How long before we stop reading the code?

Code review processes face significant challenges with the rise of AI-generated code, as these tools produce code faster than humans can effectively review it, creating a bottleneck that traditional methods cannot address. Research has shown that as changes grow larger, the quality of review comments declines, and AI tools have exacerbated this issue by increasing the volume of pull requests while prolonging review times. Relying on AI to review AI-generated code introduces problems such as non-determinism, intent misinterpretation, and blind spots due to the same model both generating and reviewing the code. To overcome these challenges, teams are advised to codify review feedback into deterministic checks, shifting human involvement to earlier stages where intent is defined, and utilizing AI where deterministic methods fall short. By moving the focus from code review to intent verification, teams can ensure that the final product aligns with the original purpose and constraints, allowing AI to assist in enforcing standards and verifying specifications without compromising quality.