HackerRank’s AI Interviewer Gives a Look at the Future of Job Interviews

Meta description: HackerRank launches Chakra, an AI interviewer that ran 500,000 beta interviews and cuts suspicious flags by 70% to 80% while reshaping hiring.

Tags: HackerRank, Chakra, AI interviews, developer hiring, automated assessment

Featured image: Abstract technology scene with interview panels, code repositories and evaluation signals, no real people, no company logos, no text.

HackerRank Chakra is an AI agent and interviewer built by HackerRank, the developer hiring platform used by companies to assess and hire developers. It conducts interviews, observes candidates as they work and evaluates not only answers but also how they got there. The product moved from beta to general availability to customers on Monday after around six months in beta. HackerRank says Chakra has already conducted more than 500,000 interviews during testing, with companies including Snowflake, Snorkel and Capgemini trying it, while HackerRank also tested the product internally. The launch marks a shift from AI tools that help candidates prepare to AI systems that score how they work.

Background: HackerRank’s Hiring Model Before Chakra

HackerRank launched at TechCrunch Disrupt in 2012 and built a business around coding challenges used to assess and hire developers based on technical skills. The Y Combinator-backed startup now serves more than 3,000 business customers, including Amazon, Nvidia, Clay and Replit, and has a community of over 30 million developers worldwide.

AI has been a staple in job interviews for some time. Companies used voice agents and other automated tools to screen candidates and make the hiring process more efficient, while job seekers increasingly gained their own AI tools to navigate interviews, sometimes without employers knowing. HackerRank’s traditional model asked whether a developer could solve coding problems correctly.

Vivek Ravisankar, HackerRank co-founder and CEO, told TechCrunch that AI has changed that baseline. The previous mode of evaluation focused on output. Because AI can let anyone produce an artifact, employers now need to understand the thinking and judgment behind it.

Development: From Beta Testing to a New Interview Format

Chakra is designed to look more like doing the job than taking a traditional coding test. A candidate receives a task involving a real-world code repository and works through it in a canvas that includes an AI assistant. As the candidate works, Chakra can use the context of what they are doing to ask follow-up questions, such as why one approach was chosen over another or how the solution would change if a new constraint were introduced. HackerRank credits the image and says Chakra shows a detailed report to the hiring manager after the interview.

HackerRank says Chakra changes not only how interviews are conducted, but also what employers can measure. The company wants to assess harder-to-capture signals beyond whether someone arrives at the right answer: critical thinking, judgment and AI fluency. HackerRank defines AI fluency as how well a candidate frames a problem for an AI system, judges its output and steers it toward a solution.

Ravisankar told TechCrunch that Chakra is also changing the basic structure of the hiring process. A process that previously involved three separate rounds, comprising a recruiter screen, a take-home assessment and a follow-up interview with an engineer, can now be combined into a single Chakra interview.

Giving candidates access to AI during an interview might seem to make cheating easier. 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 depending on factors such as geography and seniority. Giving candidates access to AI reduces the incentive to secretly use outside tools that can feed them answers during an interview.

Latest: A Bigger Bet and a Regulated Market

Chakra represents a bet against the kind of 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: the old product still has value, but the new one represents where the startup believes the market is headed. He said Chakra is going to be the headline and the way HackerRank moves 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, while human interviewers can spend more time determining whether they actually want to work with a candidate and answering questions about the company, team and role.

Ravisankar argued that AI is way less biased than humans, if it is tuned properly, because it 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, however, 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.

The current stage is a general availability launch backed by beta volume, customer pilots and a new evaluation framework. The next phase will show whether employers accept a single AI-assisted interview as a replacement for multiple rounds, and whether regulators treat more detailed AI scoring as a deeper step into automated employment decision tools.