AI fatigue Is real and nobody talks about it (siddhantkhare.com)

A recent introspective blog post highlights a growing concern in the AI/ML community: "AI fatigue." The author, an experienced AI infrastructure developer, shares personal experiences of increased exhaustion despite shipping more code than ever. While AI tools indeed streamline task completion, they inadvertently lead to heightened workloads and expectations, resulting in mental fatigue due to constant context-switching and extensive review demands. The author emphasizes that rather than solely being creators, engineers are becoming reviewers and quality controllers, which is emotionally taxing and mentally draining. This phenomenon exposes a paradox within the AI landscape: while AI enhances efficiency in producing outputs, it complicates the processes of coordination, evaluation, and coding integrity. The reliance on AI-generated code, often flawed and unpredictable, necessitates thorough scrutiny, which leads to decision fatigue and psychological stress for engineers. The author advocates for solutions that include adopting frameworks focused on long-term sustainability and recognizing that navigating this fast-evolving technological landscape requires a shift in mindset from reactive tool adoption to understanding foundational infrastructure. Such insights resonate deeply within the community, prompting a crucial conversation about the sustainability of work environments increasingly driven by AI capabilities.