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Dev tools · February 19, 2024

CA

CodeRev.app – Code Review as Interview

I've long had a dislike for leetcode interviews on both sides of the coin. Project-based interviews can also be challenging because it can end up filtering out folks who don't want to spend several hours building something in their free time. I met up with a friend last year -- a very senior dev -- who had taken some time off to study leetcode exercises while preparing for FAANG interviews. It struck me that one of the key measures of whether a candidate is a fit for a team is rather synthetic. CodeRev.app is a simple, lightweight tool that helps teams evaluate candidates using code reviews.…

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In plain words

CodeRev.app is a tool for evaluating job candidates through code reviews instead of traditional leetcode or project-based interviews. It's designed for hiring teams who want to assess candidates based on real collaborative work—how they read code, provide feedback, and communicate—rather than synthetic coding challenges. The platform aims to reduce barriers to participation while giving a more authentic picture of a candidate's day-to-day working style.

written from the facts on this page · September 2026

From the sources

In the maker’s words, at launch

I've long had a dislike for leetcode interviews on both sides of the coin. Project-based interviews can also be challenging because it can end up filtering out folks who don't want to spend several hours building something in their free time. I met up with a friend last year -- a very senior dev -- who had taken some time off to study leetcode exercises while preparing for FAANG interviews. It struck me that one of the key measures of whether a candidate is a fit for a team is rather synthetic. CodeRev.app is a simple, lightweight tool that helps teams evaluate candidates using code reviews. While programming tends to be a more isolated activity, code reviews tend to be more open ended, collaborative, and reflective of how a candidate communicates, interacts, and provides feedback day-to-day. It may also be a better yardstick for roles that are biased towards reading code rather than writing code (engineering manager, support, QA). More interesting is that as we come to rely on AI generated code in our workflows, testing for the ability to read and evaluate the quality of generated code and whether it is fit-for-purpose becomes more important. Being able to quickly identify security flaws, logical flaws, and domain specific gaps (auditing, logging, etc.) becomes increasingly important. More in depth thoughts here: https://chrlschn.dev/blog/2023/07/interviews-age-of-ai-ditch...

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