The growing divide between AI hype and software engineering reality

The article argues that the gap between AI hype and day-to-day software engineering reality is widening: while LLMs can accelerate some tasks, many open source maintainers are banning or tightly restricting AI-generated contributions because they increase review burden, introduce quality and security risks, and create more low-value work for experts. For CIOs and technology leaders, the key implication is that AI adoption in IT should be governed by clear quality controls, human accountability, and use-case-specific policies rather than assumed productivity gains. Organizations that rely on AI for code, documentation, or support content will need stronger review standards, better developer training, and explicit rules to prevent “AI slop” from degrading engineering throughput and trust.