AI fatigue is real and nobody talks about it
siddhantkhare.com
February 8, 2026
19 min read
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66/100
Summary
AI fatigue affects developers who are deeply involved in AI projects, leading to increased workload and emotional drain despite higher productivity. Siddhant Khare has shipped significant code and contributed to various AI infrastructure projects, including OpenFGA and agentic-authz.
Key Takeaways
- AI tools can significantly reduce the time required for individual tasks, but they lead to increased cognitive load due to the need for constant context-switching between multiple tasks.
- The shift from being a creator to a reviewer in the engineering process results in decision fatigue, as engineers must evaluate and judge AI-generated outputs rather than solely focusing on creation.
- The paradox of AI is that while it enhances productivity by speeding up task completion, it simultaneously raises the demands on human coordination and evaluation, leading to increased exhaustion.
- Engineers using AI extensively report feeling more drained despite increased output, highlighting a disconnect between productivity and mental well-being in the AI-driven work environment.
Community Sentiment
Positives
- Despite the fatigue, many users are able to make meaningful progress on multiple projects in a single day, showcasing the potential of AI to enhance productivity.
- The discussion highlights the need for a new balance in working practices, indicating that AI tools can lead to innovative workflows if managed correctly.
Concerns
- The unpredictability of LLM response times disrupts workflow, causing frustration and preventing users from achieving a productive flow state.
- Constantly reviewing AI output leads to decision fatigue, suggesting that while AI can assist, it also adds cognitive burdens that can overwhelm users.
