HackerRank’s AI interviewer Chakra signals a new era in hiring

HackerRank is rolling out an AI interviewer called Chakra that can conduct coding interviews, observe how candidates solve problems, and evaluate the reasoning behind their answers. The move matters because it could reshape technical hiring from a series of human-led screening steps into a single AI-guided assessment.

After roughly six months in beta, Chakra is now generally available to HackerRank customers. The company says the system has already taken part in more than 500,000 interviews during testing and has been used by employers including Snowflake, Snorkel and Capgemini.

The launch is one of the clearest signs yet that artificial intelligence is moving from an interview aid into an active gatekeeper. For years, companies have used automation to screen resumes, administer coding tests and schedule interviews. At the same time, candidates have increasingly relied on AI tools to prep for interviews or answer questions in real time, often without employers knowing. Chakra pushes that dynamic further by putting AI on the employer side of the conversation.

What Chakra does and why HackerRank is betting on it

Chakra is designed to do more than ask a candidate a few questions and score the final result. It watches a developer work through a task in a live coding environment and uses that context to probe how the person is thinking, not just what they produced.

HackerRank says the product reflects a broader shift in hiring. As AI makes it easier for almost anyone to generate polished output, employers need new ways to judge whether someone can structure a problem, use tools well and make sound decisions under pressure.

Vivek Ravisankar, HackerRank’s co-founder and chief executive, argues that traditional technical assessment has become less reliable as a measure of true engineering ability. His view is that when AI can quickly produce an artifact, the real hiring signal increasingly lies in the reasoning behind it.

Ravisankar said the old model focused too heavily on evaluating the end result, while AI has made it easier for candidates to generate outputs that look impressive on their own. In his view, employers now need to understand the thinking process behind those outputs.

How Chakra changes the interview flow

HackerRank says Chakra makes the interview feel closer to the actual job than to a timed exam. Candidates are given a task based on a real code repository and complete it in a canvas that includes an AI assistant. As they work, Chakra can ask follow-up questions about trade-offs, architecture choices and how the solution would need to change if requirements shifted.

That structure is notable because it merges steps that often happen separately. According to Ravisankar, what may have once required a recruiter screen, a take-home assignment and a follow-up interview with an engineer can now be combined into one AI-led session.

In other words, Chakra is not merely another automated test. It is intended to function like an interviewer that can keep pace with a candidate’s work, adapt its questions and evaluate not only correctness but also adaptability, judgment and AI fluency.

What is AI fluency in hiring?

AI fluency, in HackerRank’s framing, is the ability to use AI effectively and critically during a task. That includes knowing how to describe a problem to an AI system, recognizing when its output is useful, spotting when it is wrong and steering it toward a better answer.

The concept may become increasingly important as more engineering work involves collaborating with AI tools rather than coding entirely from scratch. For employers, that means the ideal candidate may not be the person who can memorize the most syntax, but the one who can direct tools intelligently and still exercise judgment.

Why HackerRank says giving candidates AI can reduce cheating

One of the more surprising claims around Chakra is that giving candidates access to AI appears to reduce suspicious behavior rather than increase it. HackerRank says suspicious-activity flags were 70% to 80% lower in Chakra interviews than in comparable traditional assessments, although the rate varied based on geography and seniority.

The company’s explanation is straightforward: if candidates are allowed to use AI openly, they may be less tempted to secretly rely on outside tools that hide their activity. In that sense, Chakra is positioned as a controlled environment where AI use is visible rather than clandestine.

That argument cuts against a common fear in hiring, where any AI access during an interview is often assumed to make cheating easier. HackerRank’s position is that transparency can actually make evaluation cleaner, not messier, because employers know what assistance is being used and can design the interview around it.

How does Chakra fit into HackerRank’s business?

Chakra is a major strategic shift for HackerRank, not just a product update. The company built its reputation on coding challenges that helped employers judge developers by technical skill. That model worked when the key question was whether a candidate could solve a problem correctly under test conditions.

Now HackerRank is suggesting that this approach is no longer enough. As AI becomes embedded in software development, the company believes employers need tools that evaluate how people work with AI, how they reason through ambiguity and how they make decisions when the answer is not predetermined.

That is a risky bet because it partially undercuts the business HackerRank spent years building. But it is also a classic product transition story: a startup taking the logic of its old platform and recasting it for a market changed by new technology.

Ravisankar compared the company’s shift to Apple’s move from the iPod to the iPhone, saying the earlier product still had value but the newer one represented the future of the market.

HackerRank’s scale helps explain why it feels able to make that pivot. The Y Combinator-backed startup says it serves more than 3,000 business customers and has a community of over 30 million developers worldwide. Its customer list includes Amazon, Nvidia, Clay and Replit.

Key HackerRank facts at a glance

• Founded as a coding-assessment platform
• Launched at TechCrunch Disrupt in 2012
• Backed by Y Combinator
• Serves more than 3,000 business customers
• Claims a developer community of over 30 million people

What worries people about AI interviewing?

The biggest concern is whether companies should trust an algorithm to play such a central role in hiring. Even if a human makes the final decision, an AI system that scores or steers the interview can influence who advances and who does not.

That concern is not hypothetical. Hiring tools built on data and machine-learning models can reflect the biases of the systems and criteria used to train them. They can also amplify the blind spots of the organizations that deploy them. A system that looks consistent on the surface may still disadvantage certain groups if the underlying scoring rules are poorly designed.

Ravisankar says Chakra will score candidates rather than decide who gets hired. He argues that AI is best used for the structured portions of the process, while humans should handle the parts that require cultural judgment, relationship-building and candidate questions about the role and company.

Still, the tension is obvious: if AI helps decide who gets through the door, how much independence does the final human decision really have?

Why regulators are likely to pay attention

Hiring is already a regulated area, and automated employment tools are under more scrutiny than ever. That is especially true in jurisdictions that require audits, disclosures or other safeguards before companies can use algorithmic decision-making in employment.

New York City is one of the most cited examples. Employers using certain automated employment decision tools there must provide notice to candidates and subject the systems to an independent bias audit. That kind of framework matters because products like Chakra do not simply automate admin work; they influence how people are evaluated for jobs.

HackerRank says it has had to build compliance into the product from the start. The company’s challenge is to offer employers more efficiency without creating legal, ethical or reputational risk.

Ravisankar acknowledged that because hiring is regulated, compliance requirements are part of the product design, not an afterthought.

Regulatory issues employers must consider

1. Whether candidates must be told an automated tool is being used
2. Whether the tool needs an independent bias audit
3. How candidate data is stored and reviewed
4. Whether the system’s scoring criteria can be explained to applicants
5. How final hiring authority stays with human decision-makers

How Chakra could change technical hiring

If Chakra gains traction, it could change the way companies think about early-stage technical interviews. Instead of treating assessment as a separate hurdle, employers may begin to see it as a simulation of the actual work a developer would do on the job.

That shift could bring several advantages. It may reduce scheduling overhead, compress a longer interview pipeline and give employers a richer picture of how a candidate approaches open-ended problems. It could also make interviews more comparable, because the AI system can apply the same rubric repeatedly.

But there is a trade-off. The more hiring is optimized for consistency and scale, the greater the risk that subtle qualities are lost. Human interviewers still matter for evaluating communication style, curiosity, values and the less measurable aspects of fit.

In practice, the future hiring model may not be fully automated or fully human. Instead, it may be a hybrid system in which AI handles structured assessment while people reserve judgment for final decisions and relationship-building.

Why this launch matters beyond HackerRank

Chakra is important because it shows AI moving deeper into one of the most consequential business functions: deciding who gets hired. Many companies already use AI behind the scenes in recruiting. HackerRank is now packaging that logic into a visible product that can actually conduct an interview.

That makes the launch a signal to both employers and job seekers. Employers are being told that AI can help them assess not just what candidates know, but how they think. Candidates are being told that interviews may increasingly test how well they collaborate with AI tools in real time.

The long-term effect could be a redefinition of technical merit itself. In a world where AI can generate code, the most valuable skills may shift toward problem framing, tool use, debugging, judgment and the ability to navigate ambiguity. Chakra is built around that assumption.

Timeline: how HackerRank reached Chakra

What happens next?

The next test for Chakra is adoption. It remains to be seen whether employers trust AI enough to move core interview functions into a product like this, and whether candidates will accept being evaluated by an automated interviewer that asks follow-up questions and scores their performance.

For HackerRank, the answer will determine whether Chakra becomes a meaningful new growth engine or remains an ambitious sign of where the market could go. Either way, the company is making a clear statement: the age of AI in hiring is not just about assistance anymore. It is about evaluation.

And if that becomes the norm, the job interview may look far less like a conversation with a recruiter and far more like a real-time collaboration between a person and a machine — with both being judged at once.