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Founded by Jason Madeano & Matt Stallone
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, they kept running into the same hiring issues.
As candidates, they saw how arbitrary and inconsistent technical interviews could be. As interviewers, they 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.
They built NextByte to fix this. Their goal is to make hiring decisions fairer, more efficient, and focused on what actually matters. They are helping companies identify the best engineers while giving candidates a better experience.
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. Their approach ensures that hiring decisions are based on practical ability rather than memorization.
Instead of testing candidates on obscure theoretical concepts, they focus on challenges that reflect real engineering work. Their Magic Import tool helps companies design assessments tailored to their job descriptions, ensuring that candidates are evaluated on the skills they will actually use. They 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. Their process is interactive, guided, and built to evaluate both technical skill and thought process.
By mirroring a real-world coding environment, they prevent candidates from simply rehearsing answers and instead uncover how they think and work through challenges.
A correct answer isn’t enough – they analyze the entire coding process to provide a deeper, more meaningful assessment of candidate ability including
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