Blog
Who Reviews the AI Reviewer? AI Code Review & Software Engineering
Who Reviews the AI Reviewer?
AI can write the code. AI can review the code. So who reviews the reviewer? AI is becoming part of more stages of software development — from writing and debugging code to testing and code review. That creates a new engineering question: If AI is reviewing code, how do we know the AI reviewer is actually good at reviewing it? |
AI code review is becoming part of the workflow
The shift is already measurable. According to the 2026 Stack Overflow Developer Survey, 66% of respondents use AI coding assistants or coding agents, while 26.2% use AI agents or automated workflows. Stack Overflow Developer Survey |
The same survey found that 44.9% of respondents had delegated reviewing code, pull requests or technical changes to AI tools or agents in the previous 30 days. Stack Overflow Developer Survey So AI-assisted code review isn’t just a theoretical idea. It is becoming part of how developers work. But adoption creates another problem: How do you evaluate the evaluator? |
Enter ReviewBench
On 5 October 2026, GitHub launched ReviewBench, an open benchmark designed specifically to evaluate AI code-review agents. Rather than simply asking whether an AI can produce a review, ReviewBench looks at what different AI reviewers catch, what they miss and how much noise they generate. The benchmark uses representative GitHub pull requests, multiple sources of ground truth and production-oriented evaluation metrics. The GitHub Blog That’s important because a useful code reviewer isn’t necessarily the one that produces the most comments. A good reviewer needs to help identify meaningful problems while avoiding unnecessary noise. |
More AI doesn't automatically mean safer software
Imagine a development workflow like this: Human → AI generates code → AI reviews code → automated tests → human decision It sounds efficient. But every automated step introduces another system that needs to be evaluated. An AI reviewer could potentially miss a subtle security issue, misunderstand the intended behaviour, or flag something that isn’t actually a problem. That’s why verification still matters. Stack Overflow’s 2026 survey found that 48% of respondents trust AI output when they can easily verify it, while only 6.6% say they trust AI for many tasks including important work decisions. Stack Overflow Developer Survey The message isn’t that AI code review doesn’t work. It’s that trust shouldn’t come from automation alone. |
The future of code review may be human + AI
AI can make code review faster. It can help developers scan changes, identify potential problems and focus attention where it matters. But the goal shouldn’t be: “Let AI review everything.” It should be: “Use AI to expand what engineers can review — while keeping engineering judgment in the loop.” As AI takes on more responsibility in software development, measuring, testing and validating the AI itself becomes part of engineering. Because eventually, someone still needs to ask: “Are we confident enough to ship this?”And that’s a question worth keeping a human in the loop for. |