HackerRank is launching Chakra on Monday, an AI agent that conducts interviews, watches candidates work, and grades them on how they think, not just what answer they produce.
The tool has completed six months of beta testing and has already overseen more than 500,000 interviews. Companies including Snowflake, Snorkel, and Capgemini used it during this phase, alongside internal tests by HackerRank.
Automated voice agents have screened applicants for years. Job seekers have also adopted their own AI tools to prepare, sometimes without employer knowledge.
Chakra aims to measure harder-to-capture signals like critical thinking and judgment. It also assesses “AI fluency” — how a candidate frames a problem for an AI, evaluates its output, and guides it toward a solution.
“The previous modality of evaluation was evaluating the output,” Vivek Ravisankar, co-founder and CEO of HackerRank, said in an interview. “Now, because of AI, anybody can produce an artifact.” He argued the new question for employers is whether they can understand the thinking and judgment behind that output.
A Chakra interview resembles doing the job rather than taking a standard coding test. A candidate receives a task involving a real-world code repository and works through it in a canvas with an AI assistant. Chakra uses context to ask follow-up questions, such as why a candidate chose one approach over another, or how their solution would change if a new constraint were introduced.
Ravisankar told TechCrunch that Chakra changes the basic structure of the hiring process. Three separate rounds, comprising a recruiter screen, a take-home assessment, and a follow-up interview with an engineer, are now combined into a single Chakra interview.
Allowing candidates access to AI during an interview might seem to encourage cheating. HackerRank found the opposite. Suspicious-activity flags were 70% to 80% lower in Chakra interviews than in comparable traditional HackerRank assessments, though the rate varied depending on factors such as geography and seniority.
Ravisankar told TechCrunch that giving candidates access to AI reduces the incentive to secretly use outside tools that can feed them answers during an interview.
Launched at TechCrunch Disrupt in 2012, HackerRank built its business around coding challenges. The Y Combinator-backed startup now has more than 3,000 business customers, including Amazon, Nvidia, Clay, and Replit, and a community of over 30 million developers worldwide.
Chakra represents a shift away from the technical assessment business HackerRank spent years building. Its traditional product largely tested whether developers could solve coding problems correctly. Ravisankar believes AI has made that earlier model less useful for measuring engineering ability.
Ravisankar compared the transition internally to Apple moving from the iPod to the iPhone. He noted the old product still has value, but the new one represents where the startup believes 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.”
Giving AI a deeper role in evaluating candidates raises questions about how much of a hiring decision companies should delegate to an algorithm. Ravisankar told TechCrunch that Chakra is designed to score candidates rather than make the final hiring decision, which remains with humans.
AI can handle more structured parts of an interview by consistently applying criteria set by an employer. Human interviewers can then spend more time determining whether they 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. He argued an AI system can be instructed to follow the same rubric for every candidate rather than being influenced by factors such as a candidate’s background or education.
Applying the same criteria consistently does not necessarily make an AI system free of bias. Automated hiring tools can inherit or amplify biases from the data, models, and criteria used to build them, prompting regulators to scrutinize their use in employment decisions.
The use of AI in hiring is already drawing regulatory scrutiny. New York City requires employers using certain automated employment decision tools to subject them to an independent bias audit and provide notice to candidates before using them. Ravisankar acknowledged that hiring is a regulated area and said complying with such requirements is part of what HackerRank has had to build for.
What it means
For people applying for jobs, the change is a move away from isolated coding puzzles toward a simulation of actual work. Candidates will need to demonstrate how they use AI as a tool rather than just delivering a correct final result. The process is shorter, combining multiple steps into one session, and the environment is explicitly designed to allow AI assistance.
