Agentic AI Coding Boom Creates Review Bottleneck and Reliability Concerns

The rise of agentic AI coding tools, which operate on high-level goals rather than simple line completion, has pushed code production to machine speed but introduced what researchers term the Productivity-Reliability Paradox. While individual developer productivity has risen by over 50%, organisations are reporting a 98% surge in merged pull requests alongside a 91% increase in review time, straining system-level reliability. Traditional line-by-line code review has become unsustainable, prompting a shift from humans being directly involved in every review cycle to overseeing the process at a higher, supervisory level. Engineers are responding by designing automated workflows that let AI agents find, implement, and verify work independently, supplemented by automated verification gates for logic and edge-case checks. A key hidden cost, dubbed the Verification Tax, is that senior developers often spend more time auditing AI-generated code than they would have spent writing it themselves, a burden that grows with codebase complexity.