The focus on AI writing code is narrow, as coding represents only 10-20% of the total software development effort. The most significant productivity gains will come from AI automating other critical, time-consuming stages like testing, security, and deployment, fundamentally reshaping the entire lifecycle.
Contrary to fears of job replacement, AI coding systems expand what software can achieve, fueling a surge in project complexity and ambition. This trend increases the overall volume of code and the need for high-level human oversight, resulting in continued growth for developer roles rather than a reduction.
While AI accelerates code generation, it creates significant new chokepoints. The high volume of AI-generated code leads to "pull request fatigue," requiring more human reviewers per change. It also overwhelms automated testing systems, which must run full cycles for every minor AI-driven adjustment, offsetting initial productivity gains.