HackerRank has made Chakra, an AI agent that conducts job interviews for developers, generally available to customers. The product completed about six months in beta and conducted more than 500,000 interviews during testing, with Snowflake, Snorkel and Capgemini among the trial users. The shift matters for business because it moves AI in hiring from screening answers to scoring judgment, critical thinking and work with AI assistants.
How Chakra runs a single combined interview
Chakra replaces a three-stage sequence described by co-founder and CEO Vivek Ravisankar: a recruiter screen, a take-home assessment and a follow-up interview with an engineer. Instead, a candidate receives a task based on a real-world code repository and works inside a canvas that includes an AI assistant. While the person codes, the agent watches the process and asks follow-up questions about choices, trade-offs and changes under new constraints. HackerRank also tested the system internally before the commercial launch.
The evaluation logic focuses on process rather than the final artifact alone. Ravisankar said the old approach graded output, but now any person can produce code with AI, so employers need to understand reasoning behind it. Chakra is designed to measure signals such as problem framing for AI, assessment of generated output and steering toward a solution. The company positions this as AI fluency alongside technical correctness. Scoring stays with the system, while the final hiring decision remains with people.
The launch fits a hiring market where both sides already use automation. Employers have deployed voice agents and screening tools to cut recruiting costs, while candidates quietly use AI helpers to prepare or answer during interviews. HackerRank itself was launched at TechCrunch Disrupt in 2012, built a business on coding challenges, and now reports more than 3,000 business customers including Amazon, Nvidia, Clay and Replit, plus a community of over 30 million developers. Chakra therefore competes with the assessment model that made the Y Combinator-backed startup known.
What this means for hiring with AI
For companies that hire engineers, the practical effect is consolidation of vendor tooling and interview time. One AI-led session can cover screening, practical work and probing questions, which reduces scheduling with recruiters and engineers and creates a uniform rubric across candidates. Smaller firms gain access to structured technical interviews without a large hiring team, while large employers can standardize early stages across locations and roles. The value shows up in roles where output alone no longer separates candidates who use coding assistants.
The limits concern bias, oversight and compliance rather than cheating statistics. HackerRank reported suspicious-activity flags 70% to 80% lower in Chakra interviews than in comparable traditional assessments, with variation by geography and seniority, linking this to legal access to AI during the task. Still, consistent scoring does not equal neutrality, since models and criteria can carry inherited bias and face regulatory review. Buyers should ask how rubrics are set, how scores are documented, what audit exists such as the bias audit required in New York City, and how candidate notice is handled.
The marker to watch is whether enterprise customers move Chakra from pilot to default first-round interviews through 2026. Ravisankar compared the shift to Apple moving from the iPod to the iPhone, calling Chakra the headline product. If Snowflake-scale employers keep it in production and publish hiring-quality data, process-based AI interviews will become a standard procurement requirement rather than an experiment.
