When artificial intelligence shifts from assisting job applicants to assessing them, the hiring landscape could change dramatically. HackerRank, a company whose platform helps businesses evaluate and recruit developers, is providing a preview of that possible future through Chakra—an AI agent that performs interviews, watches candidates as they work, and assesses not only their final answers but the process they used to reach them. After roughly six months in beta, HackerRank is releasing Chakra to its customers broadly on Monday. According to the startup, the AI interviewer has already carried out over 500,000 interviews during its testing phase, with organizations such as Snowflake, Snorkel, and Capgemini among those that experimented with it, while HackerRank also ran internal trials of the product.

AI has already become a common fixture in job interviews for some time, as companies deploy voice agents and other automated systems to filter applicants and streamline hiring. At the same time, job seekers have increasingly acquired their own AI tools to help them get through interviews, occasionally without their prospective employers being aware. With Chakra, HackerRank is wagering that AI can transform not just how interviews happen, but also what employers are able to measure. Beyond simply checking whether a candidate reaches the correct answer, the startup aims to evaluate more elusive qualities like critical thinking and judgment, along with what it terms "AI fluency"—a candidate's ability to frame a problem for AI, assess its output, and guide 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." For employers, he explained, the real question becomes whether they can grasp the thinking and judgment that went into creating it.

In practice, a Chakra interview is built to resemble actually doing the job rather than completing a conventional coding test. A candidate receives a task tied to a real-world code repository and works through it on a canvas that includes an AI assistant. While the candidate works, Chakra can draw on the context of their actions to pose follow-up questions—for instance, why they selected one approach over another, or how their solution would shift if a new constraint were added. What used to require three separate stages—a recruiter screen, a take-home assessment, and a follow-up interview with an engineer—is now consolidated into a single Chakra interview, he said.

Giving candidates access to AI during an interview might appear to make cheating easier. But HackerRank reports the opposite. Suspicious-activity flags, Ravisankar said, were 70% to 80% lower in Chakra interviews compared to similar traditional HackerRank assessments, though the rate differed based on factors like geography and seniority.

The Y Combinator-backed startup now counts more than 3,000 business customers, among them Amazon, Nvidia, Clay, and Replit, along with a community of over 30 million developers globally. Chakra amounts to a bet against the type of technical assessment business HackerRank spent years developing. Its traditional offering mostly tested whether developers could solve coding problems accurately. Even so, Ravisankar believes AI has rendered HackerRank's earlier model less effective for measuring engineering ability. He compared the shift internally to Apple transitioning from the iPod to the iPhone—the old product still holds value, but the new one reflects where the startup believes the market is heading. "Chakra is going to be the headline," he said. "It's going to be the way that we're going to move forward."

Yet granting AI a larger role in evaluating candidates introduces a separate set of concerns, especially regarding how much of a hiring decision companies should hand over to an algorithm. AI, Ravisankar said, can manage the more structured portions of an interview by uniformly applying criteria established by an employer, freeing human interviewers to focus on determining whether they genuinely want to work with a candidate and to answer questions about the company, team, and role.

"AI is way less biased than humans, if you tune it properly," Ravisankar said, contending that an AI system can be directed to follow the same rubric for every candidate instead of being swayed by factors like a candidate's background or education. Applying identical criteria consistently, however, does not automatically make an AI system free of bias. Automated hiring tools can inherit or magnify biases from the data, models, and criteria used to construct them, which has led regulators to examine their use in employment decisions.

The use of AI in hiring is already attracting regulatory attention. New York City, for example, requires employers using certain automated employment decision tools to undergo an independent bias audit and to notify candidates before using them. Ravisankar acknowledged that hiring is a regulated area and said meeting such requirements is part of what HackerRank has had to build for