Merge is a online code review assessment that helps engineering teams assess engineering judgement. With Merge, candidates review a PR, just like on the job. Then, our AI agent addresses PR comments in realtime, simulating a real engineer. At the end, we assess bug coverage, communication, PR quality, and token use efficiency.
We’re 5 founders who’ve collectively done over 250 interviews - everywhere from startups to FAANG+ to quant shops. Most of the interviews we’ve done were Leetcode based or tested skills that weren’t used on the job.
Meanwhile, at each of our companies, though, PR counts have nearly tripled. Most of us haven’t manually edited a line of code in a year. Our teams are putting more and more emphasis on code and architecture reviews, yet hiring processes haven’t changed whatsoever.
Even the AI-assisted ones we’ve done still assess code output as the primary evaluation metric. As agents develop, we truly believe this will not be the most challenging ability for an engineer to have.
We’ve seen that the real difficulty with using AI is not just reviewing code your AI generates; it's reviewing code that another engineer’s AI has generated, having little context yourself.
That’s why we’re launching Merge today: to help hiring teams assess engineering judgement. Here’s how it works:
1. Candidates are shown a small codebase to understand and a PR to review and comment on.
2. An AI agent addresses each PR comment via a code change or reply, simulating a real engineer.
3. Candidates can repeat until 5 revisions are used up or time runs out.
Throughout this process, we assess the following:
1. Coverage - How many bugs or vulnerabilities did the candidate identify and address?
2. Communication - Was the candidate efficient and constructive with their feedback?
3. Efficiency - How many revisions and tokens did the review take?
We’re the first platform that can show you exactly how efficient a candidate is with token use, LLM costs, and PR revisions — all of which are becoming exceedingly important in industry positions.
If you’re interested in the next-generation of engineering hiring, book a demo with us! Feel free to ask any questions below as well.
how do you stop a candidate from just running the take home assessment through an AI code review tool of their own before submitting it back to you? feels like an arms race where both sides eventually just have AI grading AI
About Merge on Product Hunt
“AI-native code review assessments”
Merge launched on Product Hunt on August 7th, 2026 and earned 111 upvotes and 5 comments, placing #10 on the daily leaderboard. Merge is a online code review assessment that helps engineering teams assess engineering judgement. With Merge, candidates review a PR, just like on the job. Then, our AI agent addresses PR comments in realtime, simulating a real engineer. At the end, we assess bug coverage, communication, PR quality, and token use efficiency.
Merge was featured in Hiring (15.4k followers), SaaS (43.5k followers) and Developer Tools (517.2k followers) on Product Hunt. Together, these topics include over 139.9k products, making this a competitive space to launch in.
Who hunted Merge?
Merge was hunted by Harshith Latchupatula. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Merge stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Harshith Latchupatula
Hey ProductHunt 👋!
We’re 5 founders who’ve collectively done over 250 interviews - everywhere from startups to FAANG+ to quant shops. Most of the interviews we’ve done were Leetcode based or tested skills that weren’t used on the job.
Meanwhile, at each of our companies, though, PR counts have nearly tripled. Most of us haven’t manually edited a line of code in a year. Our teams are putting more and more emphasis on code and architecture reviews, yet hiring processes haven’t changed whatsoever.
Even the AI-assisted ones we’ve done still assess code output as the primary evaluation metric. As agents develop, we truly believe this will not be the most challenging ability for an engineer to have.
We’ve seen that the real difficulty with using AI is not just reviewing code your AI generates; it's reviewing code that another engineer’s AI has generated, having little context yourself.
That’s why we’re launching Merge today: to help hiring teams assess engineering judgement. Here’s how it works:
1. Candidates are shown a small codebase to understand and a PR to review and comment on.
2. An AI agent addresses each PR comment via a code change or reply, simulating a real engineer.
3. Candidates can repeat until 5 revisions are used up or time runs out.
Throughout this process, we assess the following:
1. Coverage - How many bugs or vulnerabilities did the candidate identify and address?
2. Communication - Was the candidate efficient and constructive with their feedback?
3. Efficiency - How many revisions and tokens did the review take?
We’re the first platform that can show you exactly how efficient a candidate is with token use, LLM costs, and PR revisions — all of which are becoming exceedingly important in industry positions.
If you’re interested in the next-generation of engineering hiring, book a demo with us! Feel free to ask any questions below as well.