How long until we stop reviewing code?

A viral discussion among software engineers is sounding the alarm that traditional manual code review is becoming an unsustainable bottleneck in the age of AI-assisted development. The core argument, gaining traction on platforms like Reddit, is that two factors are scaling exponentially: the sheer number of code changes being produced and the size of individual changes, often generated by tools like GitHub Copilot or GPT-4. Developers cannot manually consume this volume, and many report that reviewing AI-generated code actually requires *more* cognitive effort than reviewing code from colleagues, as it often lacks contextual understanding and may introduce novel, non-idiomatic patterns. This creates a paradoxical scenario where teams produce more code but then spend disproportionately more time scrutinizing it, leading to burnout and delays.

The implication is that the historical code review process—an approval gate designed for human-paced, collaborative development—is fundamentally mismatched to the new shape of work. The post argues there is 'no way we win this fight' with current manual methods. This forces a critical industry conversation about the future of software quality assurance. The path forward likely involves augmenting or replacing manual review with automated, AI-powered analysis tools that can scale, focusing human attention on high-level architecture, security, and business logic rather than line-by-line syntax. The next evolution may see 'review' shift from pre-merge approval to continuous, automated validation and post-merge monitoring, fundamentally redefining developer workflows and team responsibilities.