HackerRank is pushing AI deeper into the hiring process with Chakra, an AI agent that conducts developer interviews, watches candidates work, and scores more than the final answer. The product is now generally available to customers after around six months in beta.
The move reflects a larger shift in technical hiring: as AI tools make it easier for candidates to produce code, employers are looking for ways to understand the reasoning, judgment, and process behind that output.
What Chakra Does Differently
Chakra is not built as a standard coding test with a single answer at the end. In a Chakra interview, a candidate works on a task involving a real-world code repository inside a canvas that includes an AI assistant.
As the candidate works, Chakra can use the context of the session to ask follow-up questions. Those questions may focus on why the candidate chose one approach over another, or how the solution might change if a new constraint were introduced.
That changes the interview from a narrow test of completion into a more detailed look at how someone thinks through a problem. HackerRank wants employers to measure signals such as critical thinking, judgment, and what it calls AI fluency.
In this context, AI fluency means how well a candidate frames a problem for AI, evaluates the AI's output, and guides the tool toward a useful solution. The idea is that modern engineering work may depend not only on writing code directly, but also on knowing how to collaborate with AI systems effectively.
Why HackerRank Is Reworking Its Own Model
HackerRank built its business around coding challenges. The Y Combinator-backed startup launched at TechCrunch Disrupt in 2012 and became known for helping companies assess and hire developers based on technical skills.
The company 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 significant change for a company whose earlier products largely focused on whether developers could solve coding problems correctly.
HackerRank co-founder and CEO Vivek Ravisankar told TechCrunch that the old evaluation model is less useful in an AI-assisted environment. As he put it,
"The previous modality of evaluation was evaluating the output,"and added,
"Now, because of AI, anybody can produce an artifact."
That framing explains why HackerRank is emphasizing process. If AI can help many candidates generate a working artifact, employers may need to ask different questions: Did the candidate understand the problem? Did they choose an appropriate path? Did they recognize limitations in the AI's response? Did they adapt when requirements changed?
A Single Interview Instead Of Three Steps
Ravisankar told TechCrunch that Chakra can also change the structure of the hiring funnel. What previously involved three separate rounds, comprising a recruiter screen, take-home assessment, and follow-up interview with an engineer, is now combined into a single Chakra interview, he said.
For employers, the appeal is clear: fewer disconnected steps, more structured evaluation, and a closer simulation of real work. For candidates, the interview may feel less like a closed-book exam and more like a task performed with the kind of AI assistance that is increasingly present in software work.
During testing, Chakra conducted more than 500,000 interviews. Companies including Snowflake, Snorkel, and Capgemini tried it, and HackerRank also tested the product internally.
One surprising result involved suspected cheating. Giving candidates access to AI might appear to create more room for misuse. HackerRank says it found the opposite: suspicious-activity flags were 70% to 80% lower in Chakra interviews than in comparable traditional HackerRank assessments, although the rate varied depending on factors such as geography and seniority.
Ravisankar told TechCrunch that when candidates are allowed to use AI during the interview, they have less incentive to secretly rely on outside tools that can feed them answers.
The Human Role Still Matters
Chakra also raises a more sensitive question: how much of a hiring decision should be handed to software? HackerRank says Chakra is designed to score candidates, not make the final hiring decision. According to Ravisankar, that decision remains with humans.
The company sees AI as useful for the more structured parts of an interview. An employer can define criteria, and the system can apply those criteria consistently. Human interviewers, in this model, can spend more time deciding whether they 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 you tune it properly,"saying an AI system can be instructed to follow the same rubric for every candidate instead of being influenced by background or education.
But applying the same criteria consistently does not automatically remove bias. Automated hiring tools can inherit or amplify bias from the data, models, and criteria used to build them. That risk is one reason regulators are already scrutinizing AI in employment decisions.
New York City, for instance, 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 compliance with such requirements is part of what HackerRank has had to build for.
What This Signals For Future Interviews
Chakra shows how job interviews may evolve as AI becomes a normal part of work. Instead of asking whether a candidate can avoid AI, employers may increasingly ask whether the candidate can use it well.
That shift could make interviews more realistic, especially for technical roles where AI-assisted work is already becoming part of the workflow. It also creates new responsibilities for companies using automated systems: they must decide what the AI should measure, how scores should be interpreted, and where human judgment must remain central.
For HackerRank, Chakra is more than a product update. Ravisankar compared the transition internally to Apple moving from the iPod to the iPhone, saying the old product still has value but the new one represents where the startup believes the market is headed. As he told TechCrunch,
"Chakra is going to be the headline,"and
"It's going to be the way that we're going to move forward."