Theory of constraints, AI, and code review
TLDR Dev
An article argues that despite AI enabling engineers to write code 50% faster and complete 26% more coding tasks, company-level shipping speed has barely improved because code review has become the bottleneck in software development pipelines. Studies show AI productivity gains are marginal at 0.4% to 4% across various measures, and the constraint applies theory suggests optimizing the slowest part of the system—in this case, code review speed—rather than just accelerating code generation. The author recommends teams spend less time generating code and more time reviewing it through quality gates like testing, screenshots, and knowledge sharing, while cautioning against fully automating code review since it eliminates valuable mentorship between senior and junior engineers.
Why it matters
Startups experiencing hypergrowth may produce more code due to advancements like AI, but this doesn't necessarily translate to faster shipping or increased productivity, as the real bottleneck lies in the code review process. Even with higher individual productivity, companies often struggle with long review times, leaving them overwhelmed with pull requests and reducing overall progress.
