Why AI Coding Falls Short of Its Promised Efficiency in Complex Enterprise Systems
Although AI coding agents like Claude Code and Codex promise dramatic productivity gains, the article explains that in large‑scale enterprise software the benefits are limited by unclear requirements, extensive context engineering, hidden token and rework costs, subtle bugs that pass superficial tests, and the need for strict risk‑tiered usage and human‑AI collaboration.
