Now an AI Interviews You: What HackerRank's Chakra Evaluates and How to Prepare as a Developer
On Monday, October 5, HackerRank, the technical assessment platform many companies use to hire developers, opened Chakra to all its customers: an AI interviewer that runs the technical interview on its own, according to TechCrunch and Runtime Wire. It arrives after roughly six months in beta, during which it conducted more than 500,000 interviews, with Snowflake, Snorkel and Capgemini among its first customers.
The striking part is not that an AI asks the questions, but what it evaluates: in this interview you can use an AI assistant, and part of your score depends on how you use it. If you apply for remote jobs at companies that hire through platforms like this, it pays to understand the format before you face it.
How a Chakra Interview Works
According to the official product page and TechCrunch's coverage:
- A real problem, not a puzzle. You get a task on a code repository, such as debugging an application or fixing a bug, in an environment similar to a development editor.
- AI included. The environment comes with an AI assistant you can use while you work.
- Follow-up questions. Chakra watches what you do and asks about your decisions: why you chose one approach or what you would change given a new constraint.
- A single session. HackerRank says it replaces the recruiter screen, the take-home test and the engineer interview. Its website mentions 30-minute interviews.
- Monitoring. It flags for review the use of unauthorized apps, another person on camera or help from another device.
- A person decides. Chakra delivers a report with scores per competency and the evidence behind each one; the hiring decision stays with the company.
What It Measures: Judgment and "AI Fluency"
HackerRank CEO Vivek Ravisankar put it this way to TechCrunch: evaluation used to focus on the output, and now, thanks to AI, anyone can produce one. That is why Chakra scores critical thinking, judgment and what the company calls AI fluency, in addition to whether the solution works.
On its blog, HackerRank defines it as the ability to direct an AI tool toward a real outcome, catch it when it is wrong and make the judgment calls the tool cannot make on its own. The signals it looks for: prompts with enough context, critical review of what the AI returns, knowing how to take back control when the approach is wrong, and explaining what you are doing. The red flag, in its words: silence followed by a paste, with no narration and no verification.
According to HackerRank, as cited by TechCrunch, suspicious-activity flags were 70% to 80% lower than on its traditional assessments; the company attributes this to the fact that when AI is allowed, there is less reason to seek help in secret.
How to Prepare
- Practice with AI, out loud. Solve exercises with an assistant and narrate your plan: what you will ask it and what you will verify yourself.
- Write prompts with context: file, function, constraints and what it must not touch.
- Never accept code without testing it. Run tests, check edge cases (null values, empty lists, network errors) and say so as you go.
- Train on other people's code. Read and debug repositories you did not write; that is closest to the real task.
- Prepare your whys. For each decision, have a reason and an alternative you ruled out.
- Respect the environment. Use only the tools provided, with no other apps or devices: that is exactly what the system flags.
If You Are the One Hiring
If your developers will work with AI, it makes sense to evaluate them working with AI, and you do not need a platform for that: a short task on real code, with an assistant allowed, and a conversation about the decisions is enough. If you use automated tools, keep in mind what TechCrunch points out: AI can inherit biases from its data and criteria. Review the reports and leave the final decision to a person.
How We Approach It at SimCodec
At SimCodec we use AI assistants every day in software development and in our artificial intelligence projects, with a simple rule: AI proposes, and a person reviews, tests and is accountable for the code. With that same approach we help companies in Quito and across Ecuador bring AI into their teams and processes.
If you want to define how your team uses AI to write code, or you need software built with this approach, write to us or call our AI assistant Cyntia at +593 99 726 6838.
