3 Causes of AI Fatigue and How Developers Can Cope
- The faster AI tools become, the more workload actually increases
- Developers reduced to code reviewers, tired of inspection instead of creation
- A 30-minute timer and morning contemplation time can be the solution
The Paradox of More Work as AI Gets Faster
AI tools have significantly reduced work time. But the reality is the opposite. Developer Siddhant Khare addressed this phenomenon head-on in his blog.[Siddhant Khare]
When AI lowers production costs, people don’t work less, they work more. The key is that the costs of coordination, review, and decision-making actually increase.
Reviewer Fatigue and the Problem of Indeterminacy
Khare confesses that he has changed from a creator to an inspector. Creating gives energy, but reviewing takes it away. AI-generated code has unpredictable patterns, so you have to check it line by line.
The same prompt yields different results every time. The premise of “same input, same output” is broken, making debugging difficult.[Siddhant Khare]
The Trap of FOMO and the Prompt Spiral
New tools come out every week. Prompts refined over several weeks become useless with a single model update. Khare revealed that a prompt he worked on for two weeks backfired after an update.[Siddhant Khare]
His solution is simple. Try three times, and if it doesn’t work, write the code yourself.
Practical Coping Methods Found in Burnout
Khare experienced burnout at the end of 2025. He recorded maximum output, but his motivation was at rock bottom. The method he found was setting boundaries.
Limit AI usage to 30 minutes. Think without AI in the morning. Accept 70% quality results. Focus review energy only on key code paths.
Frequently Asked Questions (FAQ)
Q: What exactly is AI fatigue?
A: It is a state of cognitive overload that comes from using AI tools. Although the tool reduces work, the burden of review, coordination, and continuous learning increases overall fatigue. It is especially noticeable in occupations that use AI on a daily basis, such as developers.
Q: How can I reduce AI fatigue?
A: Time limits are key. Break up AI tasks into 30-minute chunks and secure time to think without AI in the morning. Limiting prompt iterations to 3 and not chasing new tools indiscriminately also helps.
Q: Is AI fatigue a temporary phenomenon?
A: It is a structural problem. As AI tools develop, indeterminacy and tool replacement cycles accelerate, and the review burden also increases. It is a long-term task for both individuals and organizations to create sustainable AI usage habits.
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References
- AI fatigue Is real and nobody talks about it – Siddhant Khare Blog (2026-02-09)
- AI Fatigue Is Already Here – Harvard Business Review (2024-09-13)
- Gartner Hype Cycle for AI – Gartner (2023-08-17)