AutoIterative Job Interviews
Using AutoIterative Job Interviews in the hiring loop
AutoIterative Job Interviews are the best way to hire great software engineers.
To achieve that, we made the candidate do the same thing they do at work. Their task is to build a product according to a real-life problem specification. The AutoIterative platform provides them with a dedicated production environment. The continuous delivery system deploys the candidate's code on every code push. The platform checks the solution with real-life tests and gives constant feedback. There is no artificial time limit or judgment of someone watching over the shoulder. The candidate can iterate until they are confident in their solution. They are free to pick the tools they consider the best for the task.
AutoIterative Job Interviews: are they unbiased?
Yes.
It cuts out both types of biases: the ones coming from humans and from tasks.
To eliminate biases that come from humans, we excluded humans from the process. The platform is fully automated and self-service. It allows the candidate to solve the challenge at their own pace and time. The platform is completely anonymous by design. It does not store names, origins, genders, or any other details of the candidates. It focuses only on whether the candidate can deliver the code working in the production.
To eliminate biases that come from tasks themselves, we don't use synthetic problems. The platform doesn't check if the candidate used the expected data structure. It couldn't care less about algorithm selection or code style. Instead, it deploys their solution to a dedicated production environment and runs it. Real-life data tests will show whether the code is correct, scalable, and performant. If not, the candidate will receive feedback and continue iterating on their solution.
The unbiased focus of the platform is to assess whether the candidate can build a product that works.
AutoIterative Job Interviews: are they low-stress for your candidates?
Yes.
We designed them to exclude the common stress factors to allow the candidates to focus on the job.
AutoIterative Job Interviews mimic real remote work. The candidates are free to do them when and how they like. They can pick their own pace or step back for a few days to sleep on the problem. They can start from scratch if they want to, as there are no artificial deadlines. They can be humans and make mistakes without the burden of someone judging their every move.
AutoIterative Job Interviews: are they real work?
Yes.
Both the setting of the interview and the task presented to the candidate mimic real life.
The goal of the AutoIterative Job Interview is to code a solution to a real-life business problem. The platform gives the candidate a problem definition and a familiar work environment. It consists of a code repository and a continuous delivery pipeline to production. The tasks are language-agnostic, allowing the candidate to pick the best tool for the job. The platform gives them immediate feedback after each deployment. In addition to that, they can use custom metrics to profile and debug their code in production.
AutoIterative Job Interviews: are they a good predictor of future performance?
Yes.
The only focus is on assessing whether the candidate can build a working product.
AutoIterative Job Interviews explicitly ignore all proxy metrics during the skill assessment. The platform does not check for algorithmic knowledge or data structure choice. Those are not reliable indicators of how well the code solves the business problem. Running the solution in the production according to the specification is. If you hire software developers to work on your product, let them show that they can build a working product.
AutoIterative Job Interviews: additional benefits for your hiring loop
AutoIterative Job Interviews have overwhelmingly positive feedback from the candidates. They love fiddling with the platform, showing their skills, and learning new things. That enjoyment passes to the company, as one of the candidates put it:
All in all, I really enjoyed using the system, and I think it gave me a perspective into the company I am applying too as a company that actually cares about the quality of the engineering instead of just if you can pass a random question in a timed video conference.
AutoIterative Job Interviews give everyone the same chance. They allow you to stop wasting time pre-filtering candidates with artificial criteria. It is surprising how much talent one can find hidden behind unexpected backgrounds. And don't worry about the candidates who do not engage with the challenge. With AutoIterative, you filter them for free.
AutoIterative Job Interviews allow you to design fully blind hiring loops. First, the candidate demonstrates their abilities to build a working product. After that, your engineers might want to examine their code for additional information. The platform explicitly does not store any identifying information about the candidate. The code review will be free from unconscious biases due to not knowing who the candidate is.
AutoIterative Job Interviews provide rare insights into your candidates' behavioral traits. While solving the challenge, they continuously interact with the platform. That allows us to amass valuable data about their working and thinking processes. On completion, we provide you with a detailed report of their performance. It includes the potential questions you can ask them during a face-to-face meeting. The questions are based not on the technicalities of their code but the quality of their product.
AutoIterative Job Interviews to the rescue!
All those benefits are just a few clicks away. Register a demo account, invite your engineers to test it, and you'll get a perfect understanding of how AutoIterative Job Interviews could supercharge your hiring loop!
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