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Let’s be real for a second: hiring engineers is hard. Like, really hard. You’ve got resumes, coding quizzes, and endless interviews, and at the end of it all, you’re still not sure if the person in front of you can actually do the job.
And here’s the kicker—most companies are still using the same “coding quizzes” from ten years ago to evaluate engineers. Yep, ten years ago. Like, before AI, before DevOps, and when system design was still that thing you read about in textbooks.
Kodiva.ai decided to do something about that. We’ve built a platform that benchmarks engineers not just on their ability to churn out code, but on the real-world skills that matter. Stuff like code review, system design, and debugging.
But enough of that fluffy talk. You’re here to understand how Kodiva.ai does benchmarking, without your brain melting in the process. So let’s get into it.
Step 1: Defining Your Rockstar Engineer
Every engineering team has that one person. You know, the rockstar who can juggle 10 tasks, review a PR with one hand, and debug production issues faster than you can say “deploy.”
Kodiva.ai starts by helping you define that person. What are the key skills that make them a standout? Is it their problem-solving? Their knowledge of distributed systems? Or are they just a wizard at debugging that gnarly code no one else dares to touch?
We break down these competencies into specific skills (e.g., “system design,” “code quality,” “problem-solving”) and set up proficiency levels for each—Beginner, Intermediate, and Advanced. This gives us a clear roadmap of what your ideal candidate should look like.
Step 2: The Assessment – Where the Magic Happens
Here’s where it gets interesting. Once you’ve defined your rockstar, we build an assessment that mimics the real-world tasks they handle every day. No more multiple-choice questions or “write a function that reverses a string” nonsense.
Instead, Kodiva.ai tests candidates with scenarios like:
• Code Reviews: Can they improve and refactor a messy codebase?
• System Design: Can they sketch out a scalable architecture for a system that won’t blow up under real-world traffic?
• Debugging: How quickly and efficiently can they hunt down bugs and fix them?
The idea is simple: if you want to hire someone to do real engineering work, then test them on real engineering tasks.
Step 3: Running the Benchmark on Your Best People
Now, this is where we bring in some serious technical chops. To create a benchmark, we run the same assessment on your top-performing engineers. Why? Because they are the living, breathing version of what you want in your new hires.
Here’s the deal—your engineers take the test, and Kodiva.ai evaluates them on all the key metrics: speed, accuracy, decision-making, and how well they tackle the complexity of the task. We collect this data, process it, and—voilà—you’ve got a benchmark.
But this isn’t just any old benchmark. Kodiva’s secret sauce is our use of AI-driven insights combined with human engineer feedback. We calculate things like average scores and percentile ranks across various skills, giving you a clear, data-driven baseline to compare candidates.
Step 4: Mathematically Solving the Benchmark (Without the Headache)
Now, let’s talk numbers. Kodiva.ai uses a mix of statistical analysis and machine learning to define the benchmark thresholds. Here’s how it works:
1. Data Collection: We gather performance data from your ideal engineers across tasks like code review, system design, and debugging.
2. Mean and Standard Deviation: We calculate the mean score (average) and standard deviation to understand how much variance there is in their performance. This helps us define what “average,” “good,” and “excellent” performance looks like.
3. Percentiles: We map out the scores into percentile ranks. For example, if your top engineer scores in the 90th percentile, we know that a candidate will need to score that high to match or exceed their level.
4. Thresholds: Finally, we set the benchmark thresholds. If you want candidates who are on bar with your top 10%, the benchmark will be set accordingly. Kodiva.ai provides a detailed breakdown for each skill so you can see exactly where a candidate stacks up.
And no, this doesn’t require a PhD in math. Kodiva.ai’s platform does all the heavy lifting for you.
Step 5: The Moment of Truth – Evaluating New Candidates
So, you’ve got your benchmark. Now it’s time to see how new candidates measure up.
Every candidate who takes the Kodiva.ai assessment is scored against your ideal engineer benchmark. And because we’re using real-world tasks, you get a true sense of their abilities. No more “he aced the coding quiz, but can’t debug worth a damn” surprises.
The platform gives you a detailed report with:
• Skill Proficiency: Where the candidate excels and where they fall short.
• Gap Analysis: How they compare to your current engineers.
• Overall Score: Whether they meet or exceed your benchmark thresholds.
Basically, it’s like having a personal AI assistant that tells you whether a candidate is worth your time.
Why Kodiva.ai’s Benchmarking Changes the Game
Let’s be honest—traditional coding tests don’t cut it anymore. Engineering is about more than just typing fast or solving abstract algorithmic problems. It’s about how you think, collaborate, and solve real-world problems.
With Kodiva.ai, you’re not just testing candidates. You’re getting a complete picture of their abilities, benchmarked against your best engineers. And the best part? You’re saving 36+ hours of engineering time per hire by cutting out the fluff and getting straight to what matters.
No more wasted interviews. No more guesswork. Just data-driven hiring that makes sense.
Conclusion: Say Goodbye to Hiring Guesswork
The future of hiring isn’t just about who can code. It’s about finding engineers who can think, solve problems, and contribute to your team right from day one. Kodiva.ai does exactly that by helping you benchmark candidates against your top performers, ensuring you only hire the best.
Ready to revolutionize your hiring process? Start benchmarking smarter with Kodiva.ai.
