews during a roughly six-month beta, and on Monday the company is making the product generally available to its customers.

Chakra is an AI agent that conducts interviews, watches candidates as they work, and evaluates not just their answers but how they arrived at them. Snowflake, Snorkel, and Capgemini were among the companies that tried the product during testing. HackerRank also tested it internally.

The stakes are significant. HackerRank, launched at TechCrunch Disrupt in 2012 and backed by Y Combinator, has more than 3,000 business customers — including Amazon, Nvidia, Clay, and Replit — and a community of over 30 million developers. With Chakra, the company is betting against the technical-assessment business it spent years building.

What does Chakra change about interviews?

AI has featured in hiring for some time. Companies use voice agents and other automated tools to screen candidates, while job seekers increasingly deploy their own AI tools during interviews, sometimes without employers knowing.

HackerRank's bet is that AI can change not only how interviews are conducted but what employers can measure. Beyond checking whether someone arrives at the right answer, Chakra is designed to assess harder-to-capture signals such as critical thinking and judgment, plus what HackerRank calls "AI fluency" — how well a candidate frames a problem for AI, judges its output, and steers it toward a solution.

"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 question for employers, he said, becomes whether they can understand the thinking and judgment that went into producing it.

How does a Chakra interview work?

A Chakra interview looks more like doing the job than taking a traditional coding test.

• The candidate receives a task involving a real-world code repository.
• They work through it in a canvas that includes an AI assistant.
• As they work, Chakra asks follow-up questions grounded in context — why they chose one approach over another, or how the solution would change under a new constraint.

Ravisankar said Chakra is restructuring the hiring process itself. What previously took three separate rounds — a recruiter screen, a take-home assessment, and a follow-up interview with an engineer — is now combined into a single Chakra interview.

Does giving candidates AI invite cheating?

HackerRank says it found the opposite. Ravisankar said suspicious-activity flags were 70% to 80% lower in Chakra interviews than in comparable traditional HackerRank assessments, though the rate varied by factors such as geography and seniority.

His explanation: giving candidates access to AI reduces the incentive to secretly use outside tools that can feed them answers during an interview.

Why is HackerRank betting against itself?

HackerRank built its business on coding challenges, helping companies assess and hire developers based on technical skills. Its traditional product largely tested whether developers could solve coding problems correctly. Ravisankar believes AI has made that model less useful for measuring engineering ability.

He compared the transition internally to Apple moving from the iPod to the iPhone — the old product still has value, but the new one reflects where the market is headed.

"Chakra is going to be the headline," he said. "It's going to be the way that we're going to move forward."

How much of hiring should be delegated to an algorithm?

Giving AI a deeper role in evaluating candidates raises questions about how much of a hiring decision companies should hand to an algorithm. Ravisankar said Chakra is designed to score candidates rather than make the final hiring decision, which remains with humans.

In his framing, AI handles the structured parts of an interview by consistently applying criteria set by the employer, while human interviewers spend more time determining whether they actually want to work with a candidate and answering questions about the company, team, and role.

"AI is way less biased than humans, if you tune it properly," Ravisankar said, arguing that an AI system can follow the same rubric for every candidate rather than being influenced by a candidate's background or education.

Applying the same criteria consistently does not guarantee freedom from bias. Automated hiring tools can inherit or amplify biases from the data, models, and criteria used to build them, which has drawn regulatory attention.

New York City, for example, requires employers using certain automated employment decision tools to subject them to an independent bias audit and notify candidates before use. Ravisankar acknowledged that hiring is a regulated area and said complying with such requirements is part of what HackerRank has had to build for.

With 500,000 interviews already run and a general release underway, Chakra now faces its real test: whether employers and regulators accept an AI agent as a standard gatekeeper for engineering jobs.