HackerRank releases Chakra to assess developers working with AI
Illustration, not documentary evidence of the event.
HackerRank is making Chakra, its AI interviewer, generally available to customers after roughly six months in beta, according to techcrunch.com. The company says the agent conducted more than 500,000 interviews during testing, with Snowflake, Snorkel, and Capgemini among the companies that tried it.
Candidates work on a task involving a real-world code repository in a workspace with an AI assistant. Chakra observes their work and asks contextual follow-up questions about their choices or changing constraints. HackerRank wants to evaluate both the result and the candidate’s judgment, including how they direct AI and assess its output. CEO Vivek Ravisankar says Chakra scores candidates while humans retain the final hiring decision.
For engineering hiring teams, the immediate decision is whether this format measures the work they actually need someone to do. If a role involves using AI to modify an existing codebase, the format appears more closely aligned with that task than a test focused solely on producing a correct answer. Before adopting it, define what a strong performance looks like: identifying a flawed AI suggestion, explaining a design tradeoff, or adapting a solution when requirements change. Ask to review how those behaviors translate into scores, and have engineers assess sample work against the same criteria.
Ravisankar says Chakra combines a recruiter screen, take-home assessment, and engineer follow-up into one interview. Treat that as a workflow proposal to validate. Map each existing round to the information it supplies, then check whether a Chakra session supplies enough evidence to replace it. Preserve time for candidates to question a human about the team and role. Keeping a person responsible for the final decision is more useful when that person can examine the work behind the score.
HackerRank also reports 70% to 80% fewer suspicious-activity flags than in comparable traditional assessments, with variation by geography and seniority. That is a company-reported change in flags, not proof of better hiring decisions. Before using it to justify a switch, ask what triggers a flag in each format and how the comparison groups were selected. Judge the proposed replacement on the quality of evidence it gives hiring managers, rather than treating fewer flags as a substitute for that evidence.