Screen candidates for ability and output, not rote memorization
TL;DR: AI is changing how engineers work - it's time hiring caught up. Built by MIT engineers, NextByte tests for real-world skills, conceptual knowledge, and AI tool usage, not memorized algorithms.
Today's best engineers aren’t grinding Leetcode - they're vibe coding. AI copilots and codegen tools are making developers more productive than ever, yet tech hiring is stuck in the past.
Current coding screens reward those who memorize algorithms, not those who can actually build and problem solve. Worse, LLMs can ace many Leetcode problems better than humans, so what are these screens really testing?
NextByte is an AI-first interview platform that helps companies screen for the skills that actually matter. Our approach ensures that hiring decisions are based on practical ability rather than memorization.
Instead of testing candidates on obscure theoretical concepts, we focus on challenges that reflect real engineering work. Our Magic Import tool helps companies design assessments tailored to their job descriptions, ensuring that candidates are evaluated on the skills they will actually use. We eliminate unnecessary algorithmic puzzles and instead measure problem-solving ability in a way that aligns with on-the-job performance.
Technical interviews should reflect how engineers actually work. Our process is interactive, guided, and built to evaluate both technical skill and thought process.
By mirroring a real-world coding environment, we prevent candidates from simply rehearsing answers and instead uncover how they think and work through challenges.
A correct answer isn’t enough – we analyze the entire coding process to provide a deeper, more meaningful assessment of candidate ability including
We’re MIT grads, engineers, and longtime friends who have experienced the flaws of technical hiring firsthand.
Matt led post-training efforts for Enterprise LLMs at IBM Research delivering open weight models, including the Granite family which achieved state-of-the-art benchmarks that rivaled Meta's LLaMA 3. Jason worked on Home Relevance at Pinterest, leading the development of new recommendation systems that scaled non-pin content from zero to 100M daily impressions in months.
Despite working on different problems at different companies, we kept running into the same hiring issues.
As candidates, we saw how arbitrary and inconsistent technical interviews could be. As interviewers, we saw colleagues struggle to find time to properly evaluate applicants while juggling their own workloads. Some interviews were so broken that proctors would literally fall asleep on Zoom calls.
We built NextByte to fix this. Our goal is to make hiring decisions fairer, more efficient, and focused on what actually matters. We're helping companies identify the best engineers while giving candidates a better experience.