Code review is becoming the most important decision-making surface in software engineering, and it’s outgrowing the diff. The assumption was always that code review exists to catch bugs. Its real job is taste, judgment, and applying organizational processes: Is this the right thing for our product?<\/p>\n\n\n\n
Now that AI writes thousands of lines of code in minutes, and there\u2019s no way engineers can keep up with the review, engineering teams are stuck between two bad options: skip code review and risk shipping slop, or keep reviewing everything and become the bottleneck. That\u2019s why conversations about reviewing AI code keep going in circles – everyone is arguing about a different part of code review.<\/p>\n\n\n\n
Strip away line-by-line inspection, and code review still does three things that teams need.<\/p>\n\n\n\n
First, it’s a place to collaborate.<\/strong> This is where teams come together to decide what belongs in the product.<\/p>\n\n\n\n The second role of code review is alignment and knowledge sharing.<\/strong> Every review builds shared context about the changes happening to a code base and the underlying business needs. This context is increasingly important for both people and agents and carries the institutional knowledge and historical considerations for the product and organization.<\/p>\n\n\n\n Its third function is verification:<\/strong> Is the code correct? Will it work? What’s the risk?<\/p>\n\n\n\n These three jobs don’t go away when AI generates the code. If anything, they become more important because the volume of code demanding review is growing faster than the number of people available to review it. Code review was never strictly about reviewing code. Is this even the right name for it? Code is the medium, but the review is where we exercise judgment, and it\u2019s still important.<\/p>\n\n\n\n