What causes AI fatigue for engineers and how to ease the strain

Thoughtbot's report on AI fatigue for engineers highlights that “most feel pressure to assess every AI trend, struggle to evaluate tools, and wrestle with evaluating AI‑generated code,” underscoring a growing burnout among development teams. For website owners, this fatigue translates into a slowdown in the adoption of new AI‑driven plugins, crawlers, and content generators. Fewer engineers will be experimenting with experimental AI bots, which can reduce unexpected AI traffic spikes but also means fewer fresh integrations that could boost SEO or personalization. At the same time, teams that do deploy AI tools are likely to be more selective, favoring proven, well‑documented bots that respect site policies. This shift makes it critical to maintain a clear llms.txt file and to monitor bot behavior closely, as the remaining AI traffic will be more concentrated and potentially more impactful. **Actionable tips:** 1. **Audit and tighten your llms.txt** – list only the vetted AI bots you want to allow, and explicitly disallow generic “AI‑crawler” user‑agents that may be used by fatigued developers experimenting with low‑quality tools. 2. **Implement granular bot analytics** – use server logs or a bot‑management platform to flag sudden increases in AI‑generated requests, enabling you to react quickly if a fatigued team inadvertently releases a noisy bot. 3. **Create a “bot health dashboard”** – track response times, error rates, and content‑type usage for each allowed AI bot, so you can spot performance degradation before it harms user experience or SEO.