HackerRank

Every engineering leader has felt the same disconnect at some point in the last two years: a candidate who looked strong on paper, cleared the technical screen, and then struggled in the first month because the job they were hired to do wasn’t the job the interview tested for. That gap isn’t a hiring mistake in the usual sense — it’s a sign that the technical bar itself hasn’t caught up to how engineering work actually happens now.

When an engineering leader asks how Chakra works, they’re usually really asking: can I trust the score. That’s a fair question to ask of any interview system, human or AI. The honest answer starts with the mechanics — what Chakra is doing, turn by turn, during an interview — because the trustworthiness of the signal follows directly from the design of the process that produces it. The core loop: listen, adapt, probe A Chakra interview isn’t a form with pre-written questions dropped in sequence.

Your engineers write code with AI. Your interviews need to test for that reality, not pretend it doesn’t exist. That’s the thinking behind HackerRank’s July release. It’s not a feature dump. It’s a shift in what “technical signal” means when every candidate has a copilot open in a second window. Why traditional coding interviews are losing signal Whiteboard problems and isolated coding challenges answer one question: can this person write an algorithm from memory.

Let candidates use AI tools in the interview. Banning them tests a skill nobody uses on the job anymore, and it tells you nothing about how the candidate will actually perform once they’re hired. The harder question isn’t whether to allow AI in the interview. It’s what to test once you do. Should candidates be allowed to use AI in a technical interview? Yes, with intention.

AI fluency means a candidate can direct an AI coding tool toward a real outcome, catch it when it’s wrong, and make the judgement calls the tool can’t make on its own. You test it by watching how someone works with AI under a real constraint. Most interview loops haven’t caught up to this yet. What is AI fluency in software engineering?

Yes. Leetcode-style interviews are dead, or close enough that treating them as your hiring bar is now a liability. It’s confusing, because algorithms still matter. The death came with AI. One prompt can solve the exact question you’re asking in seconds, which means the question stopped measuring what matters. This isn’t a hot take anymore. It’s the consensus in most engineering orgs, just not always said out loud in the hiring loop itself. Because the implication means change, and change is hard.

Connect an approved AI client to HackerRank to review assessment activity, prepare interview briefs, and create recruiting reports from the data your account can access.

The honest answer to “what’s the best AI interviewer” is: it depends entirely on what you’re hiring for. A tool built for high-volume, low-complexity screening and a tool built to evaluate a Staff Backend Engineer’s system design thinking are solving different problems, even if they both get marketed as “AI interviewers.” Here’s how to think about the category, and what separates a tool worth buying from one that just looks good in a sales demo.

Orchestrate is a 24-hour hackathon organised by HackerRank, where developers design, build, and ship an agent. Every submission is judged on four signals: the code, the performance of the agent build, the AI chat transcript, and a 30-minute voice interview in which participants defend their architecture to an AI judge. After looking through a range of Orchestrate submissions, this blog is meant to help developers understand what makes a build stronger and closer to real engineering work.

No. Chakra’s scoring is evidence-anchored: every score traces back to a specific, verbatim moment in the interview transcript. If there’s no relevant moment, the expectation isn’t scored at all. It’s marked Not Assessed, not guessed at. Three separate AI agents, each with one job: Interview Creator Agent works with the recruiter upfront to turn a job description into a structured interview plan: sections, sample questions, and explicit expectations.