Many engineering teams are rushing to implement AI coding assistants after hearing promises of 40% increased code output. However, this approach fundamentally misunderstands software delivery systems. When organizations optimize code writing speed without addressing actual bottlenecks, they create traffic jams of unfinished work rather than improving throughput.

The Theory of Constraints reveals a critical truth: every system has exactly one bottleneck. In most organizations, the constraint isn't writing code but understanding requirements and navigating post-code processes like reviews and deployments. Accelerating non-bottleneck steps simply increases work-in-progress without improving overall delivery speed or system quality.

This misguided approach leads to longer cycle times, rubber-stamped reviews, and complex code that nobody fully understands. Teams ship more features while delivering less value to users. Organizations focusing on AI code generation should examine their value streams, identify true constraints, and invest resources where they'll actually improve delivery rather than creating more inventory that sits unfinished.